Massive-Dataset Algorithmics
for Network Security

Description | People | Publications


As malicious attacks on computer systems increase in severity and sophistication, developing effective methods for protecting the Internet is among the most important challenges facing computer science today. Network-based security mechanisms offer both good coverage and the possibility of early threat detection, but they often conflict with the performance requirements of network elements because of the vast amounts of traffic data that must be analyzed.

This project will apply massive-dataset (MDS) algorithmics to network security, bringing together two previously unconnected research areas. The objective is to achieve a qualitative improvement in network security by developing efficient, yet theoretically rigorous, algorithmic defenses that can be deployed at scale in modern networks. The project addresses both fundamental algorithm-design problems and practical applications.

This project is supported by the NSF grants CNS-0716158, CNS-0716172, and CNS-0716223 (Oct 1, 2007 - Sep 30, 2010).



Contact: shmat AT cs DOT utexas DOT edu