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dc.contributor.authorKirwa, Solomon Cheruiyot
dc.date.accessioned2011-07-22T07:21:44Z
dc.date.available2011-07-22T07:21:44Z
dc.date.issued2009
dc.identifier.citationQA76.87.K57 2009en_US
dc.identifier.urihttp://hdl.handle.net/11071/1553
dc.descriptionPartial fulfillment for award of the degree of Master of Science in Information Technology.en_US
dc.description.abstractIntrusion detection systems are increasingly a key part of systems defense. Various approaches to intrusion detection are currently being used, but they are relatively ineffective. A major concern of existing anomaly intrusion detection approaches is that they tend to produce excessive false alarms. One reason for this is that the normal and abnormal behaviour of a monitored object can overlap or be very close to each other which makes it difficult to define a clear boundary between the two. This thesis presents a fuzzy logic model for misuse and access intrusion detection where instead of using crisp conditions, or fixed thresholds, fuzzy sets are used to represent the parameter space as defined by a human expert. This is implemented using a neuro-fuzzy system which is a high breed system combiningen_US
dc.language.isoenen_US
dc.publisherStrathmore Universityen_US
dc.subjectSecurity systemsen_US
dc.subjectFuzzy logicen_US
dc.subjectIntelligent Systemsen_US
dc.titleAnomaly and misuse intrusion detection model : using neuro-fuzzy logic.en_US
dc.typeThesisen_US


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