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Support vector machine SVM is a branch of artificial intelligence. SVM has many advantages in solving small sample size, nonlinear and high dimensional pattern recognition problem. Kernel function is the key technology of SVM, the choice of Kernel function will affect the learning ability and generalization ability of SVM, and different kernel function will construct different SVMS. At present, there...
Recently network intrusion detection is one of the hottest research topics. Existing network-based Intrusion Detection System (IDS) has drawbacks in many aspects, among of which the two outstanding problems are the high ratio of false alarms and the lack of self-adaptation. The powerful information processing capabilities of the biological immune system, such as feature extraction, pattern recognition,...
Intrusion detection systems help improve the security of networks by providing early warning and response. To improve the detection of attacks, sharing data among distributed nodes or terminals and collaborating on a decision is key. This paper presents a distributed and collaborative intrusion detection (DaCID) system that relies on Dempster Shafer theory of evidence for fusing data from multiple...
The implementation of network security devices such as firewalls and IDSs are constantly being improved to accommodate higher security and performance standards. Using reliable and yet practical techniques for testing the functionality of firewall devices particularly after new filtering implementation or optimization becomes necessary to assure required security. Generating random traffic to test...
Modern forensic analytics applications, like network traffic analysis, perform high-performance hypothesis testing, knowledge discovery and data mining on very large datasets. One essential strategy to reduce the time required for these operations is to select only the most relevant data records for a given computation. In this paper, we present a set of parallel algorithms that demonstrate how an...
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