Applications of Non-Uniquely Decodable Codes to Privacy-Preserving High-Entropy Data Representation

Non-uniquely-decodable (non-UD) codes can be defined as the codes that cannot be uniquely decoded without additional disambiguation information. These are mainly the class of non-prefix-free codes, where a code-word can be a prefix of other(s), and thus, the code-word boundary information is essential for correct decoding. Due to their inherent unique decodability problem, such non-UD codes have not received much attention except a few studies, in which using compressed data structures to represent the disambiguation information efficiently had been previously proposed. It had been shown before that the compression ratio can get quite close to Huffman/Arithmetic codes with an additional capability of providing direct access in compressed data, which is a missing feature in the regular Huffman codes. In this study we investigate non-UD codes in another dimension addressing the privacy of the high-entropy data. We particularly focus on such massive volumes, where typical examples are encoded video or similar multimedia files. Representation of such a volume with non-UD coding creates two elements as the disambiguation information and the payload, where decoding the original data from these elements becomes hard when one of them is missing. We make use of this observation for privacy concerns. and study the space consumption as well as the hardness of that decoding. We conclude that non-uniquely-decodable codes can be an alternative to selective encryption schemes that aim to secure only part of the data when data is huge. We provide a freely available software implementation of the proposed scheme as well.