ResSen: Imager Privacy Enhancement Through Residue Arithmetic Processing in Sensors

Document Type

Conference Proceeding

Publication Date

1-1-2024

Abstract

The increasing use of image sensors across various domains poses notable privacy challenges. In response, this paper introduces a novel architecture, namely ResSen, to enhance the privacy and efficiency of traditional image sensors. Our approach integrates the Residue Number System (RNS) with in-sensor digital encryption techniques to forge a robust, dual-layer encryption mechanism. By embedding RNS within analog-to-digital converters (ADCs), we significantly strengthen privacy measures, effectively countering different violations and ensuring the integrity and confidentiality of data transmissions. A key feature of our system is its programmable key, which complicates unauthorized output prediction or replication, providing a supe-rior encryption methodology. Notably, ResSen demonstrates that deactivating one of the moduli results in 25 % bandwidth savings at the cost of minor accuracy degradation. This underscores the practicality and effectiveness of our sensor architecture in addressing the dual objectives of privacy enhancement and operational efficiency.

Identifier

85206192901 (Scopus)

ISBN

[9798350354119]

Publication Title

Proceedings of IEEE Computer Society Annual Symposium on VLSI, ISVLSI

External Full Text Location

https://doi.org/10.1109/ISVLSI61997.2024.00070

e-ISSN

21593477

ISSN

21593469

First Page

349

Last Page

354

Grant

2216772

Fund Ref

National Science Foundation

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