Combining 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.
b90399dd9a3cc0d592bd51c7120b738e541023f3f1c7418542dd0d85860168afUsing Aritificial Anomalies to Detect Unknown and Known Network Intrusions.
3b377a761ba35262df65a76dd11b3dbc95ee7a4736d59ecf1eb8a64df9199939Using Program Behavior for Intrusion Detection.
095e99067c52c8430859ca16f922ac5e9d525d0d3381bb91f5e9d21f45cf1521A RealTime Intrusion Detection System based on Learning Program Behavior.
0e8a47781283f6cc330dddf6e88f496211be2a23d3b455a2013438fb5378ecbbAn Application of Machine Learning to Anomaly Detection.
382e3dd60f7bbf10b274abc609279cb4d359796893a194a890770cbccf87e701An Immunological Approach to Change Detection: Algorithms, Analysis and Implications.
9aa8bbbecb2de8548f2276bf36961313f1b9e3ab6748c5453b3acfc1b4efd985
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