Anomaly and misuse intrusion detection model : using neuro-fuzzy logic.
Publication details: Nairobi Strathmore University 2009Description: v; 62pSubject(s): LOC classification:- QA76.87.K57 2009
Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
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Thesis | Strathmore University (Main Library) Open Shelf | TH | QA76.87.K57 2009 | Not for loan | 69829 |
Partial fulfillment for award of the degree of Master of Science in Information Technology.
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Intrusion 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 combining
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