Publications

Abstract : With recent advancement in Sensors technology, multimedia data has been exponentially generated every day. As a result, there is always a huge demand for fast data processing and storage. In order to effectively acquire and process such a huge amount of data, the concept of compressive sensing (CS) as well as the abundant computing and storage resources of cloud have been increasingly used nowadays. In this paper, we propose a novel secured cloud assisted recovery scheme for compressively sensed signals using a proposed new chaotic map that has wider chaotic range and better attributes when compared to existing maps. With pseudo randomness and unpredictability of the chaotic sequence, generated using the proposed chaotic map, sensing matrix for CS problem and the encryption algorithm are designed. The proposed system ensures that the data owners securely outsource the compressively sensed samples to cloud which occupies less storage. Data users then insist cloud to perform the complex reconstruction problem in an encrypted domain with substantial computational cost being shifted to cloud. Cloud performs the expensive reconstruction problem and provides the reconstructed signal in encrypted form which is later decrypted by the data users. Cloud thus gets no knowledge about the original underlying data samples ensuring privacy of the proposed system. Empirical analysis on the proposed system shows satisfactory compression and security performance on both one dimensional and two dimensional data. The simulation results prove the efficiency of the proposed cloud assisted scheme.