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UNSAIL: Thwarting Oracle-Less Machine Learning Attacks on Logic Locking

  • Published:2021 Issue: Volume:16 Page:2508-2523
  • ISSN:1556-6013
  • Container-title:IEEE Transactions on Information Forensics and Security
  • language:
  • Short-container-title:IEEE Trans.Inform.Forensic Secur.

Author:

Alrahis LilasORCID,Patnaik SatwikORCID,Knechtel JohannORCID,Saleh HaniORCID,Mohammad BakerORCID,Al-Qutayri MahmoudORCID,Sinanoglu OzgurORCID

Funder

Khalifa University of Science, Technology and Research

Center for Cyber Security at NYU New York/Abu Dhabi

Global Ph.D. Fellowship at NYU/NYUAD

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Safety, Risk, Reliability and Quality

Cited by 29 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. DECOR: Enhancing Logic Locking Against Machine Learning-Based Attacks;2024 25th International Symposium on Quality Electronic Design (ISQED);2024-04-03

2. Learning Your Lock: Exploiting Structural Vulnerabilities in Logic Locking;IEEE Design & Test;2024-04

3. LIPSTICK: Corruptibility-Aware and Explainable Graph Neural Network-based Oracle-Less Attack on Logic Locking;2024 29th Asia and South Pacific Design Automation Conference (ASP-DAC);2024-01-22

4. Machine Learning-Based Security Evaluation and Overhead Analysis of Logic Locking;Journal of Hardware and Systems Security;2024-01-22

5. Thwarting GNN-Based Attacks Against Logic Locking;IEEE Transactions on Information Forensics and Security;2024
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