In this paper, machine learning attacks are performed on a novel hybrid delay based Arbiter Ring Oscillator PUF (AROPUF). The AROPUF exhibits improved results when compared to traditional Arbiter Physical Unclonable Function (APUF). The challenge-response pairs (CRPs) from both PUFs are fed to the multilayered perceptron model (MLP) with one hidden layer. The results show that the CRPs generated from the proposed AROPUF has more training and prediction errors when compared to the APUF, thus making it more difficult for the adversary to predict the CRPs.


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    Title :

    A novel hybrid delay based physical unclonable function immune to machine learning attacks


    Contributors:


    Publication date :

    2017-06-01


    Size :

    610885 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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