Steganographic and Steganalytic Methods for Timing Channels with Side Information

具有侧信息的定时信道的隐写和隐写分析方法本建议解决了应用于异步网络上的定时信道的隐写(用于隐蔽通信的编码技术的设计)和隐写分析(用于检测隐蔽通信的统计方法设计)的双重问题。隐藏消息通过调制覆盖分组流(例如，SSH文件传输数据；用于即时消息传递或其他交互会话的击键数据)的定时来嵌入，该覆盖分组流扮演编码器的辅助信息的角色。编码器还受到因果关系和时延的限制，因此本研究的目的是构建和分析在具有边信息的定时信道上进行隐蔽通信的新方法，以及检测这种通信的新方法。该项目围绕四个研究主题展开：1)建立数学公式，研究带有边信息的定时编码的信息论极限。问题描述包括输入分组过程(例如，更新过程或马尔可夫过程)的统计模型、隐写约束(以保证嵌入消息的统计不可检测性)、因果约束和延迟约束。2)开发和分析满足上述约束的一族实用代码。这些代码是非线性和随机的(它们通过队列注入最佳量的“噪声”)，我们将它们称为基于队列的隐写码。3)开发一个高效的计算框架，用于优化与排队过程相关的信息论泛函。4)构建隐写分析学习机(基于经验数据和各种定时代码)，它返回关于是否存在隐藏数据的二元决策。广泛的影响和智力价值：该项目是高度多学科的，涉及随机过程、通信、编码、排队理论、信息论、统计学和学习理论的研究和教育活动的协同。该项目解决了信息保护和网络安全应用的基本问题。其他影响包括排队过程的计算方法、信号处理的隐写方法和其他定时通道等。许多研究生对进入这样一个有吸引力的研究领域感兴趣，该领域结合了广度和对基础知识的强烈重视与实际意义。我们打算对这些学生进行培训，让他们在信息技术领域担任领导角色。

Steganographic and Steganalytic Methodsfor Timing Channels with Side InformationThis proposal addresses dual problems of steganography (design ofcoding techniques for covert communications) and steganalysis(design of statistical methods for detection of covert communications)applied to timing channels on asynchronous networks. Hidden messagesare embedded by modulating the timings of a cover packet stream(e.g., SSH file transfer data; keystroke data for instant messagingor other interactive session) which plays the role of side informationfor the encoder. The encoder is also subject to causality and latency constraints.Hence the objective of this research is to construct and analyze novel methodsfor covert communications over timing channels with side information,as well as novel methods for detecting them.The project is organized around four research thrusts:1) Develop mathematical formulations and research the information-theoretic limits of timing codes with side information. The problem formulation includes a statistical model for the input packet process (e.g., a renewal process, or a Markov process), steganographic constraints (to guarantee statistical undetectability of the embedded messages), causality constraints, and latency constraints.2) Develop and analyze a family of practical codes that satisfy the above constraints. These codes are nonlinear and stochastic (they inject an optimized amount of ``noise'' via a queue) and we refer to them as queue-based steganographic codes.3) Develop an efficient computational framework for optimizing information-theoretic functionals associated with queueing processes.4) Construct a steganalysis learning machine (based on empirical data and various timing codes) which returns a binary decision about the presence of hidden data.Broad Impact and Intellectual Merit:This project is highly multidisciplinary and involves a synergy betweenresearch and educational activities in random processes, communications,coding, queueing theory, information theory, statistics, and learningtheory. The project addresses fundamental questions with applicationsto information protection and cybersecurity.Other impact includes computational methods for queueing processs,steganographic methods for signal processing and other timing channels, etc.Many graduate students are interested in moving into such anattractive research area, which combines breadth and strong emphasison fundamentals with practical relevance. We intend to train thesestudents for leadership roles in information technology.