Privacy-preserving smart surveillance using local color correction and optimized ElGamal cryptosystem over cloud

Abstract

The emergence of cloud computing in integration with smart multimedia devices has created an attractive business model today. However, due to the involvement of third party servers, there is a risk of privacy for highly confidential data like surveillance images/videos. Moreover, due to inconsistent lightning conditions, there is a usual requirement of post-processing the captured multimedia for better appearance. Addressing these problems, we propose a novel cloud based privacy-preserving approach for image color enhancement in this paper. Unlike existing color correction schemes, where colors of the test image are processed in plain domain with visible image contents, we propose to perform color correction operations in the encrypted domain over cloud. As a consequence, superior results are achieved along with complete privacy assurance. In addition, we propose a block-based image encryption method using logistic-tent system and ElGamal cryptosystem. As a result, size of the encrypted image is significantly reduced as compared to the naive approach. Experimental results are performed under various tests and the proposed approach is found to be highly effective as compared to state-of-the-art schemes. Moving ahead, security strength of the proposed approach is demonstrated through a challenge response game model.