Characterizing cryptographic primitives for lightweight digital image encryption

We present a statistical footprint-based method to characterize several symmetric cryptographic primitives as they are used in lightweight digital image encryption. In particular, using spatial-domain histogram and frequency-domain image analysis techniques, we identify a number of metrics from the encrypted images and use them to contrast the security performance of different cryptographic primitives. For each of the metrics, the best performing cryptographic primitive is identified. Complementary primitives are then combined to result in a product cipher with better cryptographic performance.