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Ethical and Trustworthy Autonomous Agents in Network SecOps: Transparency, Auditing, and Human-in-the-Loop Overrides

Author

Listed:
  • Amar Gurajapu

    (Principal Member of Tech Staff, Network Systems, AT&T, New Jersey, United States)

  • Swapna Anumolu

    (Principal Member of Tech Staff, Network Systems, AT&T, New Jersey, United States)

  • Vardhan Garimella

    (Consultant, Intellibus, United States)

  • Venkata Manikanta Sai Ramakrishna Chundi

    (Lead Architect, Intellibus, United States)

  • Venkata Sita Anand Prakash Gubbala

    (Vice President, Wissen Inc, United States)

Abstract

This paper introduces EthosSecOps, a comprehensive framework designed to enhance transparency, auditability, and ethical alignment in AI-driven intrusion detection and automated response systems. EthosSecOps integrates an Explainability Layer for generating feature-attribution explanations, a Blockchain-backed Audit Store to immutably record alerts, actions, and overrides, and a Policy-Driven Override Engine that empowers human analysts to pause, modify, or abort agent actions. Implemented within a hybrid-cloud telecom environment, EthosSecOps demonstrated 95% attack mitigation accuracy, delivered real-time explanations within 10 milliseconds, and enabled immediate human intervention without disrupting service. The paper details the system's architecture, provides a Python-based audit-logging example, presents empirical evaluation results, and discusses ethical implications for trustworthy autonomous SecOps in regulated and high-availability network operations.

Suggested Citation

  • Amar Gurajapu & Swapna Anumolu & Vardhan Garimella & Venkata Manikanta Sai Ramakrishna Chundi & Venkata Sita Anand Prakash Gubbala, 2025. "Ethical and Trustworthy Autonomous Agents in Network SecOps: Transparency, Auditing, and Human-in-the-Loop Overrides," Frontiers in Computer Science and Artificial Intelligence, Al-Kindi Center for Research and Development, vol. 4(2), pages 63-66, November.
    • Handle: RePEc:alk:fcsai0:v:4:y:2025:i:2:id:12116
    DOI: 10.32996/jcsts.2025.4.2.7
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