Artificial Intelligence & Machine Learning
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Identity & Access Management
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Next-Generation Technologies & Secure Development
Why CISOs Must Rethink Trust, MFA and Machine Identity Governance
AI-driven phishing emails, voice deepfakes and synthetic identities have changed the threat landscape. Attackers now mimic trusted users with precision. Security teams can no longer rely on static controls or traditional verification methods.
For CISOs, the priority is clear. Move beyond passwords and basic MFA. Embrace context-aware authentication, continuous verification and strong governance for human and non-human identities. Matthew Berzinski, field CTO, EMEA at Ping Identity, said organizations must treat AI agents as first-class identities with strict controls. “We need to make sure all agents have their own identity and that they’re related back to some type of person that can continually authorize them as needed.”
Amani Ibrahim, regional director at Securiti, stressed visibility and behavior monitoring as foundational controls. “For me, the piece of advice, I would say master your data before you secure your AI or before you think about your security strategy. Because simply, we can’t protect what we don’t see.”
In this video interview with Information Security Media Group, the panellists also discussed:
- Rethinking identity verification as AI fuels phishing, deepfakes and help desk attacks;
- Moving from static access policies to real-time, context-aware trust decisions;
- Governing AI agents and non-human identities with visibility and control.
As field CTO for EMEA, Berzinski is responsible for building product strategies and bringing the Ping Identity product portfolio to market. Matt works closely with customers and partners to understand their current and strategic business needs.
Ibrahim is a strategic cybersecurity and AI leader recognized for driving resilient, data-driven technology and security initiatives. She has blended academic insight with industry impact to help organizations navigate emerging cyber and data risks and opportunities in AI and digital transformation.
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