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When Machine Learning Meets Hardware Cybersecurity: Delving into Accurate Zero-Day Malware Detection.

, , , , , and . ISQED, page 85-90. IEEE, (2021)

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Data-oblivious graph algorithms for secure computation and outsourcing., , and . AsiaCCS, page 207-218. ACM, (2013)Redefining Trust: Assessing Reliability of Machine Learning Algorithms in Intrusion Detection Systems., , , and . ISCAS, page 1-5. IEEE, (2024)Mitigating Autonomous Vehicle GPS Spoofing Attacks through Scene Text Observations., , , , , and . HICSS, page 6706-6715. ScholarSpace, (2023)Towards AI-Enabled Hardware Security: Challenges and Opportunities., , , , , , and . IOLTS, page 1-10. IEEE, (2022)Analysis of Reusability of Secure Sketches and Fuzzy Extractors., and . IEEE Trans. Inf. Forensics Secur., 8 (9): 1433-1445 (2013)On the (Non-)Reusability of Fuzzy Sketches and Extractors and Security Improvements in the Computational Setting., and . IACR Cryptol. ePrint Arch., (2012)Global Attack and Remedy on IC-Specific Logic Encryption., , , , and . HOST, page 145-148. IEEE, (2022)Computing the Optimal Longest Queue Length in Torus Networks., , and . TPNC, volume 13082 of Lecture Notes in Computer Science, page 3-14. Springer, (2021)Secure Computation of Hidden Markov Models., and . SECRYPT, page 242-253. SciTePress, (2013)Secure outsourced computation of iris matching., and . J. Comput. Secur., 20 (2-3): 259-305 (2012)