STBS-Stega: Coverless text steganography based on state transition-binary sequence. (March 2020)

• Record Type: Journal Article
• Authors: Wu, Ning; Yang, Zhongliang; Yang, Yi; Li, Lian; Shang, Poli; Ma, Weibo; Liu, Zhenru
• Is Part Of: International journal of distributed sensor networks. Volume 16:Number 3(2020)
• Publication Date: 2020-03
• Subjects: STBS-Stega -- coverless text steganography -- Markov chain model -- transition probability -- state transition-binary sequence diagram; Sensor networks -- Periodicals; Intelligent agents (Computer software) -- Periodicals; Multisensor data fusion -- Periodicals; 681.2
• DOI: 10.1177/1550147720914257
• Languages: English
• ISSNs: 1550-1329

Abstract

Information-hiding technology has recently developed into an area of significant interest in the field of information security. As one of the primary carriers in steganography, it is difficult to hide information in texts because there is insufficient information redundancy. Traditional text steganography methods are generally not robust or secure. Based on the Markov chain model, a new text steganography approach is proposed that focuses on transition probability, one of the most important concepts of the Markov chain model. We created a state transition-binary sequence diagrams based on the aforementioned concepts and used them to guide the generation of new texts with embedded secret information. Compared to other related works, the proposed method exploits the use of the transition probability in the process of steganographic text generation. The associated developed algorithm also encrypts the serial number of the state transition-binary sequence diagram needed by the receiver to extract the information, which further enhances the security of the steganography information. Experiments were designed to evaluate the proposed model. The results revealed that the model had higher concealment and hidden capacity compared to previous methods.