Public Lecture Laskov 2014
Title: Towards Automatic Detection of Novel Security Threats (venia legendi)
Speaker: Dr Pavel Laskov, University of Tuebingen
Location: X-212 (TUT social sciences building, Akadeemia 3, right next to the library)
Time: 1000-1130, 6th of February
Abstract:
Computer security is a never-ending race between attack and defense. What makes this race particularly challenging nowadays is the value of assets targeted by cyberattacks. One a "mass-market" of cybercrime lie personal credentials of millions of Internet users such as credit card and bank account numbers, email and social network accounts, virtual currencies in online games and many other kinds of personal information that can be exploited for monetary profit. On the other end of computer attack spectrum lies targeted penetration of highly sensitive corporate or governmental sites, with the aim of stealing corporate know-how and classified data, or even carrying out acts of sabotage. The strong "economic motivation" behind modern cyberattacks fuels a rapid development of novel attack methods and raises a major challenge for security technologies: to detect previously unseen threats.
A powerful instrument for effective protection against novel security threats is data analysis tools. An almost unlimited amount of data can be collected by monitoring various security-related indicators such as audit logs and network traffic. Using such data, predictive models can be built by machine learning methods and subsequently deployed to assess previously unseen data. In this talk, I will review the general principles of building data-driven cybersecurity techniques and present examples of several successful reactive security systems built on these principles. As a future challenge, I will discuss the problem of secure data analysis, the importance of which transcends the field of cybersecurity and has a potential impact on many crucial Internet applications.
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More information about the public lectures: http://courses.cs.ttu.ee/pages/Public_Lectures