A comparative study of anomaly detection schemes in network intrusion detection.
b9928e0c57d7fdc9212d412d47a979bfa6ae04da6fed4884e9c6313b71e3f0c1A Data Mining Framework for Building Intrusion Detection Models.
60d04b31fcfe448027bbb5860b8344475e331292a2f38a9c58a5f6bf8565794dA Framework For An Adaptive Intrusion Detection System with Data Mining.
8f6eb99f5161f3bdc97f1b2abc1790661385fcd2a732370cb3a64ad0d76ff3b4A Framework for Classifying Denial of Service Attacks.
6bb2ae1d0f82b729c5207119d92f40b2d239e203a10af9bec1f54258ede9691eA Framework for Constructing Features and Models for Intrusion Detection Systems.
f61527cf4af2510db8ad35437d3eb26e96999237907e12a510de0e49b2733a31A Geometric Framework for Unsupervised Anomaly Detection: Detecting Intrusions in Unlabeled Data.
0449a5f802f6d128eb3b915c406f89489a0cd361eccb64aa70000c137ec98639A Learning Based Approach to the Detection of SQL Attacks.
fb14d0903dcb142210d09d168d0e7272d143fb9ec59f4aea8414793dabf2f3d3A Multimodel Approach to the Detection of Web-based Attacks.
9117f01a49f372f1077722bd13c30ab099dadef91785ce47ff698440299999b1ADAM: Detecting Intrusions by Data Mining.
365871b2726492c541c1128a5b7aa28e3b8f49a1efca1a45ea31c32a99328740Adaptive ModelBased Monitoring and Threat Detection.
ffb2ace3c126a841b0995e6762b65668e80fa180369921ba297bf8a07215995cAdvanced Polymorphic Worms: Evading IDS by Blending with Normal Traffic.
172077357cd30fcc62e04169f1ec84f6a94d98bf29814df319b1c50ade80699aAn Analysis of 1999 DARPA for Network Anomaly Detection.
d4666f6ffd4ce7a95bacc505648efa236a6525bb48d04ed5b62be09a89deaf2bAnagram: A Content Anomaly Detector Resistant to Mimicry Attack.
b8315ea07cf451e421585c010d3d279254f025a76e8535e1570373c64d43931cArtificial Neural Networks for Misuse Detection.
453df9e792073f3916624b46fe6e9046520fa730ae9f4f767c0dd6fc2b1dbba3Anomalous Payloadbased Network Intrusion Detection.
9c25b1fec06554bffaf334517971c4cb2970439182656787fe2c7be234ba7537Anomalous Payloadbased Worm Detection and Signature Generation.
1a316e80a29f60a55607e500d38fbace3e0c8aa7b2006af81a622cbbe5f4d5c0Anomaly Detection of Webbased Attacks.
c369809658f5a0f07f13ac5ff735d08a77fc9ec3cf8423f28b77e5130f59be51Application of Artiticial Neural Network to Misuse Detection: Initial Results.
ad265ece6bdbe90f06722c37a8c536e35747fae08fb3245b7017a1639611694eAudit Data Reduction for Intrusion Detection.
b35c688d5912ca6b3d789328c4e4a6e187a7d8c3ef95b11e1529030e8287538dAutograph: Toward Automated, Distributed Worm Signature Detection.
0cb4a3046f7bf52bd0b79c0cbfe693b088d13cc12fc0289d06e30e18c8114e8cBayesian Event Classification for Intrusion Detection.
ad80f2bb538c68b96ee709af75a70a2fae32e56977d7f19e998361089e52922dBro: A System for Detecting Network Intruders in RealTime.
a6a812761c18136a77155455be3a7647d70dec890681e1d874f2143672587d31Characteristics of Network Flow Anomalies.
2af73f0d81a7be88804e65be8fc333406c2fbbd53f394f35f29fe3432578771fCombining Knowledge Discovery and Knowledge Engineering to Build IDSs.
d1e793eb894a058b611199b27ae1fdafbd3b6366813722d9d8a1243fd4743797Connectionhistory Based Anomaly Detection.
83f53982d1f972a9de97b6bbee118e150b2b9cc20cd442db5d0cbe80d1947eb3
© 2022 Packet Storm. All rights reserved.
%7Cutmcsr%3D(direct)%7Cutmcmd%3D(none)){kind=small}
Follow us on Twitter
Follow us on Facebook
Subscribe to an RSS Feed