ChaoSen: Security Enhancement of Image Sensor through in-Sensor Chaotic Computing

Wireless Sensor Networks (WSN) are integral to diverse applications, ranging from environmental monitoring to urban smart infrastructure. In the realm of WSNs, security remains a critical challenge owing to the complex nature of the sensor environment. As a result, WSN security has become a research focus in recent years. In this paper, we introduce ChaoSen, a novel image sensor system incorporating analog chaotic circuits within the sensor, thereby enhancing the overall system security. The system utilizes a scrambler module, which intricately intertwines with the chaotic encryption process, to reduce the predictability of pixel values and enhance the security of the system. Comparative evaluations demonstrate that the system achieves an NPCR value of 99.5562% and a UACI of 35.81900%, indicating high sensitivity to input changes and significant alteration in pixel intensity. Our approach also demonstrates its resilience against common cyber attacks, balancing enhanced security with resource efficiency.

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Publication Details

Published
2024-11-18
DOI
https://doi.org/10.1109/iccd63220.2024.00012
Citations
1
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.21

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article

ChaoSen: Security Enhancement of Image Sensor through in-Sensor Chaotic Computing

Sepehr Tabrizchi, Shaahin Angizi, Arman Roohi, Nedasadat Taheri
1 citations
Advanced Memory and Neural Computing
0.21
article

ChaoSen: Security Enhancement of Image Sensor through in-Sensor Chaotic Computing

Sepehr Tabrizchi, Shaahin Angizi, Arman Roohi, Nedasadat Taheri
article en
1 citations

Abstract

Wireless Sensor Networks (WSN) are integral to diverse applications, ranging from environmental monitoring to urban smart infrastructure. In the realm of WSNs, security remains a critical challenge owing to the complex nature of the sensor environment. As a result, WSN security has become a research focus in recent years. In this paper, we introduce ChaoSen, a novel image sensor system incorporating analog chaotic circuits within the sensor, thereby enhancing the overall system security. The system utilizes a scrambler module, which intricately intertwines with the chaotic encryption process, to reduce the predictability of pixel values and enhance the security of the system. Comparative evaluations demonstrate that the system achieves an NPCR value of 99.5562% and a UACI of 35.81900%, indicating high sensitivity to input changes and significant alteration in pixel intensity. Our approach also demonstrates its resilience against common cyber attacks, balancing enhanced security with resource efficiency.

University of Nebraska–Lincoln (US), New Jersey Institute of Technology (US), University of Illinois Chicago (US)
National Science Foundation
Openalex Percentile: Top 44%
Advanced Memory and Neural Computing
0.21
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