Attacking Arbiter PUFs Using Various Modeling Attack Algorithms: A Comparative Study

Contribution for newspaper or weekly magazine English OPEN
Fang, Yue; Ma, Qingqing; Gu, Chongyan; Wang, Chenghua; O'Neill, Maire; Liu, Weiqiang;
  • Publisher: IEEE
  • Related identifiers: doi: 10.1109/APCCAS.2018.8605618
  • Subject: Machine Learning | Modeling Attacks | Physical Unclonable Functions | /dk/atira/pure/subjectarea/asjc/2200/2204 | Biomedical Engineering | /dk/atira/pure/subjectarea/asjc/2200/2208 | Electrical and Electronic Engineering | /dk/atira/pure/subjectarea/asjc/3100/3105 | Instrumentation

In this paper, we investigate the effectiveness of four different modeling attack algorithms, including Logistic Regression (LR), Naïve Bayes, AdaBoost and Covariance Matrix Adaptation Evolutionary Strategies (CMA-ES), on attacking arbiter physical unclonable functions ... View more
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