International Journal of Computer Techniques Volume 12 Issue 1 | AI Driven ChatOps with for Realtime Security Incident Response in DevSecOps
AI-Driven ChatOps for Real-time Security Incident Response in DevSecOps
Balajee Asish Brahmandam
University of Texas at Austin, Austin, Texas, USA
balajeeasish@utexas.edu
Abstract
DevSecOps enhances software delivery but struggles with integrating swift security incident response. This study introduces an AI-powered ChatOps framework, enabling automated remediation, real-time threat detection, and collaborative investigation. Our solution integrates machine learning-driven threat detection with chat-based operations, facilitating quicker reaction times and improved security posture.
Keywords
DevSecOps, ChatOps, AI in Cybersecurity, Security Automation, Incident Response, SIEM, Security Bots, NLP, Continuous Monitoring.
Conclusion
AI-driven ChatOps enhances security teams’ efficiency by providing automated responses within DevSecOps environments. Businesses benefit from rapid incident handling, improved team collaboration, and AI-assisted threat mitigation, fostering proactive cybersecurity practices.
References
- NIST, Computer Security Incident Handling Guide (SP 800-61 Rev.2), 2012.
- Palo Alto Networks, βFaster incident response and reduced alert fatigue at NKGSB Bank,β 2023.
- Microsoft, βUse a Microsoft Sentinel playbook to stop compromised users,β 2023.
- IBM Security, βIBM QRadar Advisor with Watson,β 2017.
- Google Cloud, βChronicle SOAR: Threat Investigation and Response,β 2023.
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