Detecting Network Intrusion Using Computational Intelligence

According to rapid development and popularity of Internet and online procedures, the potential of network attacks has increased substantially in recent years. Therefore, network security needs to be concerned to provide secure information channels. Intrusion Detection System (IDS) becomes an essential component of computer security. This work is devoted to focus on how to construct a fast accurate NIDS. The book propose two different hybrid NIDS, the proposed hybrid NIDS models involves data pre-processing, data reduction and intrusion classificationtion. Experiments and Analysis of the proposed hybrid NIDSs with other previous NIDSs demonstrated that; the two proposed hybrid NIDSs enhance the intrusion detection rate and decreasing the testing speed.

Autorentext

Dr. Ahmed Elngar is assistant professor of computer Science. He graduated with a B.Sc. from Al-Azhar University. He received his Master from Ain Shams University. Also he received his P.hD from Al-Azhar University. He is a member of Scientific Research Group in Egypt (SRGE) and Egyptian Mathematical Society (EMS). He published more fifteen papers.