CITATION.cff

cff-version: 1.2.0
title: "GenAI in the SOC Paper - Acceleration v. Responsibility"
message: "If you use this work, please cite it as below."
type: article

authors:
  - name: "ESKme"

url: "https://ESKme.net"

repository-code: "https://github.com/ESKme/genai-in-the-soc-paper"

license: "CC-BY-SA-4.0"

abstract: >
  This paper analyzes the integration of generative artificial intelligence into Security Operations
  Centers (SOCs), with a specific focus on incident response processes.

  The central objective is to examine how generative AI can accelerate analytical workflows such as
  alert triage, log interpretation, and contextual threat analysis, while maintaining the necessary
  level of human oversight, accountability, and decision authority.

  The work introduces a conceptual framework describing the tension between operational acceleration
  and responsibility in AI-assisted security environments. It argues that generative AI should be
  understood as a decision-support system rather than an autonomous decision-making entity.

  Based on this perspective, the paper outlines a human-in-the-loop architecture in which AI acts as
  an analytical layer within the SOC workflow, augmenting but not replacing human expertise.

  In addition, key risks associated with generative AI in security contexts are discussed, including
  hallucinations, automation bias, lack of explainability, and adversarial manipulation.

  The results demonstrate that while generative AI has the potential to significantly improve
  efficiency in incident response, its responsible use requires clearly defined governance models,
  validation mechanisms, and a strict separation between support and authority.

keywords:
  - cybersecurity
  - generative-ai
  - soc
  - incident-response
  - ai-in-security
  - human-in-the-loop
  - decision-support
  - security-operations-center
  - threat-detection
  - ai-governance

date-released: 2026-04-13
version: "1.0"

preferred-citation:
  type: article
  title: "GenAI in the SOC Paper - Acceleration v. Responsibility"
  authors:
    - name: "ESKme"
  year: 2026
  url: "https://github.com/ESKme/genai-in-the-soc-paper"