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Fast and Automated Generation of Attack Signatures: A Basis for Building Self-Protecting Servers (2005)
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@MISC{Liang05fastand,
author = {Zhenkai Liang and R. Sekar},
title = {Fast and Automated Generation of Attack Signatures: A Basis for Building Self-Protecting Servers},
year = {2005}
}
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Abstract
Large-scale attacks, such as those launched by worms and zombie farms, pose a serious threat to our network-centric society. Existing approaches such as software patches are simply unable to cope with the volume and speed with which new vulnerabilities are being discovered. In this paper, we develop a new approach that can provide effective protection against a vast majority of these attacks that exploit memory errors in C/C++ programs. Our approach, called COVERS, uses a forensic analysis of a victim server's memory to correlate attacks to inputs received over the network, and automatically develop a signature that characterizes inputs that carry attacks. The signatures tend to capture characteristics of the underlying vulnerability (e.g., a message field being too long) rather than the characteristics of an attack, which makes them effective against variants of attacks. Our approach introduces low overheads (under 10%), does not require access to source code of the protected server, and has successfully generated signatures for the attacks studied in our experiments, without producing false positives. Since the signatures are generated in tens of milliseconds, they can potentially be distributed quickly over the Internet to filter out (and thus stop) fastspreading worms. Another interesting aspect of our approach is that it can defeat guessing attacks reported against address-space randomization and instruction set randomization techniques. Finally, it increases the capacity of servers to withstand repeated attacks by a factor of 10 or more.
Keyphrases
automated generation building self-protecting server attack signature message field interesting aspect new approach zombie farm effective protection underlying vulnerability forensic analysis software patch serious threat address-space randomization vast majority network-centric society source code approach introduces low overhead new vulnerability large-scale attack memory error protected server randomization technique false positive victim server
