Abstract-In the era of info rmation and communicat ion technology, Security is an important issue. A lot of effort and finance are being invested in this sector. Intrusion detection is one of the mos t prominent fields in this area. Data min ing in network intrusion detection can automate the network intrusion detection field with a greater efficiency. This paper presents a literature survey on intrusion detection system. The research papers taken in this literature survey are published fro m 2000 to 2012. We can see that almost 67 % of the research papers are focused on anomaly detection, 23 % on both anomaly and misuse detection and 10 % on misuse detection. In this literature survey statistics shows that 42 % KDD cup dataset, 20 % DA RPA dataset and 38 % other datasets are used by the different researchers for testing the effectiveness of their proposed method for misuse detection, anomaly detection or both.
Medium carbon steel (EN8) substrates with different Surface Roughness (SR) were deposited by Titanium Nitride (TiN). The research work was carried out to investigate the effect of SR and thickness of the thin film coating on substrate structure and tribological properties. EN8 rectangular blocks (60x10x10mm) were used as substrate materials. The variations in SR were achieved by using emery paper on one side and by machining the other side. Scratch tests were conducted and they showed that TiN coatings on substrate with higher SR (1.2 µm) exhibited less adhesion strength compared to TiN coatings on substrate with a lower SR (0.4 µm). Scratch tests also indicated poor adhesion with an increase in the SR of the substrate. The traction force and Coefficient of Friction (COF) were measured during the dry scratch tests under different normal loads, sliding speeds and ramp load conditions. To examine the morphologies of coated substrates and worn surfaces after the scratch test, optical microscopy was utilized. It was found out that TiN coating with a substrate roughness of 0.4 µm exhibited a lower COF and its wear mechanism was adhesive wear. It was experimentally found out that by decreasing the SR of the substrate coatings, wear resistance could be improved.
Abstract-Intrusion detection system is the most important part of the network security system because the volume of unauthorized access to the network resources and services increase day by day. In this paper a genetic algorithm based intrusion detection system is proposed to solve the problem of the small disjunct in the decision tree. In this paper genetic algorithm is used to improve the coverage of those rules which are cope with the problem of the small disjunct. The proposed system consists of two modules rule generation phase, and the second module is rule optimization module. We tested the effectiveness of the system with the help of the KDD CUP dataset and the result is compared with the REP Tree, Random Tree, Random Forest, Naï ve Bayes, and the DTLW IDS (decision tree based light weight intrusion detection system). The result shows that the proposed system provide the best result in comparison to the above mentioned classifiers.
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