Enhancing IoT security through encrypted image processing for intelligent surveillance system

The growing use of Intelligent surveillance systems based on Internet-of-Things (IoT) devices, the issue of security of sensitive visual information, e.g. privacy, ascends to the top of the agenda. We offer an IoT attack security improvement in this research by introducing an encrypted image processing to the smart surveillance systems. The presented approach relies on the need to ensure confidentiality between the image data gathered by the IoT device, including cameras, sensors, etc., and image data via encryption algorithm in a manner to avoid unauthorized access when the image is being transferred and processed. On the basis of high-level cryptography algorithms, e.g. symmetric encryption- (AES) and homomorphic encryption, secure encrypted picture information may be enhanced and transported to support clever observation activities, e.g. recognition of an object and tracking movements. The performance of the proposed system is assessed in regards to encryption strength, processing time, computational overhead, and impact on image quality in a performance analysis. Experiments demonstrate that encrypted image processing pushed into the IoT can accomplish more than only standardizing the protection of data (privacy protection): onto the board with a response to the key challenges of the security of hiring in the framework of the entire IoT environment. This work is helpful to the construction of secure Internet of Things (IoT)-enabled monitoring systems, and provides a foundation for IoT security researches, especially on privacy preserving image processing.

Authors

Publication Details

Journal
Journal of Information and Optimization Sciences
Published
2025-01-01
DOI
https://doi.org/10.47974/jios-2133
Primary Topic
Chaos-based Image/Signal Encryption
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Enhancing IoT security through encrypted image processing for intelligent surveillance system

Erdal Büyükbıçakcı, Prashant A. Athavale, B. C. Kavitha, J. Latha et al.
Journal of Information and Optimization Sciences
Chaos-based Image/Signal Encryption
article

Enhancing IoT security through encrypted image processing for intelligent surveillance system

Erdal Büyükbıçakcı, Prashant A. Athavale, B. C. Kavitha, J. Latha, Dankan Gowda, Hariprasad Soni, Anjali Sandeep Gaikwad
article en

Abstract

The growing use of Intelligent surveillance systems based on Internet-of-Things (IoT) devices, the issue of security of sensitive visual information, e.g. privacy, ascends to the top of the agenda. We offer an IoT attack security improvement in this research by introducing an encrypted image processing to the smart surveillance systems. The presented approach relies on the need to ensure confidentiality between the image data gathered by the IoT device, including cameras, sensors, etc., and image data via encryption algorithm in a manner to avoid unauthorized access when the image is being transferred and processed. On the basis of high-level cryptography algorithms, e.g. symmetric encryption- (AES) and homomorphic encryption, secure encrypted picture information may be enhanced and transported to support clever observation activities, e.g. recognition of an object and tracking movements. The performance of the proposed system is assessed in regards to encryption strength, processing time, computational overhead, and impact on image quality in a performance analysis. Experiments demonstrate that encrypted image processing pushed into the IoT can accomplish more than only standardizing the protection of data (privacy protection): onto the board with a response to the key challenges of the security of hiring in the framework of the entire IoT environment. This work is helpful to the construction of secure Internet of Things (IoT)-enabled monitoring systems, and provides a foundation for IoT security researches, especially on privacy preserving image processing.

Journal of Information and Optimization SciencesVol. 46(7)
Openalex Percentile: Top 67%
Chaos-based Image/Signal Encryption
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.