June 2018 Issue Vol.8 No.6

Application of Data Mining Methods in the Analysis of Different Attacks on Network https://ia601509.us.archive.org/25/items/vol8no0601/vol8no0601.pdf
Shilpa Srivastava
M.Tech. Research Scholar, CSED, BERI, Bhopal,India
Dr.Mohit Gangwar
Principal/Professor (CSED), BERI, Bhopal,India

Abstract: Many of us connect to Wireless Fidelity (Wi-Fi) without knowing what specific threats one is vulnerable. The list of vulnerabilities is large by nature, and most of these ignored by users. Computer networking has made collaboration necessary to both attackers and defenders. Phishing attacks combine technology and social engineering to gain access to restricted information. The most common phishing attacks today send mass email directing the victim to a web site of some perceived authority. This paper is focused on wireless network and phishing attacks. To analysis attacks on network signal we are applying different data mining algorithms like J48, random Forest and random Tree algorithms on network dataset of 3 years with 6 different attribute name “Company”, “Data Provider”, “Data Used”, “Date”, “Class”, & “Signal” from different telecom companies to achieve 95 to 99% accuracy with a false positive rate of 0.5-1.5% and modest false negatives. Thus, the comparative views shows that J48 algorithm for phishing detection achieves better performance as compared to random Forest and random Tree algorithm.
Keywords:Phishing Attacks, J48, Random Forest, Random Tree, Confusion Matrix, Network Signal.

Framework for Opinion Mining Approach to Augment Education System Performance https://ia601502.us.archive.org/6/items/vol8no0602_201806/vol8no0602.pdf
Amritpal Kaur
Computer Science Engineering Department,Thapar Insititue of Engineering and Technology,Patiala,Punjab,India
Harkiran Kaur
Computer Science Engineering Department,Thapar Insititue of Engineering and Technology,Patiala,Punjab,India

Abstract: The extensive expansion growth of social networking sites allows the people to share their views and experiences freely with their peers on internet. Due to this, huge amount of data is generated on everyday basis which can be used for the opinion mining to extract the views of people in a particular field. Opinion mining finds its applications in many areas such as Tourism, Politics, education and entertainment, etc. It has not been extensively implemented in area of education system. This paper discusses the malpractices in the present examination system. In the present scenario, Opinion mining is vastly used for decision making. The authors of this paper have designed a framework by applying Naïve Bayes approach to the education dataset. The various phases of Naïve Bayes approach include three steps: conversion of data into frequency table, making classes of dataset and apply the Naïve Bayes algorithm equation to calculate the probabilities of classes. Finally the highest probability class is the outcome of this prediction. These predictions are used to make improvements in the education system and help to provide better education.
Keywords:Opinion Mining, Naïve Bayes, Examination System.

Statistical Dimension Identification and Implementation for Student Progression System https://ia601509.us.archive.org/17/items/vol8no0603/vol8no0603.pdf
John Paul.M
Assistant Professor, Sathyabama University, Chennai, Tamil Nadu, India
Assistant Professor,Jeppiaar Maamallan Engineering College, Chennai, Tamil Nadu, India

Abstract: e-Commerce is a emerging platform where the business are brought into the next level in modern business industries like Manufacturing, Banking, Tourism ,Hospitality and other service providers in India. The upcoming business players are adopting multi dimensional approach to reach the path of success. The major challenges and task of all kind of business is to maintain the large customer forum to make the industry healthy. The CRM is a most popular method to strengthen the business and customer value to reach the point of success. This study is the attempt to bring the challenges, needs and importances of e-commerce by adopting appropriate applications and tools. We brought some recommendations and conclusion based on findings to shape the industry to meet the global antagonism.
Keywords:e-banking, Business and Customer.

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