Delta compression correction method for covert communication in IoT

Abstract

Covert communication can conceal the existence of wireless transmission and thus has the ability to address information security transfer issue in many applications of the booming Internet of Things (IoT). However, the proliferation of sensing devices has generated massive amounts of data, which has increased the burden of covert communication. Considering the spatiotemporal correlation of data collection causing redundancy between data, eliminating duplicate data before transmission is beneficial for shortening transmission time, reducing the average received signal power of warden, and ultimately realizing covert communication. In this paper, we propose to apply delta compression technology in the gateway to reduce the amount of data generated by IoT devices, and then sent it to the cloud server. To this end, a cost model and evaluation method that is closer to the actual storage mode of computer systems is been constructed. Based on which, the delta version sequence obtained by existing delta compression algorithms is no longer compact, manifested by the still high cost. In this situation, we designed the correction scheme based on instructions merging (CSIM) correction to save costs by merging instructions. Firstly, the delta version sequence is divided into five categories and corresponding merge rules were derived. Then, for any COPY/ADD class delta compression algorithm, merge according to strict to relaxed to selection rules while generating instructions. Finally, a more cost-effective delta version sequence can be gained. The experimental results on random data show that the delta version sequences output by the CSIM corrected 1.5-pass and greedy algorithms have better performance in cost reducing.