CIF: Medium: Collaborative Research: Toward a General Theory of Information Transfer via Timing

CIF：媒介：协作研究：通过计时实现信息传输的一般理论

• 批准号: 1065352
• 负责人: Aaron Wagner
• 金额: $ 49.61万
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-01 至 2016-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1065352&HistoricalAwards=false
• 关键词: CIF; Medium; Collaborative; Research; Toward

Information theory, communication theory, and statistical signal processing have proven spectacularly successful as innovation engines for communication, data compression, and information processing technologies. Although in principle these theories are quite general, in practice they are most useful for a particular family of models, such as discrete Markov sources and channels with additive Gaussian noise. Although this family is quite rich and encompasses many practical technologies, there are several important scenarios thatfall outside of these models. In particular, the timing of discrete events is the modality of interest in many applications, such as neuroscienceand certain problems in network security, and this modality does not fit neatly into the standard classes. This research involvesextending information theory, communication theory, and statistical signalprocessing to develop a general theory of information transfer via timing. The first phase of this research involves solving several concreteproblems involving information transfer via timing, such as thesecrecy capacity of timing channels and how to minimize informationtransfer via timing side channels in both wireless and wirelinenetworks. The second phase involves interconnecting these disparateproblems to form a general theory of information transfer via timing.By elevating the role of timing in information transfer,this research better positions the fields of information theory,communication theory, and statistical signal processing toimpact allied fields such as networking, neuroscience, and operations research, where timing and delay are of fundamentalimportance. This impact is facilitated through special topics courses and invited sessions at conferences, both of which are designed to attract participants from a range of areas.

事实证明，信息论、通信理论和统计信号处理作为通信、数据压缩和信息处理技术的创新引擎取得了巨大的成功。尽管原则上这些理论非常通用，但实际上它们对于特定的模型系列最有用，例如离散马尔可夫源和具有加性高斯噪声的通道。尽管这个系列非常丰富并且包含许多实用技术，但有几个重要的场景不属于这些模型。特别是，离散事件的时序是许多应用中感兴趣的模态，例如神经科学和网络安全中的某些问题，并且这种模态并不完全适合标准类别。这项研究涉及扩展信息论、通信理论和统计信号处理，以发展通过定时进行信息传输的一般理论。本研究的第一阶段涉及解决涉及定时信息传输的几个具体问题，例如定时信道的保密能力以及如何最小化无线和有线网络中通过定时侧信道的信息传输。第二阶段涉及将这些不同的问题互连起来，形成通过定时进行信息传输的一般理论。通过提升定时在信息传输中的作用，本研究更好地定位了信息论、通信理论和统计信号处理领域，以影响相关领域，例如网络、神经科学和运筹学，其中时间和延迟至关重要。这种影响是通过专题课程和会议邀请会议来促进的，这两者都旨在吸引来自各个领域的参与者。