JSE_V9_N1_RP1 D.P. Gaikwad Kiran Kale Shabnoor Pathan Lokesh Chandawar Vivek Firake Journal on Software Engineering 2230 – 7168 9 1 9 16 ANN, Multilayer Perceptron, Anomaly Detection, NSL-KDD With the increased use of internet, cyber threats have increased exponentially. To prevent our system from such threats, we need an anomaly detection system that will inspect all the network activities and identify any suspicious pattern that may indicate breach of security resulting in damage of computing resources. In this paper, the authors are introducing anomaly detection system that uses multilayer perceptron, a model of Artificial Neural Network (ANN). In this system, Multilayer Perceptron uses backpropagation learning algorithm. For training and testing purpose, they have used NSLKDD dataset. The trained model of Multilayer Perceptron is then used for real-time anomaly detection using tcpdump (packet sniffing tool in Linux). This system has successfully achieved a very low false-positive rate. July - September 2014 Copyright © 2014 i-manager publications. All rights reserved. i-manager Publications http://www.imanagerpublications.com/Article.aspx?ArticleId=3209