<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sethu Murugan</style></author><author><style face="normal" font="default" size="100%">Dr.K.Kuppusamy</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Intelligent Intrusion Detection Prevention Systems</style></title><secondary-title><style face="normal" font="default" size="100%">Information &amp; Security: An International Journal</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">intrusion</style></keyword><keyword><style  face="normal" font="default" size="100%">multi detection</style></keyword><keyword><style  face="normal" font="default" size="100%">Unknown attack</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2013</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">26</style></volume><pages><style face="normal" font="default" size="100%">109-119</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Intelligence Intrusion Detection Prevention Systems (IDPs) have played an important role to defend our networks from malware attacks. However, since they are still unable to detect an unknown attack, i.e. the zero-day attack, the ultimate challenge in the intrusion detection field is how we can exactly identify such an attack. This paper presents a novel approach which differs from the traditional detection models that are based on intelligence. The proposed method can extract unknown activities from IDS alerts by applying data mining technique.
</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><section><style face="normal" font="default" size="100%">109</style></section></record></records></xml>