Cryptographic Compression

TL;DR

The paper presents ENCORE, a novel protocol that compresses and encrypts data simultaneously in a single pass, leveraging the properties of typical data distributions and dyadic transformations for efficient streaming encryption and compression.

Contribution

Introduction of ENCORE, a one-pass streaming protocol that combines lossless compression and encryption based on invertible transformations and Markov models.

Findings

Efficient one-pass compression and encryption process.

Achieves near-uniform output with fewer entropy bits than standard encryption.

Satisfies a modified Yao's next-bit test.

Abstract

We introduce a protocol called ENCORE which simultaneously compresses and encrypts data in a one-pass process that can be implemented efficiently and possesses a number of desirable features as a streaming encoder/decoder. Motivated by the observation that both lossless compression and encryption consist of performing an invertible transformation whose output is close to a uniform distribution over bit streams, we show that these can be done simultaneously, at least for ``typical'' data with a stable distribution, i.e., approximated reasonably well by the output of a Markov model. The strategy is to transform the data into a dyadic distribution whose Huffman encoding is close to uniform, and then store the transformations made to said data in a compressed secondary stream interwoven into the first with a user-defined encryption protocol. The result is an encoding which we show exhibits a modified version of Yao's ``next-bit test'' while requiring many fewer bits of entropy than standard encryption. Numerous open questions remain, particularly regarding results that we suspect can be strengthened considerably.