Source-Channel Coding, Data Privacy and Contagion Mitigation in Communication and Information Networks

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This proposal concerns the enhancement and continuation of our research program in network information theory and communications. Specifically, we will develop advanced source-channel coding, data privacy and contagion mitigation solutions for communication and information networks. This three-pronged objective addresses critical and complementary challenges facing future generation big data networks in which information needs to be reliably and promptly exchanged between multiple devices, efficiently harnessed without compromising user privacy and securely stored in databases that are immune to contamination from malicious attacks. Building on our achievements, we will focus on the following main themes. (i) Bi-Directional Communication: Establish core Shannon-theoretic limits for two-way communication networks where each terminal receives and transmits signals simultaneously. Guided by our theoretical findings, we will then design state-of-the-art source-channel codes for full duplex communication systems. (ii) Data Privacy: Investigate data privacy mechanisms for decentralized networks using information and estimation theoretic methods. Key aims are to enable data collection agents to optimize system utility without leaking sensitive user information and construct effective privacy-preserving algorithms for big data repositories. (iii) Contagion Mitigation: Develop stochastic contagion models for network epidemics with special emphasis on the accurate representation of both malware spread in communication networks and opinion dynamics in social networks. We will also design and thoroughly validate robust curing techniques based on maximum-entropy and game-theoretic principles for infection control and mitigation in large-scale networks. The proposed research will feature the rigorous training of seven highly qualified personnel per year (3 Ph.D., 2 M.Sc. and 2 undergraduate students), immersing them in challenging topics in information theory, wireless communications, data security and network epidemics and resulting in innovative high-quality publications. The results of this research are anticipated to provide a deeper understanding of the theory and practice of source-channel coding for two-way networks and contribute to the sustainable evolution of wireless communications and sensor networks technologies. It is also expected to contribute to the deployment of resilient user privacy techniques and the judicious control and containment of contagious phenomena in big data networks.