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https://doi.org/10.1109/secpri...
Article . 2002 . Peer-reviewed
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A trend analysis of exploitations

Authors: Hilary K. Browne; William A. Arbaugh; John McHugh; William L. Fithen;

A trend analysis of exploitations

Abstract

We have conducted an empirical study of a number of computer security exploits and determined that the rates at which incidents involving the exploit are reported to CERT can be modeled using a common mathematical framework. Data associated with three significant exploits involving vulnerabilities in phf, imap, and bind can all be modeled using the formula C=I+S/spl times//spl radic/M where C is the cumulative count of reported incidents, M is the time since the start of the exploit cycle, and I and S are the regression coefficients determined by analysis of the incident report data. Further analysis of two additional exploits involving vulnerabilities in mountd and statd confirm the model. We believe that the models will aid in predicting the severity of subsequent vulnerability exploitations, based on the rate of early incident reports.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
45
Top 10%
Top 1%
Top 10%