In this paper, a novel scheme for secure image transmission based on compressive sensing (CS) and Fractional Wavelet Transform (FrWT) is proposed. The scheme uses CS and a multi chaotic pseudo random Sine-Tent-Hénon (STH) map based measurement matrix, in the first stage of encryption. Therefore, it provides a simultaneous compression and encryption. Then the security is further enhanced through the novel approach in the second stage of encryption with an iterative procedure, in which a combination of FrWT and random pixel exchange method is applied. The key parameters used in the generation of random matrix, measurement matrix and fractional orders of FrWT are served as keys. This approach has the larger key parameters provided by the STH map and high degree of scrambling and diffusion with FrWT. With the simulation results, the novel proposed scheme has better compression performance as the PSNR value is 35.6631 dB with 0.75 compression ratio and above 25dB with only 4950 coefficients in the reconstruction of image. When the different types of attacks applied, the value of PSNR in the range of 20-30dB shows the good reconstruction robustness of the proposed scheme. Numerical value comparison with other recent CS based encryption schemes, represents the superiority of the proposed scheme in terms of security.

The security and energy efficiency of resource-constrained distributed sensors are the major concerns in the Internet of Things (IoT) network. A novel lightweight compressive sensing (CS) method is proposed in this study for simultaneous compression and encryption of sensor data in IoT scenarios. The proposed method reduces the storage space and transmission cost and increases the IoT security, with joint compression and encryption of data by image sensors. In this proposed method, the cryptographic advantage of CS with a structurally random matrix (SRM) is considered. Block compressive sensing (BCS) with an SRM-based measurement matrix is performed to generate the compressed and primary encrypted data. To enhance security, a stream cipher-based pseudo-error vector is added to corrupt the compressed data, preventing the leakage of statistical information. The experimental results and comparative analyses show that the proposed scheme outperforms the conventional and state-of-art schemes in terms of reconstruction performance and encryption efficiency.