Abstract
As post-quantum cryptography moves from theory to hardware, organizations can no longer afford to ignore the physical layer of security. In this episode of Shielded: The Last Line of Cyber Defense, host Johannes Lintzen speaks with Ferhat Yaman, security researcher at AMD’s Product Security Office, to explore how electromagnetic side-channel attacks, hybrid cryptography, and AI privacy are reshaping the future of secure system design. They discuss the risks of leakage in post-quantum implementations, the challenge of model theft in AI accelerators, and why mitigation needs to start before silicon is even taped out. From masking and shuffling to pre-silicon testing and homomorphic encryption, Ferhat offers a candid and deeply technical look at what it means to build quantum-resilient systems in hardware, not just in code.
What You’ll Learn:
- How side-channel attacks exploit physical leakage like EM emissions and power consumption
- Why even tiny hardware optimizations can create new vulnerabilities
- How AI model parameters can be extracted using electromagnetic analysis
- What homomorphic encryption means and why it’s not yet practical
- How hybrid cryptography supports post-quantum transition in real systems
- Where to start with PQC hardware implementation (hint: think bootloaders)
- How open source and commercial tools help validate hardware security pre-silicon
- Ferhat’s top 3 priorities for building post-quantum-ready chips today
Ferhat Yaman is a security researcher at AMD’s product security office, where his work spans post-quantum cryptography, AI privacy, and side-channel resilience. With a background in both theoretical cryptography and practical hardware design, Ferhat has contributed to projects including the Crystals-Kyber and Dilithium PQC implementations, Caliptra Root of Trust, and electromagnetic model extraction from Google’s Edge TPU. His research explores how secure systems can be built from the silicon up, balancing performance, cost, and long-term quantum readiness. Ferhat’s recent work looks at accelerating homomorphic encryption for AI workloads and improving pre-silicon testing using commercial and open-source tools.
With the shift to post-quantum hardware security accelerating, Yaman’s message is clear: protecting systems requires more than new math; it demands early testing, layered defenses, and security built into the silicon itself.
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