Whitepaper called IDS For Grid and Cloud Computing - An Explanation On Inner Workings and Construction.
354c2e231ed017ede385cce2677f5f85c42d60193ffade2d867a26e4e3caf1b6SNORT is the most widely used open source IDS to date. SNORT has introduced inline mode which can be used to drop packets. Using inline mode, SNORT can be used as firewall as well. This paper outlines how to write common SNORT rules to protect against common web application attacks.
d603d7cd574e3847201f6539864090cf47b67e46dbdcd2a8dafbe7a0b3cb0807A 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.
2af73f0d81a7be88804e65be8fc333406c2fbbd53f394f35f29fe3432578771f
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