Assessing Information Credibility in the Social Web

Speaker: Gabriella Pasi (Università degli Studi di Milano-Bicocca, Italy)

Abstract: In the context of the Social Web, where a large amount of User Generated Content is diffused through Social Media without any form of trusted external control, the risk of running into misinformation is not negligible. For this reason, the issue of assessing the credibility of “potential” information is of increasing interest and importance. In the last few years several approaches have been proposed to automatically assess the credibility of UCG in Social Media. Most are data-driven approaches, based on machine learning techniques, but recently model-driven approaches are also being investigated, in particular, approaches relying on the Multi Criteria Decision Making paradigm. In this talk an overview of the approaches aimed at tackling this problem are addressed, with particular emphasis on model driven approaches; their application to specific problems will also be addressed.

Deception, Deterrence and Security

Speaker: V.S. Subrahmanian (Department of Computer Science, Institute for Security, Technology, and Society, Dartmouth College, USA)

Abstract: Deception is at the heart of many security issues. For instance, phishing and spear-phishing attacks use deception. So do man in the middle attacks in which, for instance, a fake cell tower deceives individual mobile devices to connect to them. However, deception can also be used for “good’’ in order to inject uncertainty and inflict costs on a malicious adversary. In this talk, I will go over 2 major case studies involving deception for good which have a deterrent effect on a malicious adversary. In the first, I will discuss how selective disclosure of probabilistic logic-based behavioral models can help shape the actions of terrorist groups, making their behavior more predictable (for us) and hence more defendable. In a second application, this time in cybersecurity, I will show methods and a prototype system to inflict costs on an adversary who steals valuable intellectual property by populating a network with automatically generated fake documents that masquerade as intellectual property.