Enhanced Intrusion Detection System Using Machine Learning Techniques.

      Аннотация: This book provides a machine learning technique was proposed to identify the network attacks. IDS is an important technology that monitors the network traffic and identifies the network intrusions. The primary objective of this rule based intrusion detection system detects the errors with high detection rate and low false alarm rate. This book contains five chapters with including programs. Chapter 1: Covers Fundamental, motivation and Problems in IDS. Chapter 2: Discusses IDS Classification and methods. Chapter 3: Explains Development of Intrusion Detection System using Rule based Decision Tree (C4.5) Algorithm. Chapter 4: Explains Modeling of Intrusion Detection System using Rule based Genetic Algorithm. Chapter 5: Conclusions and Future work.

Ключевые слова: Anomaly Detection, Detection Rate, False Alarm Rate, fitness function, genetic algorithm, Intrusion detection system, Rule Base, KDDCup99 Dataset, Decision tree. C4.5 algorithm, Machine LearningTecniques.