We live in a data-driven era that involves the generation, collection and processing of a massive amount of data. This data often contains valuable intellectual property and sensitive user information that must be safeguarded. There is a need to both encrypt and compress the data at line speed and sometimes with added power constraints. The majority of the currently available simultaneous compression and encryption (SCE) schemes are tailored for a specific type of data such as images for instance. This reduces their generic applicability. In this paper, we tackle this issue and propose a generic, efficient, and secure simultaneous compression and encryption scheme where the data is simultaneously encrypted using chaotic maps and compressed using a fast lossless compression algorithm. We claim that employing multiple chaotic maps and a lossless compression method can help us create not only an efficient encryption scheme but also compress the data efficiently in a hardware-friendly manner. We avoid all the known pitfalls of chaos theory based encryption that have prevented its widespread usage. Our algorithm passes all the NIST tests for nine different types of popular datasets. The proposed implementation uses 1.51x less storage as compared to the nearest computing work.

翻译：我们生活在一个数据驱动的时代，涉及海量数据的生成、收集和处理。这些数据通常包含必须加以保护的知识产权和敏感用户信息。因此，需要以线速对数据进行加密和压缩，有时还会受到功耗限制。目前大多数可用的同步压缩与加密（SCE）方案都是针对特定数据类型（如图像）设计的，这降低了它们的通用性。在本文中，我们解决了这一问题，并提出了一种通用、高效且安全的同步压缩与加密方案，其中数据使用混沌映射同步加密，并通过快速无损压缩算法进行压缩。我们声称，采用多个混沌映射和无损压缩方法不仅能够构建高效的加密方案，还能以硬件友好的方式高效压缩数据。我们避免了基于混沌理论的加密中所有已知的、阻碍其广泛应用的陷阱。我们的算法在九种不同类型的主流数据集上通过了所有NIST测试。与最近的计算工作相比，所提出的实现方案在存储上减少了1.51倍。