The security tower of Babel |
Yuri Gurevich |
Abstract
And the Lord said: “Let us go down, and there confound their language, that they may not understand one another’s speech.” These days, technology and the division of labor confound us. The psychiatrists and heart surgeons speak different languages. Firewalls and database protection software speak different languages. The latter example is of particular interest to us. It makes good sense to integrate automated security experts of various kinds: anti-malware, data-leakage prevention, database protection, firewalls, etc. But how? One idea is a super-expert. There are two problems with that idea. First, there is a large overhead. Second nobody knows how to create the desired super-expert. Is there an alternative solution? Yes: Enterprise Security Assessment Sharing system (ESAS) conceived and being built at Microsoft. The idea is simple. Even if experts speak different languages, the intersection of their languages is not quite empty. Psychiatrists and heart surgeons know that a person can be male or female, sick or healthy. Similarly there is a modest language shared by security experts. We sketch how and why ESAS works. [hidepost]download presentation[/hidepost] |
Bio Yuri Gurevich is an American computer scientist and mathematician and the inventor of abstract state machines. He is currently Principal Researcher at Microsoft Research, where he founded the Foundations of Software Engineering group, and he is Professor Emeritus at the University of Michigan. Gurevich was educated in the Soviet Union, and taught in Israel before coming to the United States. The best known work of his Soviet period is on the classical decision problem. In Israel, Gurevich worked with Saharon Shelah on monadic second-order theories. The Forgetful Determinacy Theorem of Gurevich-Harrington is of that period as well. As far as his American period is concerned, Gurevich is best known for his work on finite model theory and the theory of abstract state machines. He has also contributed to average-case complexity theory. |
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