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FRAMEWORK FOR ADAPTIVE INTRUSION DETECTION SYSTEM USING NAÏVE BAYES RECOGNITION

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FRAMEWORK FOR ADAPTIVE INTRUSION DETECTION SYSTEM USING NAÏVE BAYES RECOGNITION

 

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CHAPTER ONE

INTRODUCTION

Background of the Study

The rapid growth of internet in the recent past years, together with the enormous number of computers and other devices that link up to share resources; this open up the computer networks to be vulnerable of various devastating threats (Zhou and Zhao, 2013).

The diverse of types of attacks are – Probing, ping of death, OS fingerprinting, denial of service (DoS), user to root (U2R), remote to local (R2L) and others which affect the efficiency of network.

The issue has made computer security experts to come up with improved and new techniques to explore and curtail such threats (Al-Saedi, Al-Khafaji, ALmomani and Ramadass, 2011).

Some security measures like data encryption, firewall and authentication have been developed and used to serve as first line of defense. They only serve as perimeter fencing which are effective only in protecting and preventing unauthorized access to the systems/network but, not capable of monitoring within network traffic where majority of threats take place.

FRAMEWORK FOR ADAPTIVE INTRUSION DETECTION SYSTEM USING NAÏVE BAYES RECOGNITION

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