Hybrid Image Encryption for WISN in Privacy Protection and Security of Public Big Data Using Chaotic Maps

Image big data has become pervasive in today's world. Every day huge volumes of data are being transferred across systems. Significant advancements have been made in networking and file transfer technologies. Due to the remarkable expansion of network infrastructures, multimedia transmission has become inevitable. Image data is being produced at a faster rate and the variety of data types is expanding rapidly. A number of big data-related surveillance applications use wireless image sensor networks (WISN). Important and sensitive data must be hidden from different hackers trying to break into the system. So, encryption is used to hide sensitive information from various hackers. Lorenz attractor along with the chaotic maps are used to withstand statistical attacks. Dual confusion and dual diffusion are implemented so as to ensure maximum chaos and makes the encryption system strong against attacks. The pixels of the image are scrambled using logistic maps so that only authorized users can decipher it. Through the integration of tent map and logistic map, this study approaches an efficient image encryption algorithm.