Secure and Lightweight Compressive Sensing Using Stream Cipher

Vikramkumar Pudi, Anupam Chattopadhyay, Kwok-Yan Lam

Abstract: We are proposing a lightweight and secure compressive sensing (CS) method for compression of data generated by image sensors. This method simultaneously compresses and encrypts image and video files, thereby reducing communication cost, storage space, runtime, and power/energy overhead. Our proposed method combines the CS technique with stream cipher to implement the secure CS. Furthermore, the usage of stream cipher to generate the measurement matrix results in minimal overhead to achieve the security objective. Our experimental studies using the field-programmable gate array prototype show that the security enhancements to the circuit comes, with no timing overhead, reduces 41%-84% of memory requirements and there is only a 8%-33% increase in the LUTs depending on the compression ratio.