International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 57 - Number 5 |
Year of Publication: 2012 |
Authors: Dharmendra G. Bhatti, P. V. Virparia |
10.5120/9110-3264 |
Dharmendra G. Bhatti, P. V. Virparia . Data Preprocessing for Reducing False Positive Rate in Intrusion Detection. International Journal of Computer Applications. 57, 5 ( November 2012), 15-19. DOI=10.5120/9110-3264
Intrusion detection plays vital role in computer network security since long. Experience has shown that most IDS struggle for curbing false positive rate. As part of our proposed model with the objective of reducing false positive rate here we have focused on preprocessing functionality. The main objective of our preprocessing module is to reduce ambiguity and provide accurate information to detection engine. So here we have presented preprocessing module which cleans network data and handles missing or incomplete data. Preprocessing module is highly configurable. Based on the result of vulnerability assessment and network topology, hosts exists, services running, intrusion detection analyst need to configure preprocessing module. Effectiveness of preprocessing module depends on such configuration parameters and in turn knowledge of intrusion detection analyst. Preliminary analysis of our approach has shown reduction in false positive rate.