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ISSN : 2321–8045
Impact Factor : 3.4218[UIF-2017]
Archived Articles : Volume: I Issue: III, 8 August 2013
9
Intrusion Detection System using Self Organizing Map (SOM): A Review
Samarjeet Borah, Anindita Chakraborty
Abstract
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As there is a rapid expansion in computer usage and its networks the security of computer system has become very essential. Everyday there are new kinds of attacks which are faced by the industries. Many algorithms are been proposed for the intrusion detection system development using artificial intelligence technique. One such algorithm is Self Organizing Map. The aim of intrusion detection system is to identify attacks with a high detection rate and low false alarm rate. The neural network which are capable of supervised learning after the characteristics of the user behavior are able to identify the abnormalities present, but they have their own disadvantages –they are not able to detect new intrusions. Consequently unsupervised learning methods were given a closer look. In the field of intrusion detection system the anomaly detection aspects is very important and thus there are many approaches that are addressing these security issues. The usage of Self Organizing Map (SOM) along with its different SOM algorithm is applied to the problem of host based intrusion detection networks.

10
Association Between The Acute Low Back Pain And Kinesiophobia – A Correlation Study
B.Arun, S.Mohamed Auriff And M.S.Nagarajan
Abstract
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Low back pain is one of the most frequent problems treated by Orthopaedicians. It is becoming increasingly problematic over the past century, it receive increasing amount of attention and concern due to the burdens placed on health systems and social-care systems. There are evidences showed that fear of movement has close association with low back pain. This study aims to find out the association between the acute low back pain and kinesiophobia. 100 subjects were selected by convenient sampling method with the age group ranging from 20—40 years. Subjects were chosen following suitable inclusion and exclusion criteria. The study was conducted for 6 months. The outcome measures were pain and kinesiophobia. The pain was assessed using visual analog scale and the kinesiophobia was assessed using Tampa scale of kinesiophobia. Karl pearlson's correlation coefficient is used to compute the result between the acute low back pain and kinesiophobia. The result found that it was 0.859 which shows a high correlation between the back pain and kinesiophobia.

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