Title: Image and object encryption using multiplicative cipher and K-means clustering algorithm

Authors: Maroti Deshmukh; Arjun Singh Rawat

Addresses: Department of Computer Science and Engineering, National Institute of Technology, Uttarakhand, India ' Department of Computer Science and Engineering, National Institute of Technology, Uttarakhand, India

Abstract: In recent years, the development of various visual sensing and image analysis techniques has resulted in the creation of images that contain extremely sensitive data. Unauthorised individuals who access this data illegally risk capturing and disclosing all the sensitive information. To address this issue, we propose a simple and effective image and object encryption approach using a multiplicative cipher and K-means clustering algorithm. The proposed approach involves two levels of encryption, object detection, and K-means clustering in two different phases. In phase 1, the main object from the original image is encrypted using a multiplicative cipher. Phase 2 uses the K-means clustering technique to encrypt the noisy image generated in phase 1. The decryption process is similar to the encryption process but is carried out in reverse order. Moreover, the proposed approach is indeed lossless, even if data is encrypted multiple times. Furthermore, the proposed technique is demonstrated to be robust to differential attacks and resistant to statistical attacks. The results of different experiments show that the approach is effective, secure, and suitable for a wide range of industrial applications.

Keywords: object detection; K-means clustering; edge detection; image encryption; object encryption; multiplicative cipher; decryption.

DOI: 10.1504/IJACT.2024.138424

International Journal of Applied Cryptography, 2024 Vol.4 No.3/4, pp.195 - 204

Received: 14 Jan 2023
Accepted: 01 Jun 2023
Published online: 03 May 2024 *

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