Audit 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.
83f53982d1f972a9de97b6bbee118e150b2b9cc20cd442db5d0cbe80d1947eb3Correlating Alerts Using Prerequistes of Intrusions.
ae24469850810588568de08c56716ae14b11ebffca28d8fec3e3709cee2bebefDetecting Anomalous Network Traffic with Self Organizing Map.
35f6fc49f2f118b61a2578a290fcd7a9ea9b3a61e02de63de73b893e2c04f013Detecting Malicious JavaScript Code in Mozilla.
3a373e1c5e410a6a7e90df53671d281a88a5bbb8ee22fdc81746ce1a45d4cecdDetecting Novel Scans Through Pattern Anomaly Detection.
d3e726f1d583edec97025376ab12655387592df58788e664a74b67c523d02c8eDetecting Viral Propagations Using Email Behaviour Profiles.
fb23fc758f9af49e7aaa360c8c6d01a316f5fe608098b98afee3d5554ea0c21aHoneycom Creating Intrusion Detection Signatures Using Honeypots.
518c2a01e3a12bcb6fe7169f28045b828819c20792e624485680d057a721576bIntrusion Detection Using Ensemble of Soft Computing Paradigms.
7069ade49047a4207c350f03ea0890da5bcc4c30d828be44cbbf7d0909fe1e4aIntrusion Detection with Unlabeled Data Using Clustering.
203845536bf8a4056ea75b4f291a54fe605f5d0b2ed60853813e4892fd0f1bfdIntrusion Detection Systems using Adaptive Regression Splines.
956e6e1661b5da940fea6539767e49bef41367e451013931d9150921faf5637dLanguagebased Generation and Evaluation of NIDS Signatures.
ed8917fb1b075c6ef9358f527ebd1dba0e9d6f5b4b5c339a44ae8a888dd43a4cLearning Rules for Anomaly Detection of Hostile Network Traffic.
b2aaebaa3548816b97c1927df0307e400f856fe942ed9c0ea9e4851bd6ed1d6bMining in a data flow environment: Experience in Netowrk Intrusion Detection.
6b36a8e8324599436c06db8899c2e725fee6a7f5857d48a92f88f852924fe85cNetwork Traffic Anomaly Detection based on Packet Bytes.
44a882e344b2cb8462f473b7cf05fc130df9b13bfae1aef6d5f0ee579305205eNextgeneration Instrusion Detection Expert System (NIDS): A summary.
645f03121cb6387442e2157e3b1bd44a82fd4f6457031eaad2c5d8c0869f4ecdPolygraph: Automatically Generating Signatures for Polymorphic Worms.
da1b41fe602bad7291c8016f7113690ea192d79e0a4c9eba51a3ca9c189192e9Towards Automatic Generation of Vulnerability Based Signatures.
523e5819d0299107dca236e8144187e014692025f0a1a3b3be8e4f35fb8af0b1Towards the Scalable Implementation of a User Level Anomaly Detection System.
57f1dd6e0d045a13b818f2a473907674d803e83aea2a11ab9dd94be6b4941139Undermining an Anomalybased Intrusion Detection System Using Common Exploits.
b90399dd9a3cc0d592bd51c7120b738e541023f3f1c7418542dd0d85860168af
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