Intrusion detection systems have traditionally been based on the characterization of an attack and the tracking of the activity on the system to see if it matches that characterization. Recently, new intrusion detection systems based on data mining are making their appearance in the field. This paper describes the design and experiences with the ADAM (Audit Data Analysis and Mining) system, which we use as a testbed to study how useful data mining techniques can be in intrusion detection.
['Daniel Barbará', 'Julia Couto', 'Sushil Jajodia', 'Ningning Wu']
ADAM: a testbed for exploring the use of data mining in intrusion detection