Intrusion Detection System Using SPARK'S Machine Learning Library
Secure your network
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Now a day's computer network security problems play a pivotal role. The network is vulnerable towards attacks like DOS, U2R, R2L etc. These attacks take advantage of a network vulnerability to gain illegal access to important information or sometimes create a flood to prevent genuine users from accessing it. Network attackers use massive volume of network traffic in short span of time to create a victim host unavailable whereby a fast and efficient network intrusion detection is a very challenging issue. The size of network traffic has turned into increasingly big and complex and the proposed ...
Now a day's computer network security problems play a pivotal role. The network is vulnerable towards attacks like DOS, U2R, R2L etc. These attacks take advantage of a network vulnerability to gain illegal access to important information or sometimes create a flood to prevent genuine users from accessing it. Network attackers use massive volume of network traffic in short span of time to create a victim host unavailable whereby a fast and efficient network intrusion detection is a very challenging issue. The size of network traffic has turned into increasingly big and complex and the proposed intrusion detection system should be able to process huge size of network data in order to detect intrusion in the network as early as possible. This book entails the implementation of network intrusion detection system using association rule generation and quadric classification using machine learning library of spark.
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