Toward unsupervised classification of non-uniform cyber attack tracks | IEEE Conference Publication | IEEE Xplore

Toward unsupervised classification of non-uniform cyber attack tracks


Abstract:

As adversary activities move into cyber domains, attacks are not necessarily associated with physical entities. As a result, observations of an enemy's course of action (...Show More

Abstract:

As adversary activities move into cyber domains, attacks are not necessarily associated with physical entities. As a result, observations of an enemy's course of action (eCoA) may be sporadic, or non-uniform, with potentially more missing and noisy data. Traditional classification methods, in this case, can become ineffective to differentiate correlated observations or attack tracks. This paper formalizes this new challenge and discusses three solution approaches from seemingly unrelated fields. This attempt sheds new light to the problem of classifying unknown types of non-uniform cyber attack tracks.
Date of Conference: 06-09 July 2009
Date Added to IEEE Xplore: 18 August 2009
Print ISBN:978-0-9824-4380-4
Conference Location: Seattle, WA

References

References is not available for this document.