Issue No.02 - April-June (2007 vol.4)
Kai Hwang , IEEE
Min Cai , IEEE
Christos Papadopoulos , IEEE
Fast and accurate generation of worm signatures is essential to contain zero-day worms at the Internet scale. Recent work has shown that signature generation can be automated by analyzing the repetition of worm substrings (that is, fingerprints) and their address dispersion. However, at the early stage of a worm outbreak, individual edge networks are often short of enough worm exploits for generating accurate signatures. This paper presents both theoretical and experimental results on a collaborative worm signature generation system (WormShield) that employs distributed fingerprint filtering and aggregation over multiple edge networks. By analyzing real-life Internet traces, we discovered that fingerprints in background traffic exhibit a Zipf-like distribution. Due to this property, a distributed fingerprint filtering reduces the amount of aggregation traffic significantly. WormShield monitors utilize a new distributed aggregation tree (DAT) to compute global fingerprint statistics in a scalable and load-balanced fashion. We simulated a spectrum of scanning worms including CodeRed and Slammer by using realistic Internet configurations of about 100,000 edge networks. On average, 256 collaborative monitors generate the signature of CodeRedI-v2 135 times faster than using the same number of isolated monitors. In addition to speed gains, we observed less than 100 false signatures out of 18.7-Gbyte Internet traces, yielding a very low false-positive rate. Each monitor only generates about 0.6 kilobit per second of aggregation traffic, which is 0.003 percent of the 18 megabits per second link traffic sniffed. These results demonstrate that the WormShield system offers distinct advantages in speed gains, signature accuracy, and scalability for large-scale worm containment.
Network security, Internet worms, signature generation, worm containment, traffic measurement, distributed aggregation tree, distributed hash table, cardinality counting.
Kai Hwang, Min Cai, Christos Papadopoulos, "WormShield: Fast Worm Signature Generation with Distributed Fingerprint Aggregation", IEEE Transactions on Dependable and Secure Computing, vol.4, no. 2, pp. 88-104, April-June 2007, doi:10.1109/TDSC.2007.1000