University of Cambridge > > Computer Laboratory Systems Research Group Seminar > Privacy Trading in the Apps and IoT Age: Markets and Computation

Privacy Trading in the Apps and IoT Age: Markets and Computation

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Abstract: In the era of the mobile apps and IoT, huge quantities of data about individuals and their activities offer a wave of opportunities for economic and societal value creation. However, the current personal data ecosystem is fragmented and inefficient. On one hand, end-users are not able to control access (either technologically, by policy, or psychologically) to their personal data (currently only possible for GDPR regulated countries) which results in issues related to privacy, personal data ownership, transparency, and value distribution. On the other hand, this puts the burden of managing and protecting user data on apps and ad-driven entities (e.g., an ad-network) at a cost of trust and regulatory accountability. In such a context, data holders (e.g., apps) may take advantage of the individuals’ inability to fully comprehend and anticipate the potential uses of their private information with detrimental effects for aggregate social welfare (e.g., Facebook-Cambridge Analytica, and Gmail case studies). In this talk, we investigate the problem of the existence and computationally efficient engineering design of efficient market ecosystems (and their subsequent implications to law and policy) that aim to achieve a maximum social welfare state among competing data holders by preserving the heterogeneous privacy preservation constraints up to certain compromise levels, induced by their clients, and at the same time satisfying requirements of agencies (e.g., advertising organizations) that collect and trade client data for the purpose of targeted advertising, assuming the potential practical inevitability of some amount inappropriate data leakage on behalf of the data holders.

Bio: Ranjan Pal is a visiting researcher in the department of Computer Science and Technology at the University of Cambridge, hosted by Prof. Jon Crowcroft. Prior to this, he was a Research Scientist at the University of Southern California (USC), where he was affiliated with both the Electrical Engineering and Computer Science departments. Ranjan has also been on the visiting faculty at the Indian Institute of Technology Delhi (EE/CS), Indian Institute of Management Ahmedabad, and Indian Institute of Management Calcutta. His primary research interests lie in the applications of applied mathematics tools from data science, economics, game theory, and decision science to problems in cyber-security, privacy, and blockchain-driven resource management in distributed systems. Ranjan received his PhD in Computer Science from USC in 2014, and was the recipient of the Provost Fellowship throughout his PhD studies. During his graduate studies, Ranjan held research scholar positions at Princeton University, Deutsch Telekom Research Laboratories (T-Labs) Berlin, Massachusetts Institute of Technology, National University of Singapore, University of California, and Aalborg University. His research on cyber-insurance (the first ever Ph.D on cyber-insurance for inter-networked systems) to improve cyber-security has appeared in the USC News. Ranjan has also consulted for various companies on cyber-insurance, and is currently a technical advisor to QxBranch He is a member of the IEEE , ACM, American Mathematical Society (AMS), and the Game Theory Society.

This talk is part of the Computer Laboratory Systems Research Group Seminar series.

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