Survey on Exception Rules and Anomaly Detection

Authors(2) :-S. Senthil Kumar , Dr. S. Mythili

This paper discusses about literature survey of exception rules and anomaly detection. This survey provides an overview of the research on anomaly detection. There exists a great variety of tools used for detecting outliers, exceptions or anomalies: expert systems, neural networks, clustering techniques, and association rules are some of them.

Authors and Affiliations

S. Senthil Kumar
Ph.D. Research Scholar, Department of Computer Science, Kongunadu Arts and Science College, (Autonomous), Coimbatore, Tamil Nadu, India
Dr. S. Mythili
Associate Professor & Head, Department of Information Technology, Kongunadu Arts and Science College, (Autonomous), Coimbatore, Tamil Nadu, India

Anomaly detection, anomalous rule, exception rule.

  1. Ayesha Azeema. Maniyar, Chaitra. L. Mugali, Padma. Dandannavar, Banking Fraud Analysis and Decision Support System, International Journal of Innovative Research in Advanced Engineering, Volume 2, Issue 8, August 2015.
  2. Mohamed Hegazy, Ahmed Madian, Mohamed Ragaie, Enhanced Fraud Miner: Credit Card Fraud Detection using Clustering Data Mining Techniques, Egyptian Computer Science Journal, Volume 40, Issue 03, September 2016.
  3. Oluwafolake Ayano and Solomon O. Akinola, A multi-algorithm data mining classification Approach for bank fraudulent transactions, African Journal of Mathematics and Computer Science  Research, Vol. 10(1), June 2017.
  4. Marwan Fahmi, Abeer Hamdy, Khaled Nagati, Data Mining Techniques for Credit Card Fraud Detection: Empirical Study, Sustainable Vital Technologies in Engineering & Informatics, November 2016.
  5. Raihan Ul Islam, Mohammad Shahadat Hossain, Karl Andersson, A novel anomaly detection algorithm for sensor data under Uncertainty, Springer, November 2016
  6. M. Dolores Ruiz, Daniel S´anchez,  Miguel Delgado, Maria J. Martin-Bautista, Discovering Fuzzy Exception and Anomalous Rules, Vol:24,Issue:4,PP: 930 - 944 Aug 2016.
  7. Raihan Ul Islam, Mohammad Shahadat Hossain, Karl Andersson, "A novel anomaly detection algorithm for sensor data under uncertainty", Soft Computing, 2016, ISSN 1432-7643.
  8. Anomaly Detection : A Survey, Varun Chandola,ArindamBanerjee,VipinKumar,ACM Computing Surveys, PP: 1–72. September 2009.
  9. Bassam Khorchani and Sylvain Hallé,Roger Villemaire, Firewall Anomaly Detection With A Model Checker for Visibility Logic, IEEE Network Operations and Management Symposium,PP:16-20,April 2012.
  10. M. Dolores Ruiz, Maria J. Martin-Bautista, Daniel Sánchez, M. Amparo Vila, Anomaly detection using fuzzy association Rules, International Journal of Electronic Security and Digital Forensics, Volume 6, Issue 1, ISSN: 1751-911X, Pages 25-37, March 2014.

Publication Details

Published in : Volume 2 | Issue 6 | November-December 2017
Date of Publication : 2017-12-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 521-525
Manuscript Number : CSEIT1726158
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

S. Senthil Kumar , Dr. S. Mythili, "Survey on Exception Rules and Anomaly Detection ", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 6, pp.521-525, November-December-2017.
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