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Faculty-Responsive university staff personal page

The objective of this project is to build architecture-level defenses through the use of compilers to automate side-channel resilient neural network implementations.

 

Threat Model

Threat Model



                 
Novel Side-Channel Defenses

SCA Defenses

  Source Code: empty_file.txt


PUBLICATIONS

MaskedNet: A Pathway for Secure Inference against Power Side-Channel Attacks

Anuj Dubey, Rosario Cammarota, Aydin Aysu
Conference Paper IEEE International Symposium on Hardware Oriented Security and Trust (HOST), Virtual Conference, Dec 2020

This project is funded by

SRC

SRC GRC Task 2908.

Our specific project link is private/requires sign in: https://www.src.org/library/research-catalog/2908.001/


Our work has been featured by the IEEE Spectrum Magazine.

IEE
SRC


BoMaNet: Boolean Masking of an Entire Neural Network

Anuj Dubey, Rosario Cammarota, Aydin Aysu
Conference Paper International Conference on Computer-Aided Design (ICCAD), Virtual Conference, Nov 2020