Hunting Threats with Artificial Intelligence
There is a current trend from “trapping” to “hunting”. In order to fully understand the impact of a breach, the detection of malware threats needs to be complemented by the proactive exploration of anomalous network behavior and inter-artifact relationships. This activity is supported by machine learning techniques, which can be leveraged to aggregate and classify events at an unprecedented scale. This presentation highlights how machine learning and artificial intelligence can support a human operator in assessing a sophisticated threat that has breached a target network.
Speaker: Engin Kirda, Co-Founder and Chief Architect, Lastline
In addition to being co-founder and chief architect at Lastline, Engin Kirda is a Professor at the Northeastern University in Boston, and the director of the Northeastern Information Assurance Institute. Before that, Engin held faculty positions at the Institute Eurecom in the French Riviera and the Technical University of Vienna, where he co-founded the Secure Systems Lab that is now distributed over five institutions in Europe and US. Engin’s recent research has focused on malware analysis (e.g., Anubis, Exposure, Fire) and detection, web application security, and practical aspects of social networking security. His recent work on the de-anonymization of social network users received wide media coverage. Engin co-authored more than 110 peer-reviewed scholarly publications and served on program committees of numerous well-known international conferences and workshops.
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