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Nahid Farhady Ghalaty
Researcher at Virginia Tech
Publications - 24
Citations - 548
Nahid Farhady Ghalaty is an academic researcher from Virginia Tech. The author has contributed to research in topics: Fault (power engineering) & Fault injection. The author has an hindex of 12, co-authored 24 publications receiving 470 citations. Previous affiliations of Nahid Farhady Ghalaty include George Mason University & George Washington University.
Papers
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Proceedings ArticleDOI
Differential Fault Intensity Analysis
TL;DR: Differential Fault Intensity Analysis is introduced, which combines the principles of Differential Power Analysis and fault injection and finds that with an average of 7 fault injections, it can reconstruct a full 128-bit AES key.
Posted Content
Differential Fault Intensity Analysis
TL;DR: Differential Fault Intensity Analysis (DFIA) as mentioned in this paper combines the principles of differential power analysis and fault injection to detect side-channel leakage and active attacks based on Fault Injection.
Proceedings ArticleDOI
Software Fault Resistance is Futile: Effective Single-Glitch Attacks
Bilgiday Yuce,Nahid Farhady Ghalaty,Harika Santapuri,Chinmay Deshpande,Conor Patrick,Patrick Schaumont +5 more
TL;DR: This work breaks the security of state-of-the-art instruction-level countermeasures by injecting single clock glitches with a low-cost fault injection setup.
Book ChapterDOI
Lightweight Fault Attack Resistance in Software Using Intra-instruction Redundancy
TL;DR: This work presents a class of lightweight, portable software countermeasures for block ciphers based on redundant bit-slicing, able to detect faults in the execution of a single instruction and able to intercept data faults as well as instruction sequence faults using a uniform technique.
Book ChapterDOI
Differential Fault Intensity Analysis on PRESENT and LED Block Ciphers
TL;DR: This work shows a DFIA attack on two lightweight block ciphers and shows that there is a trade-off between the number of required plaintexts, and the resolution of the fault-injection equipment, and confirms that DFIA is effective against a range of algorithms using arange of fault injection techniques.