A Phishing Detection Framework for Websites Based on Data Mining

Authors(5) :-Srushti Nawade, Shubhangi Wankhede, Dhanshree Bhaspale, Shubhangi Sathwane, Prof. Vikas Bhowate

Detecting any Phishing site is extremely an intricate and dynamic issue including numerous variables and criteria. Due to the ambiguities associated with phishing location, fluffy information mining procedures can be a viable instrument in detecting phishing websites. In this paper, we propose a strategy which consolidates fluffy rationale alongside information digging algorithms for detecting phishing websites. Here, we characterize 3 diverse phishing types and 6 unique criteria for detecting phishing websites with a layer structure. We have utilized the SVM Data Mining algorithm for classification. Besides, this we also compare the efficiency of SVM in terms of time and space complexity with Naive Bayes algorithm, the framework proactively disposes of the Phishing site or Phishing page by sending a notice to the System Administrator of the host server that it is hosting a Phishing site which may result in the evacuation of the site. Moreover, in the wake of ordering the Phishing email, the framework recovers the location, IP address and contact data of the host server.

Authors and Affiliations

Srushti Nawade
BE Scholar, Department of Information Technology, St. Vincent Pallotti College of Engineering and Technology, Nagpur, Maharashtra, India
Shubhangi Wankhede
BE Scholar, Department of Information Technology, St. Vincent Pallotti College of Engineering and Technology, Nagpur, Maharashtra, India
Dhanshree Bhaspale
BE Scholar, Department of Information Technology, St. Vincent Pallotti College of Engineering and Technology, Nagpur, Maharashtra, India
Shubhangi Sathwane
BE Scholar, Department of Information Technology, St. Vincent Pallotti College of Engineering and Technology, Nagpur, Maharashtra, India
Prof. Vikas Bhowate
Assistant Professor, Department of Information Technology, St. Vincent Pallotti College of Engineering and Technology, Nagpur, Maharashtra, India

Data Mining, SVM, Phishing, URL, Naive Bayes, Classification

  1. Joao Leal,Rui Couto,Pedro Mauricio,Teresa Galvao: IEEE tra- sanction on ”Exploring ticketing approaches using mobile technolo- gies:QR Codes,NFC and BLE” In:18th International Conference on In- telligent Transportation System (2015).
  2. Linli Hu, Yuhao Wang, Dong Li, Jing Li: IEEE transaction on” A hybrid client/server and browser/server mode-based universal mo- bile ticketing system”, In: ICIME.2010.
  3. V N Kamalesh, Vikram Ravindra, Pradeep P Bomble, M P Pa- van, B K Chandan, S K Srivatsa:” virtual ticketing International Research Journal of Engineering and Technology system” In: Inter- national Conference on e-Education, Entertainment and e-Management (2011).
  4. Yue Liu, Ju Yang, Mingjun Liu:” Recognition of QR Code with mobile phones”, In: -CCDC.2008.
  5. Li Li, Wu Chou:” Design and Describe REST API without Vi- olating REST: A Petri Net Based Approach”, In: IEEE International Conference on Web Services 2011.
  6. Beng Bao, L. Anantharaman, R. Deng:” Design of portable mobile devices based e-payment system and e-ticketing system with digital signature”, In: ICII.2001.

Publication Details

Published in : Volume 5 | Issue 2 | March-April 2019
Date of Publication : 2019-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 651-656
Manuscript Number : CSEIT1726141
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Srushti Nawade, Shubhangi Wankhede, Dhanshree Bhaspale, Shubhangi Sathwane, Prof. Vikas Bhowate, "A Phishing Detection Framework for Websites Based on Data Mining", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 5, Issue 2, pp.651-656, March-April-2019.
Journal URL : http://ijsrcseit.com/CSEIT1726141

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