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In the wake of widespread adoption of artificial intelligence (AI) in critical infrastructure, education, government, and national security entities, adversaries are working to disrupt these systems and attack AI-enabled assets. With nearly four decades in vulnerability management, the Carnegie Mellon University Software Engineering Institute (SEI) recognized a need to create an entity that would identify, research, and identify mitigation strategies for AI vulnerabilities to protect national assets against traditional cybersecurity, adversarial machine learning, and joint cyber-AI attacks. In this SEI podcast, Lauren McIlvenny, director of threat analysis in the SEI's CERT Division, discusses best practices and lessons learned in standing up an AI Security Incident Response Team (AISIRT).
By Members of Technical Staff at the Software Engineering Institute4.5
1818 ratings
In the wake of widespread adoption of artificial intelligence (AI) in critical infrastructure, education, government, and national security entities, adversaries are working to disrupt these systems and attack AI-enabled assets. With nearly four decades in vulnerability management, the Carnegie Mellon University Software Engineering Institute (SEI) recognized a need to create an entity that would identify, research, and identify mitigation strategies for AI vulnerabilities to protect national assets against traditional cybersecurity, adversarial machine learning, and joint cyber-AI attacks. In this SEI podcast, Lauren McIlvenny, director of threat analysis in the SEI's CERT Division, discusses best practices and lessons learned in standing up an AI Security Incident Response Team (AISIRT).

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