Research Paper | Computer Science & Engineering | Sudan | Volume 6 Issue 9, September 2017
Intrusion Detection Using Neural Network: A Literature Review
Asma Abbas Hassan, Alaa F. Sheta, Talaat M. Wahbi
Nowadays the computer security is important in our society,. Because of the wide use of computer networks and its application, it becomes imperative to detect the network attacks to protect the information security.therefor, anyone using a computer is at some risk of intrusion, even if he is not connected to the Internet or any other network. If the computer is left unattended, any person can attempt to access and misuse the system. The problem is, however, greater if the computer is connected to a network, especially the Internet. Any user from any place in the world can reach the computer remotely and may attempt to access private information. Solving the problem of attack detection using intrusion detection against computer networks is being a major problem in the area of network security. The intrusion detection system meets some challenges, and there are different approaches to deal with these challenges, neural network and machine learning is the best approaches to deal with it. In this paper we will illustrate different approaches of Intrusion detection system using neural network in briefly, and their advantages and disadvantages.
Keywords: intrusion detection system, HIDS, NIDS, Hybrid IDS, anomaly detection, misuse detection
Edition: Volume 6 Issue 9, September 2017
Pages: 343 - 347
How to Cite this Article?
Asma Abbas Hassan, Alaa F. Sheta, Talaat M. Wahbi, "Intrusion Detection Using Neural Network: A Literature Review", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=4091703, Volume 6 Issue 9, September 2017, 343 - 347