Privacy Preserving Through Fireworks Algorithm Based Model for Image Perturbation in Big Data

Amine Rahmani, Abdelmalek Amine, Reda Mohamed Hamou, Mohamed Elhadi Rahmani and Hadj Ahmed Bouarara
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Amine Rahmani: GeCoDe Laboratory, Tahar Moulay University of Saida Algeria, Saïda, Algeria
Abdelmalek Amine: GeCoDe Laboratory, Tahar Moulay University of Saida Algeria, Saïda, Algeria
Reda Mohamed Hamou: GeCoDe Laboratory, Tahar Moulay University of Saida Algeria, Saïda, Algeria
Mohamed Elhadi Rahmani: GeCoDe Laboratory, Tahar Moulay University of Saida Algeria, Saïda, Algeria
Hadj Ahmed Bouarara: GeCoDe Laboratory, Tahar Moulay University of Saida Algeria, Saïda, Algeria

International Journal of Swarm Intelligence Research (IJSIR), 2015, vol. 6, issue 3, 41-58

Abstract: Nowadays, Social networks and cloud services contain billions of users over the planet. Instagram, Facebook and other networks give the opportunity to share images. Users upload millions of pictures each day, including personal images. Another domain, which concerns medical studies, requires a highly sensitive medical images that retain personal details close to patients. Image perturbation have attracted a great deal of attention in the last few years. Many works concerning image ciphering and perturbing have been published. This paper deals with the problem of image perturbation for privacy preserving. The authors build three new systems that consist of hiding small details in pictures by rotating some pixels. Their models use two algorithms: the first one involves a simulation of the firework algorithm in which they place fireworks on selected pixels then represents sparks as rotation processes. The second system consists of a model of rotation based perturbation using iterated local search algorithm (ILS) with 2 optimization stages. Meanwhile, the third one consists of using the same principle of the previous system except by using the ILS algorithm with 3 optimization stages.

Date: 2015
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