LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

0.3 pJ/Bit Machine Learning Resistant Strong PUF Using Subthreshold Voltage Divider Array

Photo by zoltantasi from unsplash

This brief presents a subthreshold voltage divider based strong physical unclonable function (PUF). The PUF derives its uniqueness from random mismatch in threshold voltage in an inverter with gate and… Click to show full abstract

This brief presents a subthreshold voltage divider based strong physical unclonable function (PUF). The PUF derives its uniqueness from random mismatch in threshold voltage in an inverter with gate and drain shorted and biased in subthreshold region. The nonlinear current-voltage relationship in subthreshold region also makes the proposed PUF resistant to machine learning (ML) based attacks. Prediction accuracy of PUF response with logistic regression, support vector machine (SVM) and multi-layer perceptron (MLP) is close to 51%. A prototype PUF fabricated in 65nm consumes only 0.3pJ/bit, and achieves the best combination of energy efficiency and resistance to ML attacks. The measured inter and intra hamming distance (HD) for the PUF are 0.5026 and 0.0466 respectively.

Keywords: puf; voltage; voltage divider; subthreshold voltage; machine learning

Journal Title: IEEE Transactions on Circuits and Systems II: Express Briefs
Year Published: 2020

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.