With the growth in the present digital era, the Internet is the prime source of knowledge. This situation is depleted by phishers and they have drafted various websites which steals userâs information and misuse it. Though it is hard to locate a phishing site, various features of the phishing site helps in uncovering its mask. This paper discusses several features to identify a phishing site. Using data mining techniques like classification and association rule mining many explorations are performed to prove the notion. Similarly, the impact of various features considered for analysis is studied too.

Geetha Mary A

Department of Database Systems

School of Computer Science and Engineering

Vellore Campus

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

&nbsp;

&nbsp;

VIT University

Evaluation of Features to Identify a Phishing Website Using Data Analysis Techniques

Advances in Intelligent Systems and Computing Information Systems Design and Intelligent Applications

The present age of internet and the rising of business have resulted into many folds of increase in the volume of data which are to be used for various applications on a day to day basis. Therefore, it is an obvious challenge to reduce the dataset and find useful information pertaining to the interest of the organisation. But another challenge lies in hiding sensitive information in order to provide privacy. Thus, attribute reduction and privacy preservation are two major challenges in privacy preserving data mining. In this paper, we propose a sensitive rule hiding model to hide sensitive fuzzy association rules. Proposed model uses rough set on intuitionistic fuzzy approximation spaces with ordering to reduce the dataset dimensionality. We use triangular and trapezoidal membership function to get the fuzzified information system. Finally, decreasing the support of right hand side of the rule is used to hide sensitive fuzzy association rules.

International Journal of Autonomous and Adaptive Communications Systems

Privacy preservation in fuzzy association rules using rough set on intuitionistic fuzzy approximation spaces and DSR

International Journal of Telemedicine and Clinical Practices

Fuzzy-based random perturbation for real world medical datasets

Abstract In the present age of Internet, data is accumulated at a dramatic pace. The accumulated huge data has no relevance, unless it provides certain useful information pertaining to the interest of the organization. But the real challenge lies in hiding sensitive information in order to provide privacy. Therefore, attribute reduction becomes an important aspect for handling such huge database by eliminating superfluous or redundant data to enable a sensitive rule hiding in an efficient manner before it is disclosed to the public. In this paper we propose a privacy preserving model to hide sensitive fuzzy association rules. In our model we use two processes, named a pre-process and post-process to mine fuzzified association rules and to hide sensitive rules. Experimental results demonstrate the viability of the proposed research.

Journal	Data powered by TypesetAdvances in Intelligent Systems and Computing Information Systems Design and Intelligent Applications
Publisher	Data powered by TypesetSpringer Singapore
ISSN	2194-5357
Open Access	0