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

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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.