Colloquium

Security and Privacy Grand Challenges for the Internet of Things

The growth of the Internet of Things (IoT) is driven by market pressures, and while security is being considered, the security and privacy consequences of billions of such devices connecting to the Internet cannot be easily conceived of. The possibilities for unintended surveillance through lifestyle analysis, unauthorized access to information, and new attack vectors will continue to increase by 2020, when up to 50 billion devices may be connected. This talk summarizes our recent papers on the various kinds of vulnerabilities that can be expected to arise, and presents a research agenda for mitigating the worst of the impacts. We hope to explain the potential dangers of IoT and highlight the research opportunities in the areas of security and privacy that IoT presents.

Privacy Preserving User Profiling Using Net2Vec

We present Net2Vec, a flexible high-performance platform that allows the execution of deep learning algorithms in the communication network. Net2Vec is able to capture data from the network at more than 60Gbps, transform it into meaningful tuples and apply predictions over the tuplesin real time. This platform can be used for different purposes ranging from traffic classification to network performance analysis. Finally, we showcasethe use of Net2Vec by implementing and testing a solution able to profile network users at line rate using traces coming from a real network. We show that the use of deep learning for this case outperforms the baseline method both in terms of accuracy and performance.

Interval Graph Completion and Polynomial-Time Preprocessing

Abstract

This talk will start by arguing that the complexity class FPT can be used to capture the notion of polynomial-time preprocessing to reduce input size. This is followed by an FPT algorithm with runtime $O(n^{2k}n^{3}m)$ for the following NP-complete problem [GT35 in Garey&Johnson]: Given an arbitrary graph G on n vertices and m edges, can we obtain an interval graph by adding at most k edges to G? The given algorithm answers a question first posed by Kaplan, Shamir and Tarjan in 1994.

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