Intrusion Detection based on Neural Network and Firefly Algorithm

Intrusion detection system (IDS) , is a dynamic security protection application that monitors network or system activities to guarantee the network security. It is also used to detect unauthorized malicious. Available system based on neural networks fall into a local optimum. Firefly based back-propagation network, can solve the problem of slow convergence speed of the neural network algorithm. In this paper, firefly algorithm (FA) based neural network algorithm is applied to intrusion detection. KDD Cup 99 database was used to evaluate the proposed algorithm; and experimental results show that our proposed method has better detection rate and convergence rate within few iteration and is faster than the single back- propagation networks

کلیدواژه ها:

Intrusion detection ، firefly algorithm ، Artificial neural network ، Back propagation