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Authors
Affiliations
1 Department of Computer Applications, Erode Sengunthar Engineering College, Perundurai, Erode – 638 057, Tamilnadu, IN
2 Department of Computer Science, Erode Arts & Science College, Erode – 638 009, Tamilnadu, IN
Source
Networking and Communication Engineering, Vol 11, No 12 (2019), Pagination: 200-205
Abstract
The security of computer networks plays a strategic role in modern computer systems. Distributed Denial of Services (DDOS) act as the ‘‘second line of defense’’ placed inside a protected network and looking for known or potential threats in network traffic and/or audit data recorded by hosts. The system is developed a Distributed Denial of Service attacks detection method using LAMSTAR neural network to classify observed system activities and compared the performance of LAMSTAR method. LAMSAR method gives better performance at the cost of testing time high Computational complexity and Training time than the other classification techniques. The system is further reduced the dimension of the data using principal component analysis by reducing the Computational Complexity of LAMSTAR DDOS which in turn reduces the testing and training time with almost the same performance.
Keywords
Distributed Denial of Service, LAMSTAR, PCA, False Alarm Rate.
