TY - GEN
T1 - SenGuard
T2 - 35th Edition of the Great Lakes Symposium on VLSI 2025, GLSVLSI 2025
AU - Solanki, Neeraj
AU - Tabrizchi, Sepehr
AU - Shafiee Sarvestani, Ali
AU - Angizi, Shaahin
AU - Roohi, Arman
N1 - Publisher Copyright:
© 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.
PY - 2025/6/29
Y1 - 2025/6/29
N2 - This paper introduces SenGuard, a novel processing-in-sensor scheme to enhance imager privacy by integrating sensing and neural network computations directly within the pixel array. We demonstrate SenGuard's effectiveness against NeuralRecon, an attack combining side-channel techniques with generative adversarial networks to reconstruct input images. Evaluations across multiple datasets show SenGuard reduces attacker accuracy to as low as while maintaining classification performance with only a accuracy reduction compared to baseline models. SenGuard achieves 3.28 TOps/W energy efficiency, while making direct reconstruction of captured data extremely difficult.
AB - This paper introduces SenGuard, a novel processing-in-sensor scheme to enhance imager privacy by integrating sensing and neural network computations directly within the pixel array. We demonstrate SenGuard's effectiveness against NeuralRecon, an attack combining side-channel techniques with generative adversarial networks to reconstruct input images. Evaluations across multiple datasets show SenGuard reduces attacker accuracy to as low as while maintaining classification performance with only a accuracy reduction compared to baseline models. SenGuard achieves 3.28 TOps/W energy efficiency, while making direct reconstruction of captured data extremely difficult.
UR - https://www.scopus.com/pages/publications/105017622663
UR - https://www.scopus.com/inward/citedby.url?scp=105017622663&partnerID=8YFLogxK
U2 - 10.1145/3716368.3735263
DO - 10.1145/3716368.3735263
M3 - Conference contribution
AN - SCOPUS:105017622663
T3 - Proceedings of the ACM Great Lakes Symposium on VLSI, GLSVLSI
SP - 587
EP - 592
BT - GLSVLSI 2025 - Proceedings of the Great Lakes Symposium on VLSI 2025
PB - Association for Computing Machinery
Y2 - 30 June 2025 through 2 July 2025
ER -