We,re hard-wired to maximize likes, shares, +1s, endorsements, retweets, repins and upvotes on social networks. In doing so, we inadvertently overexpose PII on a massive scale. In fact, business models of the networks themselves are explicitly predicated upon this behavior; revenue generated from user-tailored advertising annually exceeds hundreds of billions of dollars and growing. But the security implications of readily accessible personal data are often overlooked and underestimated.

Bio: Philip Tully is a Senior Data Scientist at ZeroFOX. He employs natural language processing and computer vision techniques in order to develop predictive models for combating security threats emanating from social media. His pivot into the realm of infosec is recent, but his experience with machine learning and artificial neural networks is not. Rather than learning patterns within text and image data, his previous work focused on learning patterns of spikes in large-scale recurrently connected neural circuit models. He earned his joint doctorate degree in computer science from the Royal Institute of Technology (KTH) and the University of Edinburgh. He has previously spoken at Black Hat 2016, DEF CON 24 and across the neuroscience conference circuit.

Back to ShowMeCon 2017 video list