Secure Lossy Image Compression via Adaptive Vector Quantization
In this paper we propose a secure lossy image compression method based on Adaptive Vector Quantization. The proposed approach is founded on the principles of the Entropy-restricted Semantic Security and the logical functioning of the Squeeze Cipher algorithm. It could be useful in several application domains, including Virtual Reality (VR) or Augmented Reality (AR), for its security aspects and for its asymmetrical compression/decompression behavior. Indeed, decompression is more efficient and significantly faster with respect to compression. This aspect could be relevant in many scenarios where images are compressed once and decompressed several times, sometimes on devices with limited hardware capabilities. In the proposed approach a single key is used for the compression and the simultaneous encryption of the input image. Such a key must also be used for decryption (and the associated simultaneous decompression). We report preliminary experimental results achieved by a proof-of-concept implementation of our approach. Such results seem to be quite promising and meaningful for future investigations of the proposed approach.
KeywordsImage compression Lossy compression Entropy-restricted security Adaptive Vector Quantization
Bruno Carpentieri would like to thank its students Giovanni Festa and Michele Roviello, for the implementation of a preliminary version of the AVQS approach.
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