通信学报 ›› 2022, Vol. 43 ›› Issue (10): 121-132.doi: 10.11959/j.issn.1000-436x.2022194

• 学术论文 • 上一篇    下一篇

基于马尔可夫链的生成式区块链隐蔽通信模型

佘维1,2,3, 荣欣鹏1,3, 刘炜1,2,3, 田钊1,3   

  1. 1 郑州大学网络空间安全学院，河南 郑州 450001
    2 河南省网络密码技术重点实验室，河南 郑州 450001
    3 郑州市区块链与数据智能重点实验室，河南 郑州 450001
  • 修回日期:2022-09-08 出版日期:2022-10-25 发布日期:2022-10-01
  • 作者简介:佘维（1977− ），男，湖南常德人，博士，郑州大学教授、博士生导师，主要研究方向为区块链技术、信息安全、智能系统
    荣欣鹏（1998− ），男，山东东营人，郑州大学硕士生，主要研究方向为区块链技术、信息安全
    刘炜（1981− ），男，河南安阳人，博士，郑州大学副教授、博士生导师，主要研究方向为区块链技术、信息安全、智慧医疗
    田钊（1985− ），男，河南荥阳人，博士，郑州大学讲师、硕士生导师，主要研究方向为区块链技术、信息安全、智能交通
  • 基金资助:
    河南省高校科技创新人才支持计划基金资助项目(21HASTIT031);河南省重点研发与推广专项基金资助项目(212102310039);河南省重点研发与推广专项基金资助项目(212102310554);河南省重大公益专项基金资助项目(201300210300);河南省网络密码技术重点实验室研究课题基金资助项目(LNCT2022-A04)

Generative blockchain-based covert communication model based on Markov chain

Wei SHE1,2,3, Xinpeng RONG1,3, Wei LIU1,2,3, Zhao TIAN1,3   

  1. 1 School of Cyber Science and Engineering, Zhengzhou University, Zhengzhou 450001, China
    2 Henan Key Laboratory of Network Cryptography Technology, Zhengzhou 450001, China
    3 Zhengzhou Key Laboratory of Blockchain and Data Intelligence, Zhengzhou 450001, China
  • Revised:2022-09-08 Online:2022-10-25 Published:2022-10-01
  • Supported by:
    Program for Science＆Technology Innovation Talents in Universities of Henan Province(21HASTIT031);Key R＆D and Promotion Project in Henan Province(212102310039);Key R＆D and Promotion Project in Henan Province(212102310554);Major Public Welfare Project of Henan Province(201300210300);Program for Henan Key Laboratory of Network Cryptography Technology(LNCT2022-A04)

在线阅读

51

PDF下载

670

摘要：

摘 要：为了解决目前区块链隐蔽通信中信道构建风险高、信息交叉、隐蔽性不足等问题，提出了一种基于马尔可夫链的生成式区块链隐蔽通信模型。首先，发送方使用文本数据集获取候选单词集并进行马尔可夫模型训练，获得转移概率矩阵，并生成哈夫曼树集合；随后，对需要传输的秘密信息二进制流进行迭代式哈夫曼解码，以获得一组符合正常语言与语义特征、可读性强的载密信息语句，利用生成式隐写方法完成秘密信息嵌入；然后，将该载密信息进行环签名后，作为正常交易发布到区块链网络中并完成打包和出块；最后，接收方利用相同的文本数据集获取转移概率权值哈夫曼树，逆向操作获得秘密信息二进制流。实验结果表明，相较于目前的同类模型，所提模型可进一步提高嵌入强度和时间效率，降低隐蔽信道构建风险，避免信息交叉，提升隐蔽性。

关键词: 隐蔽通信, 区块链, 马尔可夫链, 生成式文本隐写, 环签名

Abstract:

To solve the problems of high channel construction risk, information crossover, and insufficient concealment in the blockchain covert communication, a generative blockchain-based covert communication model based on Markov chain was proposed.First, the text data set was used by sender to obtain the candidate words set and trained the Markov model to obtain the transition probability matrix, generated the Huffman tree set.Secret message to be transmitted was performed iterative Huffman decoding on the binary stream to obtain a set of highly readable carring-secret message statements that conformed to normal language and semantic characteristics, a generative steganography was used to complete secret message embedding.Then, the carring-secret message was ring-signed and published to the blockchain as a normal transaction packing and block generation were completed in the network.Finally, the same text data set was used by the receiver to obtain the Huffman tree of transition probability weights, the binary stream of secret message was obtained by reverse operation.Simulation results demonstrate that, compares with the current similar models, the proposed model can further improve the embedding strength and time efficiency, reduce the risk of covert channel construction, avoid information crossover, and improve the concealment.

Key words: covert communication, blockchain, Markov chain, generative text steganography, ring signature

中图分类号: 

No Suggested Reading articles found!