Zero Trust Architecture: A Systematic Literature Review
- URL: http://arxiv.org/abs/2503.11659v2
- Date: Fri, 21 Mar 2025 10:52:22 GMT
- Title: Zero Trust Architecture: A Systematic Literature Review
- Authors: Muhammad Liman Gambo, Ahmad Almulhem,
- Abstract summary: ZTA operates on the principle of "never trust, always verify"<n>This study applies the PRISMA framework to analyze 10 years of research on ZTA.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The increasing complexity of digital ecosystems and evolving cybersecurity threats have highlighted the limitations of traditional perimeter-based security models, leading to the growing adoption of Zero Trust Architecture (ZTA). ZTA operates on the principle of "never trust, always verify", enforcing continuous authentication, conditional access, dynamic trust evaluation, and the principle of least privilege to enhance security across diverse domains. This study applies the PRISMA framework to analyze 10 years of research (2016-2025) on ZTA, presenting a systematic literature review (SLR) that synthesizes its applications, enabling technologies, and associated challenges. It provides a detailed taxonomy that organizes ZTA's application domains, together with the emerging technologies that facilitate its implementation, and critically examines the barriers to ZTA adoption. Additionally, the study traces the historical evolution of ZTA alongside notable events and publications trends while highlighting some potential factors for the surge over the past few years. This comprehensive analysis serves as a practical guide for researchers and practitioners seeking to leverage ZTA for stronger, more adaptive security frameworks in a rapidly shifting threat landscape.
Related papers
- The Evolution of Zero Trust Architecture (ZTA) from Concept to Implementation [0.0]
Zero Trust Architecture (ZTA) is one of the paradigm changes in cybersecurity.
This article studies the core concepts of ZTA, its beginning, a few use cases and future trends.
ZTA is expected to strengthen cloud environments, education, work environments (including from home) while controlling other risks like lateral movement and insider threats.
arXiv Detail & Related papers (2025-04-16T11:26:54Z) - Towards Trustworthy GUI Agents: A Survey [64.6445117343499]
This survey examines the trustworthiness of GUI agents in five critical dimensions.
We identify major challenges such as vulnerability to adversarial attacks, cascading failure modes in sequential decision-making.
As GUI agents become more widespread, establishing robust safety standards and responsible development practices is essential.
arXiv Detail & Related papers (2025-03-30T13:26:00Z) - A Survey on Post-training of Large Language Models [185.51013463503946]
Large Language Models (LLMs) have fundamentally transformed natural language processing, making them indispensable across domains ranging from conversational systems to scientific exploration.<n>These challenges necessitate advanced post-training language models (PoLMs) to address shortcomings, such as restricted reasoning capacities, ethical uncertainties, and suboptimal domain-specific performance.<n>This paper presents the first comprehensive survey of PoLMs, systematically tracing their evolution across five core paradigms.
arXiv Detail & Related papers (2025-03-08T05:41:42Z) - Navigating the Edge with the State-of-the-Art Insights into Corner Case Identification and Generation for Enhanced Autonomous Vehicle Safety [38.07210302881341]
Several techniques are proposed that use synthetic data in virtual simulation.<n>The highest risk data, known as corner cases (CCs), are the most valuable for developing and testing AV controls.
arXiv Detail & Related papers (2025-02-27T22:47:46Z) - On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective [314.7991906491166]
Generative Foundation Models (GenFMs) have emerged as transformative tools.<n>Their widespread adoption raises critical concerns regarding trustworthiness across dimensions.<n>This paper presents a comprehensive framework to address these challenges through three key contributions.
arXiv Detail & Related papers (2025-02-20T06:20:36Z) - AILuminate: Introducing v1.0 of the AI Risk and Reliability Benchmark from MLCommons [62.50078821423793]
This paper introduces AILuminate v1.0, the first comprehensive industry-standard benchmark for assessing AI-product risk and reliability.<n>The benchmark evaluates an AI system's resistance to prompts designed to elicit dangerous, illegal, or undesirable behavior in 12 hazard categories.
arXiv Detail & Related papers (2025-02-19T05:58:52Z) - Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Survey [92.36487127683053]
Retrieval-Augmented Generation (RAG) is an advanced technique designed to address the challenges of Artificial Intelligence-Generated Content (AIGC)<n>RAG provides reliable and up-to-date external knowledge, reduces hallucinations, and ensures relevant context across a wide range of tasks.<n>Despite RAG's success and potential, recent studies have shown that the RAG paradigm also introduces new risks, including privacy concerns, adversarial attacks, and accountability issues.
arXiv Detail & Related papers (2025-02-08T06:50:47Z) - A Critical Analysis of Foundations, Challenges and Directions for Zero Trust Security in Cloud Environments [0.0]
This review discusses the theoretical frameworks and application prospects of Zero Trust Security (ZTS) in cloud computing context.
This paper analyzes the core principles of ZTS, including micro-segmentation, least privileged access, and continuous monitoring.
Main barriers to implementing zero trust security were outlined, including the dimensions of decreased performance in large-scale production.
arXiv Detail & Related papers (2024-11-09T10:26:02Z) - Enhancing Enterprise Security with Zero Trust Architecture [0.0]
Zero Trust Architecture (ZTA) represents a transformative approach to modern cybersecurity.
ZTA shifts the security paradigm by assuming that no user, device, or system can be trusted by default.
This paper explores the key components of ZTA, such as identity and access management (IAM), micro-segmentation, continuous monitoring, and behavioral analytics.
arXiv Detail & Related papers (2024-10-23T21:53:16Z) - A Survey on Point-of-Interest Recommendation: Models, Architectures, and Security [40.18083295666298]
Point-of-Interest (POI) recommendation systems are crucial for enriching user experiences, enabling personalized interactions, and optimizing decision-making processes in the digital landscape.<n>We systematically examine the transition from traditional models to advanced techniques such as large language models.<n>We address the increasing importance of security, examining potential vulnerabilities and privacy-preserving approaches.
arXiv Detail & Related papers (2024-10-03T04:11:42Z) - Generative AI for Secure Physical Layer Communications: A Survey [80.0638227807621]
Generative Artificial Intelligence (GAI) stands at the forefront of AI innovation, demonstrating rapid advancement and unparalleled proficiency in generating diverse content.
In this paper, we offer an extensive survey on the various applications of GAI in enhancing security within the physical layer of communication networks.
We delve into the roles of GAI in addressing challenges of physical layer security, focusing on communication confidentiality, authentication, availability, resilience, and integrity.
arXiv Detail & Related papers (2024-02-21T06:22:41Z) - Prioritizing Safeguarding Over Autonomy: Risks of LLM Agents for Science [65.77763092833348]
Intelligent agents powered by large language models (LLMs) have demonstrated substantial promise in autonomously conducting experiments and facilitating scientific discoveries across various disciplines.
While their capabilities are promising, these agents also introduce novel vulnerabilities that demand careful consideration for safety.
This paper conducts a thorough examination of vulnerabilities in LLM-based agents within scientific domains, shedding light on potential risks associated with their misuse and emphasizing the need for safety measures.
arXiv Detail & Related papers (2024-02-06T18:54:07Z) - Zero Trust Implementation in the Emerging Technologies Era: Survey [0.0]
This paper presents a comprehensive analysis of the shift from the traditional perimeter model of security to the Zero Trust (ZT) framework.
It outlines the differences between ZT policies and legacy security policies, along with the significant events that have impacted the evolution of ZT.
The paper explores the potential impacts of emerging technologies, such as Artificial Intelligence (AI) and quantum computing, on the policy and implementation of ZT.
arXiv Detail & Related papers (2024-01-17T19:56:01Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.