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Abstract

As organizations continue to embrace digital transformation, the need for robust cybersecurity strategies has never been more critical. This paper explores the Zero Trust Architecture (ZTA) as a contemporary cybersecurity framework that addresses the challenges posed by increasingly interconnected systems. Zero Trust (ZT) operates under the principle of “never trust, always verify,” ensuring that every access request is thoroughly authenticated, regardless of the requester’s location within or outside the network. However, implementing ZT is a challenging task, requiring an adequate roadmap to prioritize the different initiatives in agreement with company culture, exposure and cyber posture. We apply multi-criteria decision analysis (MCDA) to evaluate the relative importance of various components within a ZT framework, using the Incomplete Analytic Hierarchy Process (IAHP). Expert opinions from professionals in cybersecurity and IT governance were gathered through structured questionnaires, leading to a prioritized ranking of the eight key ZT pillars, as defined by the Cybersecurity and Infrastructure Security Agency (CISA), Washington, DC, USA, along with a prioritization of the sub-elements within each pillar. The study provides actionable insights into the implementation of ZTA, helping organizations prioritize security efforts to mitigate risks effectively and build a resilient digital infrastructure. The evaluation results were used to create a prioritized framework, integrated into the ZEUS platform, developed with Teleconsys S.p.A., to enable detailed assessments of a firm’s cyber partner regarding ZT and identify improvement areas. The paper concludes by offering recommendations for future research and practical guidance for organizations transitioning to a ZT model.

1. Introduction

Nowadays, businesses and institutions are increasingly digitalizing, with digital networks becoming highly interconnected. While this represents a significant step forward in innovation, it also expands the risk perimeter. An attack on a single part of the network can quickly spread, endangering the entire digital ecosystem. As a result, cybersecurity today focuses not only on defending existing IT infrastructures with robust strategies but also on anticipating and mitigating risks associated with ongoing technological innovation. This includes the development of artificial intelligence to predict attacks, behavioral analysis to detect suspicious activities, and the use of blockchain to ensure the integrity and traceability of information. In this way, cybersecurity continues to evolve in response to the challenges posed by a rapidly changing technological landscape, seeking to predict future threats rather than simply reacting to existing ones [1].

The Zero Trust (ZT) approach, introduced in 2010 by John Kindervag of Forrester Research, was developed to address the growing permeability of network perimeters [2]. Unlike traditional security models, which focus on defending only the outer perimeter, ZT promotes continuous, granular protection by eliminating implicit trust in internal devices and users [3]. The rise of remote work due to the COVID-19 pandemic has further expanded the attack surface for cybercriminals, with remote connections and company data on personal devices. This has led to a resurgence of the ZT security approach, which asserts that no user, device or network, whether internal or external, should be trusted without strict verification through mechanisms like strong authentication, resource segmentation and continuous monitoring [4]. The core principle of ZT is that there are no inherently secure networks, and the physical location of users or devices within the organization’s perimeter is not a reliable indicator of security [4]. In this model, trust is never assumed; access is granted only after rigorous verification at every point. ZT philosophy moves from a monolitic vision of cybersecurity to a granular approach where access to each digital resource is strictly based on a need-to-use perspective. In this way, cybersecurity is strongly tailored to the company’s needs and organization. Effectively implementing ZT can lead to a variety of advantages, including increased efficiency, better user experiences, lower IT expenses, more adaptable access and strengthened security.

The ZT principle does not apply to a single product, technology or architecture layer; rather, it represents a security framework for protecting infrastructure and data [5,6]. A Zero Trust Architecture (ZTA) has been described as one with security applied everywhere and without the implicit trust that might be common in legacy network architectures. The National Institute of Standards and Technology (NIST), Gaithersburg, MD, USA, provides guidelines for the design and implementation of ZTA in the document NIST SP 800-207 [7].

ZT is not a monolithic solution, but a strategic framework composed of multiple interconnected domains that can be prioritized and implemented differently depending on the organization’s specific context.

Various approaches exist for implementing ZT [8]. The Department of Defense (DoD) has developed a ZT model in which each ZT capability is broken down into a series of associated activities, resulting in a total of 152 distinct activities [9]. Despite the comprehensiveness of this model, the sheer volume of required activities poses a challenge. In response to this complexity, the Cybersecurity and Infrastructure Security Agency (CISA) has defined eight fundamental pillars towards the adoption of ZT: Applications, Automation and Orchestration, Contractors and Vendors, Data, Devices, Network Infrastructure, Users and Visibility and Analytics. While each of these domains contributes to the overall security posture, their relative importance may vary across organizations based on business objectives, risk tolerance and technological maturity. Typically, ZTAs are assessed using predefined models called maturity models on the basis of specific elements [10]. CISA has defined a maturity model that classifies initiatives into four levels, ranging from “traditional” to “optimal”. The four-step evaluation process proposed by CISA for each initiative, namely Initiation, Implementation, Optimization and Measurement, is valuable for tracking progress, but does not provide an effective roadmap to reach an adequate security posture, as it lacks detailed guidance on which aspects should be prioritized within each level in the ZT-implementation journey. Without a clear prioritization framework, organizations may face challenges in deciding which initiatives should be addressed first. To address this gap, we employ multi-criteria decision analysis (MCDA) to implement a prioritization strategy, incorporating expert input to guide the process. We utilize MCDA to assess the relative importance of various components within a ZTA, based on expert opinions from cybersecurity professionals. We employ the Incomplete Analytic Hierarchy Process (IAHP) [11,12,13], a systematic decision-making methodology that allows for the evaluation of complex, multi-dimensional problems by breaking them down into smaller, more manageable sub-criteria. The MCDA framework is applied to identify which components of a ZT framework are considered the most critical for securing organizational infrastructure, thereby enabling one to identify the most suitable roadmap to effectively implement ZT. To the best of our knowledge, this is the first contribution that applies AHP within the context of ZT.

By gathering data through structured questionnaires distributed to professionals with expertise in cybersecurity and IT governance, we provide a data-driven analysis that helps to prioritize the elements of ZTA. Specifically, we examine the common key pillars along with sub-criteria within each of these pillars. The expert-driven approach not only captures insights into the current state of ZTA implementation across various sectors but also highlights emerging trends and priorities in ZT adoption.

The values obtained from this evaluation were utilized to create a prioritized framework, which is embedded into the ZEUS platform, developed in collaboration with Teleconsys S.p.A., Rome, Italy, to enable detailed and systematic assessments of a firm’s cyber partner with respect to ZT and how to identify areas for improvement [14]. This platform addresses this issue by ranking the different cyber controls on the basis of their actual degree of implementation and consider the relative relevance of the different controls, helping organizations focus on the most critical initiatives and improving the efficiency of their security strategies.

The results of this study offer actionable guidelines for organizations seeking to implement or improve their Zero Trust strategy. By understanding the relative significance of each component, decision-makers can focus on the most critical areas first, ensuring a phased and efficient deployment of ZT principles. Ultimately, this paper contributes to both the theoretical understanding and practical application of ZTA, assisting organizations in navigating the complexities of modern cybersecurity challenges.

This research provides a significant contribution to understanding the implementation of the Zero Trust model, with a particular focus on identifying priorities during the transition from a traditional architecture to a ZTA. By employing an innovative approach based on MCDA, this study offers a practical framework to guide organizations in prioritizing key security pillars throughout the adoption process of Zero Trust, thereby advancing knowledge in the field of cybersecurity.

The paper is structured as follows: Section 2 introduces the ZT model, its core principles and the eight key pillars as defined by CISA; Section 3 discusses the NIST framework for ZT, including an example of a typical ZTA and its operational workflow; Section 4 explains the methodology of the study, including the application of MDCA and IAHP, and presents the results of the data analysis; Section 5 concludes with a discussion of the findings and recommendations for future research.

2. Zero Trust Architecture: Principles and Pillars

ZTA is a cybersecurity model that operates under the assumption that threats exist both inside and outside the network. It emphasizes the necessity for strict verification and continuous monitoring to safeguard data, applications and services. This section outlines the core principles and foundational pillars that constitute a robust ZT framework.

2.1. Foundational Pillars of Zero Trust

Although not mandatory, the US CISA and other Institutions strongly encourage to migrate toward a ZTA as a modern and proactive cybersecurity strategy. During the transition to this new model, organizations can assess the maturity of their implementation and identify priorities for future improvements by adopting Zero Trust maturity models (ZTMM) [15]. In the context of ZTA, several ZTMM have been developed to help organizations evaluate their current state and define actionable steps for advancement. Among the most widely recognized maturity models are those proposed by the CISA [16], NIST [17], Microsoft [18] and Palo Alto Networks [19].

CISA’s Zero Trust Maturity Model (ZTMM) evaluates organizations across four maturity levels: Traditional, Initial, Advanced and Optimal. The model is structured around five key pillars (i.e., Identity, Devices, Networks, Applications and Workloads and Data) which progress independently. CISA also includes three cross-cutting capabilities: Visibility and Analytics, Automation and Orchestration, and Governance, which enhance security by ensuring continuous monitoring, automated responses and robust policy enforcement. Microsoft’s ZTMM provides organizations with a tool to assess their Zero Trust posture across areas such as identity, endpoints, applications, infrastructure, data and networks. It follows a similar maturity progression to CISA, helping organizations gradually adopt ZT principles through a series of assessments and actionable steps, ultimately strengthening their security posture. NIST’s approach to Zero Trust emphasizes the need for a comprehensive risk assessment and a tailored implementation based on existing cybersecurity structures. NIST’s model is less structured in terms of predefined maturity levels but focuses on creating a phased, hybrid security model that evolves as organizations better understand their assets and vulnerabilities. Palo Alto Networks’ ZTMM also focuses on automation and integration, with a five-step maturity process: Initial, Managed, Defined, Quantitatively Managed and Optimizing. It stresses the importance of identifying critical assets and automating security processes to reduce human error and improve response times. While all these models share the core Zero Trust principle of “never trust, always verify,” they differ in their focus and approach. CISA and Microsoft provide structured models based on clear stages, while NIST takes a more flexible, principle-based approach. Palo Alto Networks emphasizes automation and integration, offering a technology-centric path to ZT. These variations allow organizations to select a model aligned with their specific security needs and infrastructure.

In this work, we adopt the guidelines provided by CISA. It is important to note that the ZTMM defined by CISA represents just one of many possible approaches that an organization may follow in designing and implementing its transition to ZT. While ZTMM is specifically tailored to meet the needs of U.S. federal agencies, as mandated by Executive Order (EO) 14028 “Improving the Nation’s Cybersecurity”, its structure and principles offer a valuable and adaptable framework for any organization aiming to strengthen its cybersecurity posture [16].

CISA’s ZTMM is structured around a maturity gradient applied to five core technological pillars: Identity, Devices, Networks, Applications and Workloads and Data. Each of these pillars is further evaluated through three cross-cutting capabilities: Visibility and Analytics, Automation and Orchestration and Governance (see Figure 1). Collectively, these eight elements were built upon the seven tenets of ZT outlined by NIST in NIST SP 800-207 and form a comprehensive foundation for ZT implementation [20,21]:

• User Identity
  This pillar focuses on user identification, authentication and access management. It involves incorporating access control policies to validate users that connect to the network, utilizing dynamic and contextual data analysis to ensure that the right users receive access at the right time.
• Device Security
  Device security, also known as endpoint security, involves the validation of user-controlled and autonomous devices to ensure their trustworthiness. It presupposes that companies secure all devices, including laptops, mobile phones, servers and IoT devices, to prevent unauthorized devices from accessing the network.
• Application Security
  The application security pillar encompasses the protection of all applications, both local and cloud-based. It requires adopting security and preventative measures for each compute container and workload to avoid unauthorized access across the network.
• Data Security
  The data security pillar focuses on data categorization and isolation from everyone except those who require access. It involves data encryption, information rights management, data-loss prevention and compliance with industry standards.
• Network Security
  Network security involves isolating sensitive resources, deploying micro-segmentation techniques and managing network flow. It also requires the encryption of end-to-end traffic to avoid unauthorized access.
• Automation and Orchestration
  This pillar concerns the automation of security and network operational processes across ZTA, achieved by orchestrating functions between disparate and similar security systems and applications.
• Visibility and Analytics
  Visibility and analytics provide insights into system and user behavior by observing real-time communications between each component of ZTA, enabling proactive threat detection and response.
• Governance (Contractors and Vendors)
  Governance refers to the definition and associated enforcement of agency cybersecurity policies, procedures and processes, within and across pillars, to manage an agency’s enterprise-wide environment and mitigate security risks in support of ZT principles and fulfillment of federal requirements.

These principles and pillars collectively form the foundation of a ZTA, ensuring that every component, from applications and devices to contractors and vendors, is continuously authenticated and monitored. By adopting these principles and implementing these pillars, organizations can create a comprehensive security framework where access is strictly controlled, monitored and validated at every stage, ensuring that no element of the network is trusted by default.

2.2. Zero Trust Maturity Evolution

The progression of organizations from traditional enterprise security to a modern ZT environment involves a transition toward greater automation, dynamic updates and integrated security capabilities. This evolution can be measured in accordance with CISA’s maturity model [16], as shown in Figure 1, which are not strictly linear and may differ in scope and complexity over time.

Each stage provides specific criteria to help organizations assess their maturity level within each ZT technology pillar:

• Traditional: Security configurations and access policies are manually managed and isolated across systems, offering limited visibility and static enforcement. Least privilege is applied only at the time of provisioning.
• Initial: Organizations begin to introduce automation in lifecycle management, policy enforcement and visibility. Some integration across pillars emerges, along with adaptive privilege adjustments post-provisioning.
• Advanced: Automated controls and policies are coordinated across pillars; identity and visibility are centrally managed, and enforcement becomes adaptive based on risk and posture assessments.
• Optimal: Full automation is achieved, with self-updating assets, real-time policy adjustments, dynamic least privilege access and continuous monitoring enabling enterprise-wide situational awareness and cross-pillar interoperability.

Note that as emphasized also by the main change in the Version 2.0 of the NIST Cybersecurity framework [17], a large part of the model is focalised on the “government” of the cybersecurity issue. This maturity framework offers a structured path for organizations to systematically advance their ZT implementation over time.

3. The NIST Framework for ZTA

The NIST defines a comprehensive framework for ZTA, which provides the theoretical foundation for implementing ZT principles in network security [17]. The NIST framework comprises three key components:

• Policy Engine (PE): The PE serves as the evaluator of the system. It queries and analyzes company policies and employs a Trust Algorithm (TA) to determine whether the user or device requesting access to resources is legitimate and reliable. The PE plays a crucial role in evaluating the trustworthiness of the subject before access is granted.
• Policy Administrator (PA): The PA can be integrated with the PE and acts as the system’s decision-maker. It authorizes or denies access to resources based on the assessments provided by the PE. The PA ensures that access decisions align with the organization’s security policies and regulations.
• Policy Enforcement Point (PEP): The PEP is the component that monitors and manages communication between the subject and the resource. It enforces the access decisions made by the PA, ensuring that appropriate security controls are applied when granting or denying access.

In addition to these core components, the NIST framework recognizes the need for supplementary tools to facilitate the implementation of ZT. These tools include systems for multi-factor authentication, identity and information management, and Security Information and Event Management (SIEM). These components help enforce continuous authentication and monitoring, as well as detect and respond to potential security events in real time [7].

These include internal and external data sources such as:

• Continuous Diagnostics and Mitigation (CDM) System: this provides information about asset states, including security patches, vulnerabilities and unauthorized components, helping enforce policies on nonenterprise devices.
• Industry Compliance System: this ensures regulatory compliance by applying policy rules aligned with frameworks like Federal Information Security Modernization Act (FISMA) and healthcare security standards [22].
• Threat Intelligence Feeds: this offers real-time data on vulnerabilities, malware and attacks to help the policy engine deny access from compromised assets.
• Network and System Activity Logs: this aggregates logs and network traffic to give real-time insights into the security posture of systems.
• Data-Access Policies: this defines rules for resource access based on user roles and needs, forming the basis for granting permissions.
• Enterprise Public Key Infrastructure (PKI): this manages certificates and authentication within the organization and external ecosystems for secure communication.
• Identity-Management System: this handles user accounts and roles, integrating with PKI to manage access attributes and roles.
• SIEM System: this collects and analyzes security data, refining policies and detecting potential threats.

Different approaches to ZTA, such as identity governance-driven, micro-segmentation or network-based segmentation, use these components in varying degrees to create a secure, ZT-enabled environment.

The ZTA represents a shift in the security paradigm. It incorporates a range of tools and technologies, which can be deployed gradually and customized based on the organization’s needs. Notably, ZT does not require distinct devices for each function. For example, in many cases, the processes of the PE and PA can be carried out by the same tool. However, it is essential that the architecture follows the core Zero Trust principles, adapted to meet the specific needs of the organization.

The transition from a perimeter-based security model to a ZT architecture does not focus on replacing existing tools. Instead, it represents a shift in the fundamental approach to security. This transition involves three critical steps: identifying company actors and assets, conducting a risk assessment and prioritization, and developing and validating new security procedures.

ZTA can be implemented through several approaches: user management, network micro-segmentation and software-defined perimeters. These approaches are not mutually exclusive, and the extent to which each is implemented will depend on the company’s existing infrastructure and security requirements.

Practical Example of ZTA and the Operational Workflow

A typical implementation of a ZT model is illustrated in Figure 2, which shows the various components and the workflow of a ZTA. The diagram describes how, step by step, the different systems and processes collaborate to ensure that access to enterprise resources is granted only after a thorough security assessment.

An Untrusted subject attempts to access an Enterprise resource. The access request is sent to the Policy decision/enforcement point, which is the point where security policies are enforced. Before making a decision, information is gathered from various external systems, including the Data-access policy, which defines the rules for data access, and Threat intelligence, which provides up-to-date information on threats and vulnerabilities. Activity logs and the Industry compliance system are also used to verify security and regulatory compliance.

During this process, the system leverages Public Key Infrastructure (PKI) to ensure secure and verified authentication of the subject. The PKI system validates the identity of the user or device through public key-based authentication, ensuring that only authorized entities can proceed with the access request.

The ID management system then manages the identities of users and devices, controlling access permissions based on the roles and policies established by the organization. This system ensures that only trusted users and devices are granted appropriate access over time.

The Policy engine is the central component that processes all this information, evaluating factors such as user authentication, the device’s status (e.g., whether it is up-to-date or secure) and regulatory compliance. After analyzing all the data, the policy engine determines whether the subject can be considered trustworthy and thus authorized to proceed.

If the subject is deemed trustworthy, the Policy decision/enforcement point implements the decision by applying the appropriate access policy. This may include resource segmentation, data encryption or other security controls. If access is granted, the subject gains access to the enterprise resource; otherwise, if the subject does not meet security requirements, access is denied.

Finally, Security Information and Event Management (SIEM) is used to continuously monitor security events and analyze anomalies. After access is granted, SIEM plays a crucial role in detecting suspicious activities, ensuring that the access remains secure and unauthorized actions are swiftly identified and addressed.

Thus, Enterprise resources are protected by a system that includes PKI for public key-based authentication, ID management for managing user and device identities, and a SIEM system for security event management and anomaly analysis. All these components work together to ensure that only trusted users and devices are allowed to access enterprise resources.

There are various methods an enterprise can use to implement ZTA for its workflows. These methods differ in the components utilized and the primary sources of policy rules within the organization. While each method adheres to the core principles of ZT (as outlined in Section 2.1), they may prioritize one or two components as the main drivers of security policies. A comprehensive ZT solution typically incorporates elements from all three approaches: enhanced identity governance, logical micro-segmentation and network-based segmentation.

4. Comparing ZTA Domains Through IAHP-Based Multi-Criteria Decision Analysis

As aforementioned, the transition from a traditional setup to a ZTA is a gradual process, not an immediate shift. Thus, in the context of implementing ZTA, determining the weights of various controls through MCDA is essential for prioritizing security measures effectively. Given the complexity and resource constraints organizations often face, it is crucial to identify which security controls will provide the most significant impact in enhancing the organization’s security posture. Moreover, organizations can choose to implement only certain elements of ZTA, as ZTA includes multiple techniques. By assigning appropriate weights to each control, decision-makers can focus on implementing the most critical measures first, ensuring a structured and efficient approach to achieving a robust ZTA. This prioritization process aids in aligning security efforts with organizational goals and risk-management strategies, ultimately leading to a more resilient and secure infrastructure.

4.1. Description of the Evaluation Criteria

As mentioned above, the aim of this work is the evaluation of the implementation of a ZTA using IAHP. In this model, the primary evaluation criteria are the eight pillars of ZTA, with each pillar further evaluated through its respective controls. These controls are essential security measures that organizations must meet within each pillar to ensure robust protection and compliance with ZT principles. These controls have been taken from the CISA Maturity Model Framework [16] and have been appropriately adapted and extended to account for the requirements of the EU Directive NIS2 [24]. Below, we outline the specific controls for each pillar (see Figure 3):

• User:
  • User Inventory—All users must be registered and inventoried to ensure proper monitoring and management.
  • Multi-Factor Authentication (External)—External access to resources must be protected with multi-factor authentication to verify the identity of users.
  • Multi-Factor Authentication (Internal)—Internal resources should also use multi-factor authentication for added security within the organizational network.
  • Identity Access Management (IAM)—A robust system for managing user identities and access to resources is essential, ensuring that only authorized personnel can access critical assets.
  • Identity Governance and Administration (IGA)—An IGA system should be used to manage and enforce policies related to user identities and access rights.
  • Privileged Access Management (PAM)—A PAM system should be employed to manage and control privileged user access to critical systems and data.
  • Least Privilege—The organization must adopt the principle of least privilege, ensuring that users only have the minimum access necessary to perform their roles, and periodic reviews of user access should be conducted.
  • Real-Time Risk Detection—The organization must be able to detect user-related risks in real time through orchestrated and automatic processes, without relying on manual review.
  • IGA and PAM Integration—The IGA and PAM systems should be integrated to manage the lifecycle of privileged administrative user accounts.
• Devices:
  • Smart Access Governance—Access to corporate resources from external devices must be controlled and monitored.
  • Inventory—All devices owned by the organization must be inventoried.
  • Mobile Device Management—Mobile devices should be managed and secured through an MDM system to control access to corporate resources.
  • Standard Configuration—All devices must be provided with a standard configuration to ensure security compliance.
  • Compliance—Devices owned by users (Bring Your Own Device—BYOD) must be continuously verified before being allowed to access corporate resources.
  • Conformity—Devices must comply with IT configuration policies before being granted access to the network.
  • Detection Tools—Endpoint detection and response tools must be used to monitor and respond to security incidents in real time.
  • Continuous Monitoring—The organization must continuously monitor device compliance with security standards, promptly identifying and addressing non-compliance.
  • Extended Detection and Response (XDR)—The organization must adopt solutions such as XDR to enhance threat detection and response capabilities.
  • MDR—The organization must implement Managed Detection and Response (MDR) solutions to continuously monitor the network for threats and provide expert-driven security operations.
• Data:
  • Data Classification—Structured data must be classified, tagged and access must be limited based on data sensitivity (DAM).
  • Unstructured Data Classification—Unstructured data must be classified, tagged and subject to access restrictions based on data sensitivity (DAG).
  • Cloud Security Posture Management (CSPM)—The organization must adopt a cloud security posture-management system to make informed decisions about data access.
  • Data Encryption at Rest—Critical or sensitive data at rest must be encrypted to prevent unauthorized access.
  • Data Encryption in Transit—Critical or sensitive data in transit must be encrypted to ensure data confidentiality and integrity.
  • Data-Loss Prevention (DLP)—The organization must apply DLP measures to monitor, alert and limit the flow of sensitive information (e.g., email blocking, upload or copying to USB).
  • Access Control to Data—Data access must be controlled through a request and approval process to ensure proper authorization.
  • Data Access Certification—The organization must implement a system for certifying data access rights and permissions.
• Applications:
  • Application Inventory—All applications within the organization must be inventoried to ensure security posture monitoring.
  • Access Control to Applications—The organization must implement an access control system based on application-specific criteria.
  • Session Control for Applications—The organization must apply session control measures for applications, such as limiting visibility or blocking downloads/uploads.
  • Application Performance Management (APM)—Critical applications must be monitored for performance metrics, ensuring that they meet required operational and security performance standards.
  • Workload Anomaly Detection—The organization must adopt a system for detecting anomalies in the behavior of workloads.
  • API Security—The organization must implement a system for API security to ensure secure data exchanges and interactions.
  • Security by Design—The organization must integrate security into the development lifecycle through a Security by Design methodology.
  • Software Risk Management—The organization must use a system for Software Risk Management to assess and mitigate software-related risks.
• Contractors and Vendors:
  • Assessment of Suppliers—The organization must provide questionnaires with minimum security requirements to the supply chain.
  • Assessment of Contractors—The organization must provide questionnaires with minimum security requirements to contractors.
  • Audit of Contractors—The organization must conduct audits on contractors to ensure security compliance.
  • Audit of Suppliers—The organization must conduct audits on suppliers to ensure security compliance.
  • Security Requirements for Suppliers—Security requirements for suppliers must be defined and enforced.
  • Security Requirements for Contractors—Security requirements for contractors must be defined and enforced.
  • Third-Party Risk—The organization must use a solution for managing risks related to third parties.
  • Third-Party Compliance Management—The organization must use an automated solution to manage third-party compliance.
• Network and Infrastructure:
  • Macrosegmentation—The organization must implement macrosegmentation to reduce the attack surface.
  • Microsegmentation—The organization must implement microsegmentation to enhance security at a granular level.
  • Access Control Based on Context—The organization must implement a system of access restrictions based on the context of access requests.
  • Encrypted Network Traffic—Network traffic must be encrypted to prevent unauthorized access.
  • Next-Generation Firewalls—Network entry and exit points must be protected by next-generation firewalls.
  • Cloud Architecture Risk Profile—The organization must be aware of the risk profile of its cloud architecture and develop a cloud infrastructure protection plan.
  • Cloud SIEM Capability—The organization must have the capability to detect and respond quickly to security incidents (SIEM) in a cloud environment.
  • Secure Web Gateway (SWG)—Access to cloud services must be protected by a secure web gateway.
  • Vulnerability Management—The organization must implement a vulnerability-management solution to ensure that security vulnerabilities are identified on any infrastructure device and remediated within a set timeframe (e.g., 48 h).
  • Service Continuity—The organization must have mechanisms to ensure the continuity of perimeter services even in the case of severe hardware failures or incidents. Both the plan and testing must be in place.
  • Disaster Recovery (DR)—The organization must implement disaster recovery mechanisms, with a regularly tested and documented infrastructure. The DR infrastructure should be located at an adequate distance, physically and logically isolated from the primary site, and resilient even in the event of targeted cyberattacks.
  • Cyber Recovery and Backup Technology—The organization must implement a cyber recovery plan and technology, validate its operation and monitor performance metrics. Backup snapshots must be cloned in isolated environments for security testing. Forensic investigations must be conducted on infected snapshots in isolated environments while recovery is ongoing.
  • Stateless Firewalls—type of firewall that filters network traffic based solely on pre-defined rules, without keeping track of the state of active connections. It treats each packet individually, independently of previous packets, making decisions based only on factors like source/destination IP addresses, ports, and protocols.
  • Rapid Reaction to Incidents—The organization must ensure that rapid response capabilities are in place to handle incidents affecting critical infrastructure.
  • Immutable Snapshots—The organization must utilize technologies that allow the creation of immutable backup snapshots, providing a reliable method for restoring data after a breach.
  • Snapshot Backup Cloning—The organization must clone backup snapshots in isolated environments to speed up security testing and forensic investigations.
• Automation and Orchestration:
  • Network Segmentation—The organization must use automated tools or techniques (e.g., Software-Defined Networking (SDN)) to manage and control network segmentation.
  • Classification and Labeling—The organization must implement automated classification and labeling of data.
  • Anomaly Detection—The organization must implement an automated system for detecting anomalies in security systems.
  • Remediation—The organization must automate the remediation process for security incidents.
  • Policy—The organization must adopt a Policy Decision Point (PDP) and Policy Orchestration for automating security decisions.
  • Machine Learning—The organization must use machine learning to detect threats, adapt security policies and automate security decisions to improve the efficiency and effectiveness of security operations.
  • Artificial Intelligence—The organization must utilize AI algorithms to detect threats, adapt security policies, base access on behavior and automate security decisions to enhance operational efficiency and data protection.
  • SOAR—The organization must implement a Security Orchestration, Automation and Response (SOAR) solution to streamline incident response and improve security operations.
  • Incident Response Plan—The organization must have a Security Operations Center (SOC) in place with a defined Incident Response Plan to effectively manage and respond to security incidents.
• Visibility and Analytics:
  • Discovery—The organization must use network discovery tools, flow analysis tools or packet capture tools to capture and analyze network traffic.
  • Metadata Analysis—The organization must use tools to analyze network metadata.
  • Risk Analysis—The organization must perform real-time device risk analysis integrated with user and entity behavior analytics.
  • Security Operations Center (SOC)—A SOC must be in place to monitor security 24/7.
  • Security Information and Event Management (SIEM)—A SIEM system must be in place to aggregate and analyze security data from across the network.
  • Governance—A goverance system must be implemented to manage compliance and risk policies.
  • Threat Intelligence—The organization must use a threat intelligence platform for proactive monitoring of emerging threats.
  • Automated Updates—The organization must use a system for automatic policy updates that adjust based on emerging threats and verify the presence of potential indicators of compromise.

With the aim to consider all these heterogeneous perspectives in the evaluation process, we now formalize our approach based on IAHP and the Incomplete Logarithmic Least-Squares (ILLS) problem. For further details on the method, see Appendix A—Preliminaries. We apply this method to compute the global weights ${\mathbf{w}}_1,\dots ,{\mathbf{w}}_n$ associated with each sub-criteria (see

Table 1. List of weights for all the considered sub-criteria.

Pillar	Sub-Criteria Description	Pillar Weight	Sub-Criteria Weights	Weights
Users Identity	User Inventory	${\mathbf{m}}_{\mathbf{1}}=0.2106$	${\mathbf{h}}_1=0.1036$	${\mathbf{w}}_1={\mathbf{m}}_{\mathbf{1}}·{\mathbf{h}}_1=0.0218$
	External Multi-Factor Authentication	${\mathbf{m}}_{\mathbf{1}}=0.2106$	${\mathbf{h}}_2=0.0920$	${\mathbf{w}}_2={\mathbf{m}}_{\mathbf{1}}·{\mathbf{h}}_2=0.0194$
	Multi-Factor Authentication (Internal)	${\mathbf{m}}_{\mathbf{1}}=0.2106$	${\mathbf{h}}_3=0.0997$	${\mathbf{w}}_3={\mathbf{m}}_{\mathbf{1}}·{\mathbf{h}}_3=0.0044$
	Identity Access Management (IAM)	${\mathbf{m}}_{\mathbf{1}}=0.2106$	${\mathbf{h}}_4=0.1838$	${\mathbf{w}}_4={\mathbf{m}}_{\mathbf{1}}·{\mathbf{h}}_4=0.0387$
	Identity Governance	${\mathbf{m}}_{\mathbf{1}}=0.2106$	${\mathbf{h}}_5=0.1160$	${\mathbf{w}}_5={\mathbf{m}}_{\mathbf{1}}·{\mathbf{h}}_5=0.0244$
	Privileged Access Management (PAM)	${\mathbf{m}}_{\mathbf{1}}=0.2106$	${\mathbf{h}}_6=0.0925$	${\mathbf{w}}_6={\mathbf{m}}_{\mathbf{1}}·{\mathbf{h}}_6=0.0195$
	Least Privilege	${\mathbf{m}}_{\mathbf{1}}=0.2106$	${\mathbf{h}}_7=0.1113$	${\mathbf{w}}_7={\mathbf{m}}_{\mathbf{1}}·{\mathbf{h}}_7=0.0234$
	Real-Time Risk Detection	${\mathbf{m}}_{\mathbf{1}}=0.2106$	${\mathbf{h}}_8=0.1507$	${\mathbf{w}}_8={\mathbf{m}}_{\mathbf{1}}·{\mathbf{h}}_8=0.0317$
	IGA and PAM Integration	${\mathbf{m}}_{\mathbf{1}}=0.2106$	${\mathbf{h}}_9=0.0505$	${\mathbf{w}}_9={\mathbf{m}}_{\mathbf{1}}·{\mathbf{h}}_9=0.0106$
Devices	Smart Access Governance	${\mathbf{m}}_{\mathbf{2}}=0.0764$	${\mathbf{e}}_1=0.0788$	${\mathbf{w}}_{10}={\mathbf{m}}_{\mathbf{2}}·{\mathbf{e}}_1=0.00602$
	Inventory	${\mathbf{m}}_{\mathbf{2}}=0.0764$	${\mathbf{e}}_2=0.1229$	${\mathbf{w}}_{11}={\mathbf{m}}_{\mathbf{2}}·{\mathbf{e}}_2=0.0094$
	Mobile Device Management	${\mathbf{m}}_{\mathbf{2}}=0.0764$	${\mathbf{e}}_3=0.0987$	${\mathbf{w}}_{12}={\mathbf{m}}_{\mathbf{2}}·{\mathbf{e}}_3=0.0075$
	Standard Configuration	${\mathbf{m}}_{\mathbf{2}}=0.0764$	${\mathbf{e}}_4=0.0988$	${\mathbf{w}}_{13}={\mathbf{m}}_{\mathbf{2}}·{\mathbf{e}}_4=0.0075$
	Compliance	${\mathbf{m}}_{\mathbf{2}}=0.0764$	${\mathbf{e}}_5=0.0422$	${\mathbf{w}}_{14}={\mathbf{m}}_{\mathbf{2}}·{\mathbf{e}}_5=0.0032$
	Conformity	${\mathbf{m}}_{\mathbf{2}}=0.0764$	${\mathbf{e}}_6=0.0364$	${\mathbf{w}}_{15}={\mathbf{m}}_{\mathbf{2}}·{\mathbf{e}}_6=0.0028$
	Detection Tools	${\mathbf{m}}_{\mathbf{2}}=0.0764$	${\mathbf{e}}_7=0.1573$	${\mathbf{w}}_{16}={\mathbf{m}}_{\mathbf{2}}·{\mathbf{e}}_7=0.0120$
	Continuous Monitoring	${\mathbf{m}}_{\mathbf{2}}=0.0764$	$\mathbf{e}=0.2341$	${\mathbf{w}}_{17}={\mathbf{m}}_{\mathbf{2}}·\mathbf{e}=0.0179$
	XDR	${\mathbf{m}}_{\mathbf{2}}=0.0764$	${\mathbf{e}}_9=0.0743$	${\mathbf{w}}_{18}={\mathbf{m}}_{\mathbf{2}}·{\mathbf{e}}_9=0.0057$
	MDR	${\mathbf{m}}_{\mathbf{2}}=0.0764$	${\mathbf{e}}_{10}=0.0565$	${\mathbf{w}}_{19}={\mathbf{m}}_{\mathbf{2}}·{\mathbf{e}}_{10}=0.0043$
Data	Structured Data Classification	${\mathbf{m}}_{\mathbf{3}}=0.2109$	${\mathbf{g}}_1=0.0337$	${\mathbf{w}}_{20}={\mathbf{m}}_{\mathbf{3}}·{\mathbf{g}}_1=0.0071$
	Unstructured Data Classification	${\mathbf{m}}_{\mathbf{3}}=0.2109$	${\mathbf{g}}_2=0.0529$	${\mathbf{w}}_{21}={\mathbf{m}}_{\mathbf{3}}·{\mathbf{g}}_2=0.0112$
	Cloud Security Posture Management (CSPM)	${\mathbf{m}}_{\mathbf{3}}=0.2109$	${\mathbf{g}}_3=0.2183$	${\mathbf{w}}_{22}={\mathbf{m}}_{\mathbf{3}}·{\mathbf{g}}_3=0.0460$
	Data Encryption at Rest	${\mathbf{m}}_{\mathbf{3}}=0.2109$	${\mathbf{g}}_4=0.1238$	${\mathbf{w}}_{23}={\mathbf{m}}_{\mathbf{3}}·{\mathbf{g}}_4=0.0261$
	Data Encryption in Transit	${\mathbf{m}}_{\mathbf{3}}=0.2109$	${\mathbf{g}}_5=0.1036$	${\mathbf{w}}_{24}={\mathbf{m}}_{\mathbf{3}}·{\mathbf{g}}_5=0.0218$
	Data-Loss Prevention (DLP)	${\mathbf{m}}_{\mathbf{3}}=0.2109$	${\mathbf{g}}_6=0.1497$	${\mathbf{w}}_{25}={\mathbf{m}}_{\mathbf{3}}·{\mathbf{g}}_6=0.0316$
	Access Control to Data	${\mathbf{m}}_{\mathbf{3}}=0.2109$	${\mathbf{g}}_7=0.1588$	${\mathbf{w}}_{26}={\mathbf{m}}_{\mathbf{3}}·{\mathbf{g}}_7=0.0335$
	Data-Access Certification	${\mathbf{m}}_{\mathbf{3}}=0.2109$	${\mathbf{g}}_8=0.1592$	${\mathbf{w}}_{27}={\mathbf{m}}_{\mathbf{3}}·{\mathbf{g}}_8=0.0336$
Applications	Application Inventory	${\mathbf{m}}_{\mathbf{4}}=0.0933$	${\mathbf{i}}_1=0.1391$	${\mathbf{w}}_{28}={\mathbf{m}}_{\mathbf{4}}·{\mathbf{i}}_1=0.0130$
	Access Control to Applications	${\mathbf{m}}_{\mathbf{4}}=0.0933$	${\mathbf{i}}_2=0.1449$	${\mathbf{w}}_{29}={\mathbf{m}}_{\mathbf{4}}·{\mathbf{i}}_2=0.0135$
	Session Control for Applications	${\mathbf{m}}_{\mathbf{4}}=0.0933$	${\mathbf{i}}_3=0.1197$	${\mathbf{w}}_{30}={\mathbf{m}}_{\mathbf{4}}·{\mathbf{i}}_3=0.0112$
	Application Performance Management (APM)	${\mathbf{m}}_{\mathbf{4}}=0.0933$	${\mathbf{i}}_4=0.0710$	${\mathbf{w}}_{31}={\mathbf{m}}_{\mathbf{4}}·{\mathbf{i}}_4=0.0066$
	Workload Anomaly Detection	${\mathbf{m}}_{\mathbf{4}}=0.0933$	${\mathbf{i}}_5=0.1398$	${\mathbf{w}}_{32}={\mathbf{m}}_{\mathbf{4}}·{\mathbf{i}}_5=0.0130$
	API Security	${\mathbf{m}}_{\mathbf{4}}=0.0933$	${\mathbf{i}}_6=0.1134$	${\mathbf{w}}_{33}={\mathbf{m}}_{\mathbf{4}}·{\mathbf{i}}_6=0.0106$
	Security by Design	${\mathbf{m}}_{\mathbf{4}}=0.0933$	${\mathbf{i}}_7=0.1641$	${\mathbf{w}}_{34}={\mathbf{m}}_{\mathbf{4}}·{\mathbf{i}}_7=0.0153$
	Software Risk Management	${\mathbf{m}}_{\mathbf{4}}=0.0933$	${\mathbf{i}}_8=0.1081$	${\mathbf{w}}_{35}={\mathbf{m}}_{\mathbf{4}}·{\mathbf{i}}_8=0.0101$
Contractors and Vendors	Assessment of Suppliers	${\mathbf{m}}_{\mathbf{5}}=0.0613$	${\mathbf{f}}_1=0.1232$	${\mathbf{w}}_{36}={\mathbf{m}}_{\mathbf{5}}·{\mathbf{f}}_1=0.0076$
	Assessment of Contractors	${\mathbf{m}}_{\mathbf{5}}=0.0613$	${\mathbf{f}}_2=0.1151$	${\mathbf{w}}_{37}={\mathbf{m}}_{\mathbf{5}}·{\mathbf{f}}_2=0.0071$
	Audit of Contractors	${\mathbf{m}}_{\mathbf{5}}=0.0613$	${\mathbf{f}}_3=0.0563$	${\mathbf{w}}_{38}={\mathbf{m}}_{\mathbf{5}}·{\mathbf{f}}_3=0.0036$
	Audit of Suppliers	${\mathbf{m}}_{\mathbf{5}}=0.0613$	${\mathbf{f}}_4=0.0787$	${\mathbf{w}}_{39}={\mathbf{m}}_{\mathbf{5}}·{\mathbf{f}}_4=0.0048$
	Security Requirements for Suppliers	${\mathbf{m}}_{\mathbf{5}}=0.0613$	${\mathbf{f}}_5=0.1620$	${\mathbf{w}}_{40}={\mathbf{m}}_{\mathbf{5}}·{\mathbf{f}}_5=0.0099$
	Security Requirements for Contractors	${\mathbf{m}}_{\mathbf{5}}=0.0613$	${\mathbf{f}}_6=0.1454$	${\mathbf{w}}_{41}={\mathbf{m}}_{\mathbf{5}}·{\mathbf{f}}_6=0.0089$
	Third-Party Risk	${\mathbf{m}}_{\mathbf{5}}=0.0613$	${\mathbf{f}}_7=0.1712$	${\mathbf{w}}_{42}={\mathbf{m}}_{\mathbf{5}}·{\mathbf{f}}_7=0.0105$
	Third-Party Compliance Management	${\mathbf{m}}_{\mathbf{5}}=0.0613$	${\mathbf{f}}_8=0.1480$	${\mathbf{w}}_{43}={\mathbf{m}}_{\mathbf{5}}·{\mathbf{f}}_8=0.0091$
Automation and Orchestration	Network Segmentation	${\mathbf{m}}_{\mathbf{6}}=0.0786$	${\mathbf{l}}_1=0.0978$	${\mathbf{w}}_{44}={\mathbf{m}}_{\mathbf{6}}·{\mathbf{l}}_1=0.0077$
	Classification and Labeling	${\mathbf{m}}_{\mathbf{6}}=0.0786$	${\mathbf{l}}_2=0.1046$	${\mathbf{w}}_{45}={\mathbf{m}}_{\mathbf{6}}·{\mathbf{l}}_2=0.0082$
	Anomaly Detection	${\mathbf{m}}_{\mathbf{6}}=0.0786$	${\mathbf{l}}_3=0.1478$	${\mathbf{w}}_{46}={\mathbf{m}}_{\mathbf{6}}·{\mathbf{l}}_3=0.0116$
	Remediation	${\mathbf{m}}_{\mathbf{6}}=0.0786$	${\mathbf{l}}_4=0.0894$	${\mathbf{w}}_{47}={\mathbf{m}}_{\mathbf{6}}·{\mathbf{l}}_4=0.00702$
	Policy	${\mathbf{m}}_{\mathbf{6}}=0.0786$	${\mathbf{l}}_5=0.2388$	${\mathbf{w}}_{48}={\mathbf{m}}_{\mathbf{6}}·{\mathbf{l}}_5=0.0188$
	Machine Learning	${\mathbf{m}}_{\mathbf{6}}=0.0786$	${\mathbf{l}}_6=0.0438$	${\mathbf{w}}_{49}={\mathbf{m}}_{\mathbf{6}}·{\mathbf{l}}_6=0.0034$
	Artificial Intelligence	${\mathbf{m}}_{\mathbf{6}}=0.0786$	${\mathbf{l}}_7=0.0452$	${\mathbf{w}}_{50}={\mathbf{m}}_{\mathbf{6}}·{\mathbf{l}}_7=0.0036$
	SOAR	${\mathbf{m}}_{\mathbf{6}}=0.0786$	${\mathbf{l}}_8=0.0991$	${\mathbf{w}}_{51}={\mathbf{m}}_{\mathbf{6}}·{\mathbf{l}}_8=0.0078$
	Incident Response Plan	${\mathbf{m}}_{\mathbf{6}}=0.0786$	${\mathbf{l}}_9=0.1337$	${\mathbf{w}}_{52}={\mathbf{m}}_{\mathbf{6}}·{\mathbf{l}}_9=0.005$
Visibility and Analytics	Discovery	${\mathbf{m}}_{\mathbf{7}}=0.1588$	${\mathbf{n}}_1=0.0891$	${\mathbf{w}}_{53}={\mathbf{m}}_{\mathbf{7}}·{\mathbf{n}}_1=0.0141$
	Metadata Analysis	${\mathbf{m}}_{\mathbf{7}}=0.1588$	${\mathbf{n}}_2=0.0934$	${\mathbf{w}}_{54}={\mathbf{m}}_{\mathbf{7}}·{\mathbf{n}}_2=0.0148$
	Risk Analysis	${\mathbf{m}}_{\mathbf{7}}=0.1588$	${\mathbf{n}}_3=0.1644$	${\mathbf{w}}_{55}={\mathbf{m}}_{\mathbf{7}}·{\mathbf{n}}_3=0.0261$
	Security Operations Center (SOC)	${\mathbf{m}}_{\mathbf{7}}=0.1588$	${\mathbf{n}}_4=0.1802$	${\mathbf{w}}_{56}={\mathbf{m}}_{\mathbf{7}}·{\mathbf{n}}_4=0.0286$
	Security Information and Event Management (SIEM)	${\mathbf{m}}_{\mathbf{7}}=0.1588$	${\mathbf{n}}_5=0.1596$	${\mathbf{w}}_{57}={\mathbf{m}}_{\mathbf{7}}·{\mathbf{n}}_5=0.0253$
	Governance	${\mathbf{m}}_{\mathbf{7}}=0.1588$	${\mathbf{n}}_6=0.1134$	${\mathbf{w}}_{58}={\mathbf{m}}_{\mathbf{7}}·{\mathbf{n}}_6=0.0180$
	Threat Intelligence	${\mathbf{m}}_{\mathbf{7}}=0.1588$	${\mathbf{n}}_7=0.1041$	${\mathbf{w}}_{59}={\mathbf{m}}_{\mathbf{7}}·{\mathbf{n}}_7=0.0165$
	Automated Updates	${\mathbf{m}}_{\mathbf{7}}=0.1588$	${\mathbf{n}}_8=0.0958$	${\mathbf{w}}_{60}={\mathbf{m}}_{\mathbf{7}}·{\mathbf{n}}_8=0.0152$
Network and Infrastructure	Macrosegmentation	${\mathbf{m}}_{\mathbf{8}}=0.1100$	${\mathbf{p}}_1=0.0818$	${\mathbf{w}}_{61}={\mathbf{m}}_{\mathbf{8}}·{\mathbf{p}}_1=0.0090$
	Microsegmentation	${\mathbf{m}}_{\mathbf{8}}=0.1100$	${\mathbf{p}}_2=0.1074$	${\mathbf{w}}_{62}={\mathbf{m}}_{\mathbf{8}}·{\mathbf{p}}_2=0.0118$
	Access Control Based on Context	${\mathbf{m}}_{\mathbf{8}}=0.1100$	${\mathbf{p}}_3=0.1994$	${\mathbf{w}}_{63}={\mathbf{m}}_{\mathbf{8}}·{\mathbf{p}}_3=0.0219$
	Encrypted Network Traffic	${\mathbf{m}}_{\mathbf{8}}=0.1100$	${\mathbf{p}}_4=0.0763$	${\mathbf{w}}_{64}={\mathbf{m}}_{\mathbf{8}}·{\mathbf{p}}_4=0.0084$
	Next-Generation Firewalls	${\mathbf{m}}_{\mathbf{8}}=0.1100$	${\mathbf{p}}_5=0.0095$	${\mathbf{w}}_{65}={\mathbf{m}}_{\mathbf{8}}·{\mathbf{p}}_5=0.0010$
	Firewalls stateless	${\mathbf{m}}_{\mathbf{8}}=0.1100$	${\mathbf{p}}_6=0.0032$	${\mathbf{w}}_{66}={\mathbf{m}}_{\mathbf{8}}·{\mathbf{p}}_6=0.0004$
	Awareness	${\mathbf{m}}_{\mathbf{8}}=0.1100$	${\mathbf{p}}_7=0.0583$	${\mathbf{w}}_{67}={\mathbf{m}}_{\mathbf{8}}·{\mathbf{p}}_7=0.0064$
	Available and Resilient Disaster Recovery	${\mathbf{m}}_{\mathbf{8}}=0.1100$	${\mathbf{p}}_8=0.0905$	${\mathbf{w}}_{68}={\mathbf{m}}_{\mathbf{8}}·{\mathbf{p}}_8=0.0100$
	Secure Web Gateway (SWG)	${\mathbf{m}}_{\mathbf{8}}=0.1100$	${\mathbf{p}}_9=0.0437$	${\mathbf{w}}_{69}={\mathbf{m}}_{\mathbf{8}}·{\mathbf{p}}_9=0.0048$
	Vulnerability Management	${\mathbf{m}}_{\mathbf{8}}=0.1100$	${\mathbf{p}}_{10}=0.0458$	${\mathbf{w}}_{70}={\mathbf{m}}_{\mathbf{8}}·{\mathbf{p}}_{10}=0.0050$
	Service Continuity	${\mathbf{m}}_{\mathbf{8}}=0.1100$	${\mathbf{p}}_{11}=0.0595$	${\mathbf{w}}_{71}={\mathbf{m}}_{\mathbf{8}}·{\mathbf{p}}_{11}=0.0065$
	Disaster Recovery (DR)	${\mathbf{m}}_{\mathbf{8}}=0.1100$	${\mathbf{p}}_{12}=0.0478$	${\mathbf{w}}_{72}={\mathbf{m}}_{\mathbf{8}}·{\mathbf{p}}_{12}=0.0053$
	Cyber Recovery	${\mathbf{m}}_{\mathbf{8}}=0.1100$	${\mathbf{p}}_{13}=0.0317$	${\mathbf{w}}_{73}={\mathbf{m}}_{\mathbf{8}}·{\mathbf{p}}_{13}=0.0035$
	Rapid Reaction to Incidents	${\mathbf{m}}_{\mathbf{8}}=0.1100$	${\mathbf{p}}_{14}=0.0462$	${\mathbf{w}}_{74}={\mathbf{m}}_{\mathbf{8}}·{\mathbf{p}}_{14}=0.0051$
	Immutable Snapshot	${\mathbf{m}}_{\mathbf{8}}=0.1100$	${\mathbf{p}}_{15}=0.0667$	${\mathbf{w}}_{75}={\mathbf{m}}_{\mathbf{8}}·{\mathbf{p}}_{15}=0.0073$
	Snapshot backup cloning	${\mathbf{m}}_{\mathbf{8}}=0.1100$	${\mathbf{p}}_{16}=0.0324$	${\mathbf{w}}_{76}={\mathbf{m}}_{\mathbf{8}}·{\mathbf{p}}_{16}=0.0036$

).

As mentioned earlier, we iteratively apply the ILLS approach to each level of the hierarchical structure depicted in Figure 3, in order to estimate the weights of each pillar (criteria) and sub-criterion via a Delphy approach that involved eight experts.

Starting from the highest level of the hierarchical structure, the preliminary step is the identification of the local weight of each set of pillars and sub-criteria. Let ${\mathcal{M}}^{\left(u\right)}\in {\mathbb{R}}^{8\times 8}$ be the comparison matrix provided by the u-th questionnaire respondent with respect to the eight pillars (i.e., User Identity, Devices, Data, Applications, Contractors and Vendors, Network and Infrastructure, Automation and Orchestration, and Visibility and Analytics) and let ${\mathcal{M}}_{ij}^{\left(u\right)}$ be the relative relevance of the pillar i with respect to the pillar j for the u-th questionnaire respondent, defined according to the Saaty scale (see [25] for additional details). The data have been collected using the AHP online platform “Decision HUB” [26]. Hence each expert was able to provide inputs in an autonomous way. Experts can choose to provide pairwise ratings only for those pillars/controls they are confident about.

Similarly, with the aim to compute the weights associated with each sub-criterion, let ${\mathcal{H}}^{\left(u\right)}\in {\mathbb{R}}^{N_{\text{sub-criteria}}}$ be the comparison matrices provided by the u-th questionnaire respondent, where $N_{\text{sub-criteria}}$ is the total number of sub-criteria for each pillar. These matrices collect the relative scores for the sub-criteria corresponding to each of the eight pillars.

The preliminary step is the identification of the weights ${\mathbf{m}}_i\in {\mathbb{R}}^n$ for each pillar, where i represents each of the eight pillars, derived by the comparison matrices based on Equation (A2). Note that the weights of pillars and sub-criteria are normalized between 0 and 1, with the sum equal to 1.

For the sake of clarity, in Table 1, we summarize the list of pillars, sub-criteria and their associated notation.

4.2. Questionnaire Design

Information related to ZT security elements priorities was collected through a set of structured questionnaires (no ethical approval was required for this study as the questionnaires were fully anonymous and conformed to the principles of the Declaration of Helsinki (2013 revision).) built upon the IAHP methodology. Each questionnaire was designed to collect comparative judgments within a specific domain of the ZT architecture, enabling the construction of individual comparison matrices.

A total of nine thematic questionnaires were administered to a panel of eight professionals with expertise in cybersecurity or IT governance. The panel was purposefully chosen to represent a diverse range of organizations, including enterprises, academic institutions and public sector entities, to ensure a broad perspective on the challenges and considerations of implementing ZTA. Respondents were selected based on their expertise in cybersecurity, IT governance and relevant experience in the adoption and management of security frameworks, particularly in the context of ZTA. The selection process aimed to include individuals with significant decision-making experience and knowledge of cybersecurity practices in a variety of sectors, thus ensuring the panel’s expertise and the relevance of their insights to the study’s objectives.

Each questionnaire focused on one key pillar of the ZT model and was composed of pairwise comparison questions involving four to six domain-specific sub-criteria. The domains covered were: Applications, Automation and Orchestration, Contractors and Vendors, Data, Devices, Network Infrastructure, Users and Visibility and Analytics. A ninth questionnaire was administered to compare the eight macrocriteria themselves (i.e., the eight pillars). Each questionnaire required the respondents to undertake pairwise comparisons of the criteria, expressing the weight of one criterion in relation to the other (see Figure 4).

Each respondent was asked to assess the relative importance of one sub-criterion over another using a seven-point verbal scale aligned with the IAHP framework: “significantly less important”, “a lot less important”, “slightly less important”, “equally important”, “slightly more important”, “a lot more important” and “significantly more important”. These judgments were translated into numerical values 1/7, 1/5, 1/3, 1, 3, 5, 7, enabling the construction of reciprocal comparison matrices for each domain. However, following the “incomplete” philosophy of IAHP, respondents had the freedom to choose which pairs to compare, meaning they were not required to compare all possible pairs.

As a result, each respondent generated nine comparison matrices: eight local matrices corresponding to the thematic questionnaires, and one global matrix comparing the macrocriteria. These matrices serve as the foundation for deriving individual and aggregated priority weights across the full ZT model.

4.3. Results

4.3.1. Weights for the Eight ZT Pillars

The analysis of the relative importance of the eight pillars within the Zero Trust (ZT) security model reveals distinct priorities from the experts involved in the study. The following ranking emerged based on the weights assigned to each of the ZT pillars (see

Table 2. Pillars and their corresponding weights.

Pillar	Pillar Weight (${\mathit{m}}_{\mathit{i}}$)
Users Identity	${\mathbf{m}}_{\mathbf{1}}=0.2106$
Devices	${\mathbf{m}}_{\mathbf{2}}=0.0764$
Data	${\mathbf{m}}_{\mathbf{3}}=0.2109$
Applications	${\mathbf{m}}_{\mathbf{4}}=0.0933$
Contractors and Vendors	${\mathbf{m}}_{\mathbf{5}}=0.0613$
Automation and Orchestration	${\mathbf{m}}_{\mathbf{6}}=0.0786$
Visibility and Analytics	${\mathbf{m}}_{\mathbf{7}}=0.1588$
Network and Infrastructure	${\mathbf{m}}_{\mathbf{8}}=0.1100$

).

The Users pillar reasonably ranks first as experts emphasize that securing user access is the core of Zero Trust, ensuring only authenticated users interact with critical systems. Data follows closely because protecting sensitive information is essential in preventing breaches. Visibility and Analytics are prioritized third due to their role in proactively detecting threats before they escalate. Devices rank next because unsecured endpoints are significant risk factors, particularly in environments with remote work. Applications are ranked fifth, as controlling access to applications is important but follows user and data protection. Network Infrastructure ranks sixth, seen as important but secondary to securing users and data. Contractors and Vendors rank seventh because managing third-party risks is crucial but can be deferred until internal systems are secure. Finally, Automation and Orchestration are ranked last, viewed as important for efficiency but less critical than foundational security measures.

4.3.2. Weights of the Sub-Criteria Within the Eight Pillars

This paragraph reports the Weights of the sub-criteria within the eight pillars (see Figure A1, Figure A2 and Figure A3 in Appendix B).

• The Users pillar is fundamental to Zero Trust, as it directly addresses the risk of unauthorized access and malicious user behavior. IAM, with the highest weight of 0.1838, is prioritized because it ensures that access to critical resources is granted only to verified users, a core principle of Zero Trust. Real-Time Risk Detection (weight: 0.1507) is second in importance, as continuous monitoring allows for the immediate identification of any suspicious behavior, preventing lateral movement even if initial access is compromised. PAM (weight: 0.0925) is also critical but ranks lower because it specifically controls high-risk privileged accounts, reducing the impact of a compromised insider. Finally, Identity Governance (weight: 0.1160) ensures that user access remains aligned with organizational policies, preventing over-provisioned or outdated access rights. The prioritization of IAM and real-time detection emphasizes the need to prevent unauthorized access and quickly identify any breaches, while PAM and governance ensure access is both controlled and regularly audited.
• The Data pillar underscores the importance of safeguarding data from internal and external threats. The highest weight in this pillar is associated with Cloud Security Posture Management (weight of 0.2183), followed by Data-Loss Prevention (weight of 0.1497) and Data Encryption at Rest (weight of 0.1238). Additional sub-criteria such as Structured Data Classification (weight of 0.0337) and Data-Access Certification (weight of 0.1592) reinforce the focus on ensuring data is properly classified and protected, especially in cloud environments.
• The Visibility and Analytics pillar is essential for threat detection and real-time response. The most significant sub-criterion in this pillar is Security Information and Event Management (SIEM) (weight of 0.1596), reflecting the critical role of SIEM systems in aggregating and analyzing security event data. Other key sub-criteria include Security Operations Center (SOC) (weight of 0.1802) and Risk Analysis (weight of 0.1644), both of which emphasize the importance of proactive threat detection and rapid incident response capabilities.
• The Devices pillar focuses on securing endpoints and ensuring proper device management within a Zero Trust framework. The sub-criteria with the highest weights are Continuous Monitoring (weight of 0.2341) and Detection Tools (weight of 0.1573), indicating the need for constant monitoring and the ability to quickly identify any potential vulnerabilities in connected devices. Other important sub-criteria such as Mobile Device Management (weight of 0.0987) and Smart Access Governance (weight of 0.0788) emphasize securing device access and ensuring compliance with security policies.
• The Applications pillar focuses on securing applications and ensuring they meet compliance standards. The highest weight within this pillar is associated with Security by Design (weight of 0.1641), emphasizing the need to integrate security measures throughout the application lifecycle. But also significant sub-criteria include Application Inventory (weight of 0.1391) and Access Control to Applications (weight of 0.1449), highlighting the need to manage application access and maintain an inventory of applications across the organization.
• The Network and Infrastructure pillar addresses the security of the underlying network components that support an organization’s digital infrastructure. The highest weights are associated with Access Control Based on Context (weight of 0.1994), Microsegmentation (weight of 0.1074) and Available and Resilient Disaster Recovery (weight of 0.0905). These results reflect the importance of segmenting networks and applying context-based access control to minimize potential attack surfaces.
• The Contractors and Vendors pillar focuses on managing third-party risks and ensuring that external partners adhere to the organization’s security policies. The most significant sub-criterion in this pillar is Third-Party Risk (weight of 0.1712). Notice that this pillar is not present in the CISA and NIST ZT model but we have introduced it due to the increasing relevance that third parties have acquired in the last year. Indeed, the European Union Agency for Cybersecurity (ENISA) has indicated the Third-Party as the most critical emergent risk [27], as well as the EU Directive has imposed specific cybersecurity obligations on the cybersecurity issues of the supply chain [24]. Third-Party Risk is followed by Security Requirements for Suppliers (weight of 0.1620) and Security Requirements for Contractors (weight of 0.1454). These sub-criteria reflect the importance of assessing and managing third-party security risks to ensure that external suppliers do not introduce vulnerabilities into the organization’s network.
• Finally, the Automation and Orchestration pillar focuses on streamlining security operations through automation. The sub-criteria with the highest weights are definitely Policy (weight of 0.2388). This stresses the high relevance that governance [17] has for an effective implementation of cybersecurity. Another relevant aspect is the Incident Response Plan (weight of 0.1337). While automation is an essential component for improving efficiency and response times, its lower weight suggests that it is considered more of a supportive function rather than a core security focus within ZT architecture.

5. The ZEUS Platform

ZEUS is a governance cloud-native platform designed to digitalize the security posture-assessment process based on the ZT model, developed by Teleconsys. The platform aligns with the NIS2 Directive, integrating cybersecurity-management measures aimed at protecting IT systems, networks and physical environments from significant incidents using a multi-risk approach. ZEUS offers a step-by-step, intuitive process for conducting security assessments, guiding users through the completion of specific checklists that validate the adoption of essential security measures, technologies and governance solutions. A distinctive feature of ZEUS is its use of AHP analysis to prioritize various Zero Trust components based on their relative importance. To incorporate the outcomes of the MCDA, ZEUS uses the AHP to assign weights to the evaluation criteria. These weights reflect the relative importance of different aspects of the ZT architecture. ZEUS then evaluates each countermeasure or security control based on how well it fulfills these criteria. For each item, a score is computed by multiplying the level of fulfillment by the corresponding criterion weight. These scores are then aggregated to obtain a final score for each of the eight ZT pillars, thereby enabling structured and weighted decision-making support within the ZT framework. The AHP-derived weights form the core framework for ZEUS, enabling organizations to pinpoint the most critical areas in need of improvement, such as Identity Management and Data Protection, and ensuring that resources are efficiently allocated. Once the assessment is completed, ZEUS provides a graphical representation of the organization’s security maturity, enabling comparisons with past assessments, target levels or benchmarks from similar organizations. Based on the results, ZEUS generates a prioritized intervention roadmap, focusing on pillars with lower maturity scores and prioritizing controls with higher AHP-derived weights that have not yet reached an adequate level of implementation or assessment. The platform also includes what-if analysis functionality that allows organizations to simulate the evolution of their security posture under various implementation scenarios, providing proactive monitoring. By leveraging AI algorithms, ZEUS automates evaluation processes and identifies priority interventions, ensuring continuous and proactive protection of sensitive information. It tracks assessments over time, offering clear visibility into the organization’s evolving security posture. The ZEUS report simplifies understanding Zero Trust and NIS2 compliance, eliminating complex reporting and enabling decision-makers to justify security investment budgets, while certifying continuous progress in security improvements. ZEUS offers a comprehensive set of features aimed at improving cybersecurity management, including the following key innovations:

• AHP-Based Prioritization Framework: The platform implements AHP analysis to prioritize Zero Trust components with a mathematically rigorous approach, generating empirically derived weights to guide organizations in identifying critical areas of improvement based on quantitative risk analysis.
• Multi-Risk Assessment Integration: ZEUS introduces a multi-risk approach to evaluate IT systems, networks and physical environments in a unified framework, providing a comprehensive view of security posture across all operational domains.
• Dynamic Roadmap Generation Algorithm: This innovative algorithm prioritizes interventions by focusing on pillars with the lowest maturity scores and prioritizing controls with the highest AHP-derived weights, ensuring that resources are directed towards high-impact, low-maturity security controls.
• Predictive What-If Analysis Capability: ZEUS incorporates advanced predictive modeling to simulate the evolution of security posture under different scenarios, allowing stakeholders to evaluate the long-term impact of security investments and shifting the focus from reactive to proactive cybersecurity management.
• AI-Enhanced Evaluation Engine: The integration of artificial intelligence algorithms automates the evaluation processes and identifies priority interventions, reducing human bias and enabling continuous monitoring that adapts to evolving threats.
• Temporal Security Posture Tracking: ZEUS tracks historical assessment data, enabling longitudinal analysis of security maturity, and providing empirical evidence of improvement trajectories to support evidence-based decision-making for future investments.
• Regulatory Alignment and Compliance Innovation: The platform integrates embedded compliance validation mechanisms aligned with the NIS2 Directive, automating the translation of regulatory requirements into actionable security controls and reducing compliance complexity.
• Decision Support and Visualization Innovation: ZEUS converts complex Zero Trust data into intuitive graphical representations, providing comparative analysis across time, organizational benchmarks and target maturity levels, while eliminating the need for complex documentation and offering clear justification frameworks for security investment allocation.

Overall, ZEUS represents a significant advancement in cybersecurity-assessment methodology by combining rigorous analytical frameworks with practical implementation guidance. Its integration of AHP-based prioritization, predictive modeling and AI-enhanced evaluation provides organizations with a scientifically grounded approach to Zero Trust implementation while ensuring regulatory compliance and optimizing resource utilization.

6. Discussion and Conclusions

In this study, we interviewed a panel of eight professionals with expertise in cybersecurity and IT governance, representing a diverse range of organizations, including enterprises, academic institutions and public sector entities. These individuals were selected for their deep understanding of cybersecurity practices, particularly in the context of ZTA. They provided valuable insights into the relative importance of different ZTA pillars, as well as the priorities ranking when implementing or transitioning to ZT security frameworks.

Based on the responses from the interviewed experts, a ranking emerged on which aspects of ZTA are the most critical. For organizations transitioning from a traditional security architecture to ZT, the process is inherently gradual and requires careful planning. The experts in this study emphasized that when making this transition, organizations should still prioritize Users and Data first, but they should also focus on implementing the Visibility and Analytics pillar early in the process. As Zero Trust security relies on continuous monitoring and real-time threat detection, having robust visibility over network activity and security events is essential for identifying and mitigating risks during the transition. This allows organizations to detect threats before they become critical and to ensure that any changes or vulnerabilities introduced during the transition do not go unnoticed.

Following the initial focus on Users, Data and Visibility and Analytics, organizations should then prioritize the Devices, Applications and Network Infrastructure pillars. These elements support the overall ZTA by ensuring that endpoints, applications and the underlying network are properly secured and that access to them is tightly controlled. Devices and applications must be continuously monitored and managed, particularly in environments where users may be accessing the network remotely or using mobile devices. Similarly, network infrastructure should be segmented, and access should be based on context, reducing the risk of lateral movement within the network in case of a breach.

Lastly, the Contractors and Vendors and Automation and Orchestration pillars, although still important, are seen as secondary priorities. These aspects, while necessary for managing third-party risks and streamlining security operations, are generally more focused on supporting the core ZT principles. In the initial stages of the transition, organizations can defer the implementation of these components until the fundamental security measures are in place and functioning effectively.

In addition, securing Devices can be challenging due to the variety of endpoints and operating systems within an organization’s network, which requires ongoing management and compatibility testing. Similarly, implementing Visibility and Analytics may prove difficult due to the large volumes of data generated, demanding sophisticated monitoring tools and real-time threat-detection capabilities. Addressing these challenges could involve phased deployments, using machine learning for enhanced detection, and investing in unified security solutions. Providing guidance on overcoming these hurdles will help organizations navigate their ZT journey more effectively, ensuring a smoother transition and a more resilient security posture.

It is important to note that the panel in this study consisted of only eight experts. While the sample size is sufficient for an initial investigation using the IAHP method, this is a limitation of the study. Future work could expand the panel size and include a more diverse group of experts to further validate these findings. Additionally, expanding the study to include organizations at different stages of their ZT adoption journey could provide a broader understanding of the challenges and strategies for implementing ZT frameworks.

As part of future developments, we also plan to validate the Zeurs platform, which will allow us to gain further insights into the practical implementation of Zero Trust frameworks.

In conclusion, the findings of this study highlight that organizations looking to adopt ZT principles must first focus on securing users identity and data, followed by visibility and analytics. These aspects are critical for ensuring a strong foundation for ZT security, whether an organization is implementing individual elements of the framework or transitioning from a traditional security architecture. The gradual process of adopting ZT should prioritize these elements to ensure a smooth and effective transition to a more secure, resilient architecture.