随着大数据时代的到来，越来越多的海量数据和多媒体信息应用于社会的各行各业。近年来对于数字信息的压缩和加密联合编码成为一个新兴的研究热点。由于压缩和加密通常被认为是一对矛盾体，现有算法均不能同时提供高压缩率和高安全性，往往侧重其一。本课题对数字信息的比特级性质、多维算数编码以及基于混沌理论的密码学进行研究，通过揭示传统联合编码算法中压缩操作和加密操作互相影响的深层次原因，给出一个具有高压缩率和高安全性的联合编码方案，建立起数据压缩和加密联合编码的评价体系和标准。在此基础上，结合扩展维度后的多维熵编码提出一种全新的压缩加密联合编码框架，保证数字信息的安全性同时，提高压缩率。

With the development of "Big Data" and information technology, more and more digital information are applied in all fields of society. In recent years, the research of joint compression and encryption source coding has attracted a lot of researchers' concern. As compression and encryption are generally considered as two contradiction operations, existing algorithms cannot simultaneously provide high compression ratio and high security, often focusing one. In this research project, we investigate the bit-level features of digital information, multi-dimensional arithmetic coding and chaos-based cryptosystems to find out the deep-seated reasons of the contradiction between the compression and encryption operations. Furthermore, a new joint compression and encryption source coding structure with high level security and compression ratio is proposed, and a new evaluation system will be also provided. Moreover, a new joint compression and encryption algorithm employed multi-dimensional arithmetic coding is proposed to guarantee high level security and compression ratio simultaneously.