Single-Trace Side-Channel Security Analysis of Homomorphic Encryption
Side-channels pose a significant threat to cybersecurity, as hardware can inadvertently leak sensitive information, such as cryptographic keys, through side-channel attacks, enabling adversaries to compromise mathematically-secure encryption systems. Homomorphic encryption, in particular, has emerged as a critical tool for securing sensitive data in modern computing environments. As the demand for secure and privacy-preserving computation grows, understanding and mitigating vulnerabilities within these systems becomes paramount.
In this talk, Dr. Aydin will present our research on single-trace side-channel analysis of homomorphic encryption, including the first power-based side-channel attack on homomorphic encryption. Dr. Aydin will also discuss additional single-trace vulnerabilities and explore proactive measures to strengthen homomorphic encryption against these attacks. Finally, Dr. Aydin will touch on the impact of optimization in software implementations, providing insights into potential vulnerabilities introduced by compiler optimization.
Date and Time
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- Date: 24 Oct 2024
- Time: 06:00 PM to 08:00 PM
- All times are (UTC-06:00) Mountain Time (US & Canada)
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- Starts 11 October 2024 12:00 AM
- Ends 24 October 2024 12:00 AM
- All times are (UTC-06:00) Mountain Time (US & Canada)
- No Admission Charge
Speakers
Dr. Aydin
Single-Trace Side-Channel Security Analysis of Homomorphic Encryption
Biography:
Dr. Aydin received his Ph.D. degree from North Carolina State University in 2024, where he dedicated five years to researching hardware security for emerging applications. He has authored scientific papers, focusing on exposing and mitigating side-channel attacks on hardware with innovative solutions. Notably, he published the first side-channel attacks on homomorphic encryption. He received his M.S. and B.S. degrees from Ozyegin University in Istanbul, Turkey. He also has over eight years of hardware design experience. His research interests are in emerging hardware security research and secure AI/ML hardware implementations.