Biblio

Image Encryption is a technique where an algorithm along with a set of characters called key encrypts the data into cipher text. The cipher text can be converted back into plaintext by decryption. This technique is employed for the security of data such that confidentiality, integrity and authenticity of data is maintained. In today's era security of information has become a crucial task, unauthorized access and use of data has become a noticeable issue. To provide the security required, there are several algorithms to suit the purposes. While the use and transferring of images has become easy and faster due to technological advancements especially wireless sensor network, image destruction and illegitimate use has become a potential threat. Different transfer mediums and various uses of images require different and appropriately suiting encryption approaches. Hence, in this paper we discuss the types of image encryption techniques. We have also discussed several encryption algorithms, their advantages and suitability.

Parameter estimation in wireless sensor networks (WSN) using encrypted non-binary quantized data is studied. In a WSN, sensors transmit their observations to a fusion center through a wireless medium where the observations are susceptible to unauthorized eavesdropping. Encryption approaches for WSNs with fixed threshold binary quantization were previously explored. However, fixed threshold binary quantization limits parameter estimation to scalar parameters. In this paper, we propose a stochastic encryption approach for WSNs that can operate on non-binary quantized observations and has the capability for vector parameter estimation. We extend a binary stochastic encryption approach proposed previously, to a non-binary generalized case. Sensor outputs are quantized using a quantizer with R + 1 levels, where R $ε$ 1, 2, 3,..., encrypted by flipping them with certain flipping probabilities, and then transmitted. Optimal estimators using maximum-likelihood estimation are derived for both a legitimate fusion center (LFC) and a third party fusion center (TPFC) perspectives. We assume the TPFC is unaware of the encryption. Asymptotic analysis of the estimators is performed by deriving the Cramer-Rao lower bound for LFC estimation, and the asymptotic bias and variance for TPFC estimation. Numerical results validating the asymptotic analysis are presented.