提出了一种基于时间间隔的社交行为信息隐藏算法。首先发送者和接收者获取双方共同拥有的具有社交关系的用户信息；随后发送者结合密钥，利用交互行为（如“点赞”）的时间间隔隐藏秘密信息；最后接收者通过周期性获取共同拥有的社交用户的行为信息提取出秘密信息。以知名社交平台QQ为研究对象进行实验仿真，结果表明该方法能以较少的时间代价显著提高秘密信息传递的容量。所提出的方法不局限于特定的社交平台，具有普适性。
This paper proposes a time interval-based social behavior information hiding algorithm. First, both sender and receiver store the user information of the social relationship shared by both parties; then, the sender binds the key, and hides secret information during the time interval between social interactions such as "liking"; finally, the receiver extracts secret information by periodically acquiring the behavioral information of co-shared social users. Experiment is conducted by taking the popular QQ social platform as research object, and experimental results show that the method can significantly improve the capacity of secret information transmission with a low time cost. The proposed method is not subject to any particular social platforms, and therefore has good applicability.
[1] Fridrich J. Steganography in digital media:principles, algorithms, and applications[M]. Cambridge:Cambridge University Press, 2009.
[2] Wang Z C, Zhang X P, Yin Z X. Joint cover-selection and payload-allocation by steganographic distortion optimization[J]. IEEE Signal Processing Letters, 2018, 25(10):1530-1534.
[3] Li S B, Jia Y Z, Kuo C C J. Steganalysis of QIM steganography in low-bit-rate speech signals[J]. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2017, 25(5):1011-1022.
[4] Rabie T, Baziyad M. The pixogram:addressing high payload demands for video steganography[J]. IEEE Access, 2019, 7:21948-21962.
[5] Li B, Tan S, Wang M, et al. Investigation on cost assignment in spatial image steganography[J]. IEEE Transactions on Information Forensics and Security, 2014, 9(8):1264-1277.
[6] Filler T, Judas J, Fridrich J. Minimizing additive distortion in steganography using syndrome-trellis codes[J]. IEEE Transactions on Information Forensics and Security, 2011, 6(3):920-935.
[7] Holub V, Fridrich J, Denemark T. Universal distortion function for steganography in an arbitrary domain[J]. EURASIP Journal on Information Security, 2014, 2014(1):1-13.
[8] Sedighi V, Cogranne R, Fridrich J. Content-adaptive steganography by minimizing statistical detectability[J]. IEEE Transactions on Information Forensics and Security, 2015, 11(2):221-234.
[9] Tao J Y, Li S, Zhang X P, et al. Towards robust image steganography[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2018, 29(2):594-600.
[10] Zhao Z Z, Guan Q X, Zhang H, et al. Improving the robustness of adaptive steganographic algorithms based on transport channel matching[J]. IEEE Transactions on Information Forensics and Security, 2018, 14(7):1843-1856.
[11] Pantic N, Husain M I. Covert botnet command and control using twitter[C]//Proceedings of the 31st Annual Computer Security Applications Conference, 2015:171-180.
[12] Li S J, Ho A T S, Wang Z C, et al. Lost in the digital wild:hiding information in digital activities[C]//Proceedings of the 2nd International Workshop on Multimedia Privacy and Security, 2018:27-37.
[13] Zhang X P. Behavior steganography in social network[M]. Advances in Intelligent Information Hiding and Multimedia Signal Processing, 2017.
[14] Weng J S, Lim E P, Jiang J, et al. Twitterrank:finding topic-sensitive influential twitterers[C]//Proceedings of the Third ACM International Conference on Web Search and Data Mining, 2010:261-270.
[15] 孙萌.面向社交网站的数据挖掘应用研究-用户关系分析[D].南京:南京邮电大学, 2014.
