@Article{cmc.2020.011219,
AUTHOR = {Lejun Zhang, Tianwen Huang, Xiaoyan Hu, Zhijie Zhang, Weizheng Wang, Donghai Guan, Chunhui Zhao, Seokhoon Kim},
TITLE = {A Distributed Covert Channel of the Packet Ordering  Enhancement Model Based on Data Compression},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {64},
YEAR = {2020},
NUMBER = {3},
PAGES = {2013--2030},
URL = {http://www.techscience.com/cmc/v64n3/39473},
ISSN = {1546-2226},
ABSTRACT = {Covert channel of the packet ordering is a hot research topic. Encryption 
technology is not enough to protect the security of both sides of communication. Covert 
channel needs to hide the transmission data and protect content of communication. The 
traditional methods are usually to use proxy technology such as tor anonymous tracking 
technology to achieve hiding from the communicator. However, because the 
establishment of proxy communication needs to consume traffic, the communication 
capacity will be reduced, and in recent years, the tor technology often has vulnerabilities 
that led to the leakage of secret information. In this paper, the covert channel model of 
the packet ordering is applied into the distributed system, and a distributed covert channel 
of the packet ordering enhancement model based on data compression (DCCPOEDC) is 
proposed. The data compression algorithms are used to reduce the amount of data and 
transmission time. The distributed system and data compression algorithms can weaken 
the hidden statistical probability of information. Furthermore, they can enhance the 
unknowability of the data and weaken the time distribution characteristics of the data 
packets. This paper selected a compression algorithm suitable for DCCPOEDC and 
analyzed DCCPOEDC from anonymity, transmission efficiency, and transmission 
performance. According to the analysis results, it can be seen that DCCPOEDC optimizes 
the covert channel of the packet ordering, which saves the transmission time and 
improves the concealment compared with the original covert channel.},
DOI = {10.32604/cmc.2020.011219}
}