University of California

Cristi Estan

Sumeet Singh

George Varghese

Stefan Roberts Savage

Network worms or viruses are a growing threat to the security of public and private networks and the individual computers that make up those networks. A content sifting method if provided that automatically generates a precise signature for a worm or virus that can then be used to significantly reduce the propagation of the worm elsewhere in the network or eradicate the worm altogether. The content sifting method is complemented by a value sampling method that increases the throughput of network traffic that can be monitored. Together, the methods track the number of times invariant strings appear in packets and the network address dispersion of those packets including variant strings. When an invariant string reaches a particular threshold of appearances and address dispersion, the string is reported as a signature for suspected worm.

Detecting public network attacks using signatures and fast content analysis

Detecting attacks against computer systems by automatically detecting signatures based on predetermined characteristics of the intrusion. One aspect looks for commonalities among a number of different network messages, and establishes an intrusion signature based on those commonalities. Data reduction techniques, such as a hash function, are used to minimize the amount of resources which are necessary to establish the commonalities. In an embodiment, signatures are created based on the data reduction hash technique. Frequent signatures are found by reducing the signatures using that hash technique. Each of the frequent signatures is analyzed for content, and content which is spreading is flagged as being a possible attack. Additional checks can also be carried out to look for code within the signal, to look for spam, backdoors, or program code.

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Cristi Estan