RACSen: Residue Arithmetic and Chaotic Processing in Sensors to Enhance CMOS Imager Security

Document Type

Conference Proceeding

Publication Date

6-12-2024

Abstract

The widespread adoption of vision sensors raises significant security and privacy concerns. In this paper, we present RACSen as a novel architecture that can increase the security and efficiency of conventional image sensors. RACSen leverages the intricate mathematical properties of the residue number system (RNS) with analog scrambling techniques to create a sophisticated dual-layered encryption mechanism. Incorporating RNS within analog-to-digital converters further strengthens security by mitigating replay attacks and preserving data transmission integrity and confidentiality. Our results demonstrate exceptional encryption, with a perfect pixel change rate of 99.90 and high intensity change of 45.77. This offers robust image data protection with minimal overhead of 11.11%.

Identifier

85197856732 (Scopus)

ISBN

[9798400706059]

Publication Title

Proceedings of the ACM Great Lakes Symposium on VLSI, GLSVLSI

External Full Text Location

https://doi.org/10.1145/3649476.3658791

First Page

551

Last Page

555

Grant

2216772

Fund Ref

National Science Foundation

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