By Purwanto, C. Eswaran, R. Logeswaran (auth.), Azizah Abd Manaf, Shamsul Sahibuddin, Rabiah Ahmad, Salwani Mohd Daud, Eyas El-Qawasmeh (eds.)
This 4-Volume-Set, CCIS 0251 - CCIS 0254, constitutes the refereed complaints of the foreign convention on Informatics Engineering and data technology, ICIEIS 2011, held in Kuala Lumpur, Malaysia, in November 2011. The 210 revised complete papers awarded including invited papers within the four volumes have been rigorously reviewed and chosen from quite a few submissions. The papers are equipped in topical sections on e-learning, info safeguard, software program engineering, picture processing, algorithms, man made intelligence and smooth computing, e-commerce, information mining, neural networks, social networks, grid computing, biometric applied sciences, networks, disbursed and parallel computing, instant networks, details and information administration, internet purposes and software program structures, multimedia, advert hoc networks, cellular computing, in addition to miscellaneous issues in electronic details and communications.
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Extra info for Informatics Engineering and Information Science: International Conference, ICIEIS 2011, Kuala Lumpur, Malaysia, November 14-16, 2011, Proceedings, Part III
The Number of Foreign Tourists Arrivals via Soekarno-Hatta Airport Tourist Arrivals (Thousands) 150 125 100 75 50 Month Jan Year 1989 Jan 1992 Jan 1995 Jan 1998 Jan 2001 Jan 2004 Jan 2007 Fig. 1. Plot of the number of foreign tourist arrivals in Indonesia via Soekarno-Hatta airport Design of Experiment to Optimize the Architecture of Wavelet Neural Network 19 The Number of Foreign Tourist Arrivals via Ngurah Rai Airport Tourist Arrivals (Thousands) 250 200 150 100 50 0 Month Jan Year 1989 Jan 1992 Jan 1995 Jan 1998 Jan 2001 Jan 2004 Jan 2007 Fig.
Dorothy Denning in 1987. Her proposed model is the basic core of the methodologies of intrusion detection in use today . The intrusion detection is either anomaly detection or misuse detection. Anomaly detection is the identification of the normal activities and misuse detection is the detection of attacks on the basis of attack signatures through pattern matching approach. There are many flaws in an intrusion detection system like false positive and false negative. In such cases the IDS needs more training data to be trained and more time to gain better performance rate .
Different Kernels of SVM are used for different problems to enhance performance rate. In this paper, we provide a review of the SVM and its kernel approaches in IDS for future research and implementation towards the development of optimal approach in intrusion detection system with maximum detection rate and minimized false alarms. Keywords: Intrusion Detection System (IDS), SVM, Kernel, RBF, Knowledge Discovery and Data Mining (KDD), Defense Advanced Research Projects Agency (DARPA). 1 Introduction With the continuous advancement in the computer technology and specially the internet, the exposure of malicious attacks and illegal accesses to computer systems is also increasing at a high rate [1-3].