Network intrusion detection systems have become a standard component in security infrastructures. Unfortunately, current systems are poor at detecting novel attacks without an unacceptable level of false alarms. We propose that the solution to this problem is the application of an ensemble of data mining techniques which can be applied to network connection data in an offline environment, augmenting existing real-time sensors. In this paper, we expand on our motivation, particularly with regard to running in an offline environment, and our interest in multisensor and multimethod correlation. We then review existing systems, from commercial systems, to research based intrusion detection systems. Next we survey the state of the art in the area. Standard datasets and feature extraction turned out to be more important than we had initially anticipated, so each can be found under its own heading. Next, we review the actual data mining methods that have been proposed or implemented. We conclude by summarizing the open problems in this area, along with some questions of a broader scope. We hope that by providing the motivation and summarizing the work in this area that we can stimulate further research.

Threats have become a big problem since the past few years as computer viruses are widely recognized as a significant computer threat. However, the role of Information Technology security must be revisit again since it is too often. IT security managers find themselves in the hopeless situation of trying to uphold a maximum of security as requested from management. At the same time they are considered an obstacle in the way of developing and introducing new applications into business and government network environments. This paper will focus on Transmission Control Protocol Synchronize Flooding attack detections using the Internet Protocol header as a platform to detect threats, especially in the IP protocol and TCP protocol, and check packets using anomaly detection system which has many advantages, and applied it under the open source Linux. The problem is to detect TCP SYN Flood attack through internet security. This paper also focusing on detecting threats in the local network by monitoring all the packets that goes through the networks. The results show that the proposed detection method can detect TCP SYN Flooding in both normal and attacked network and alert the user about the attack after sending the report to the administrator. As a conclusion, TCP SYN Flood and other attacks can be detected through the traffic monitoring tools if the abnormal behaviors of the packets are recognized such as incomplete TCP three-way handshake application and IP header length.