Review On Spyware - A Malware Detection Using Datamining

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2018 by IJCTT Journal
Volume-60 Number-3
Year of Publication : 2018
Authors : Mrs. Pushpa, S.Santhiya
  10.14445/22312803/IJCTT-V60P124

MLA

Mrs. Pushpa, S.Santhiya, Dr. Kalpana Sharma "Review On Spyware - A Malware Detection Using Datamining". International Journal of Computer Trends and Technology (IJCTT) V60(3):157-160 June 2018. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract
Nowadays computers are being threatened to unknown malware activities when it is connected to network. (i.e.) in system, malicious software is downloaded and installed without users knowledge. Malicious software is the one which have an intention to harm the system such as slow downing the network performance, increasing the electricity bill or to get confidential information including bank credit card number, login password details in order to misuse, to have a control over users by screen monitoring and key logger to track key or content typed by user. After gaining or processing, all such information is send to hacker by means of this software. One major type of malware is spyware. Spyware is one kind of malicious software act as spy and help hackers to steal personal information to misbehave. This paper presents the high definition , description of malware , its types and data mining concept which pave the way to detect and remove the malware mainly spyware with its tools and techniques.

Reference
Ravi, C & Manoharan, R. Malware Detection using Windows Api Sequence and Machine Learning . International Journal of Computer Application, Vol.43, No.17, 2012.
[2] Ravi, C & Chetia , G. Malware Threats And Mitigation Strategies: A Survey, Journal of Theoretical and Applied Information Technology, Vol. 29, No. 2, pp. 6973, 2011.
[3] Egele, M. S, A Survey on Automated DynamicMalwareAnalysis.ACM Computing Surveys, Vol. 44, No. 2, 2012. M. Wu, Y. Huang, S. Kuo, “Examining Web-based Spyware invasion with stateful behavior monitoring,” 13th Paci_c Rim International Symposium on Dependable Computing (PRDC '07), 17-19 Dec. Piscataway, NJ, USA: IEEE, pp. 275-81.
[4] Detection of Spyware by Mining Executable Files, 2010 International Conference on Availability, Reliability and Security 978-0-7695-3965-2/10.
[5] “Review on Feature Selection of Gene Expression Data for Autism Classification” – IJIRSET- International Journal of Innovative Research in Science, Engineering and Technology Vol. 5, Issue 3, March 2016 ISSN (Online): 2319-8753 ISSN (Print) : 2347-6710.
[6] “A Survey on Autism Spectrum Disorder Classification” - IJISET - International Journal of Innovative Science, Engineering & Technology Vol. 3 Issue 3, March 2016.ISSN 2348 – 7968.
[7] “Classification Scheme For Detecting Autism Using Three Tier Feature Selection And Single Tier Gene Selection” International Journal of Pure and Applied Mathematics Volume 117 No. 15 2017, 683-697.
[8] Yamini.K , Sivapriyadarshini.S (2010), ―A Data Mining Approach For On Time Detection Of Spyware Threat‖, IEEE International Conference on Computational Intelligence and Computing Research
[9] Bozagac .C.D, ―Application of Data Mining based Malicious Code Detection Techniques for Detecting new Spyware‖, White paper, Bilkent University 2005.
[10] Shahzak, R.K,”Detection of Spyware by Mining Executable files” Availability, Reliability, and Security, 2010. ARES '10 International Conference on Date of Conference: 15-18 Feb. 2010
[11] Nwokedi Idika and Aditya P. Mathur. “A Survey of Malware Detection Techniques.”Technical report, Software Engineering Research Center, 2007.
[12] Martin Boldt, Andreas Jacobsson, Niklas Lavesson, and Paul Davidsson. “Automated Spyware Detection Using End User License Agreements.” isa, 0:445–452, 2008.
[13] N. Lavesson, M. Boldt, P. Davidsson and A. Jacobsson, “Learning to Detect Spyware using End User License Agreements,” Knowledge and Information Systems , in .press.
[14] N. Idika and A. Mathur, "A Survey of Malware Detection Techniques.," Software Engineering Research Center, Technical report 2007.
[15] M. Siddiqui, M. C. Wang, and J. Lee, "Detecting Internet worms Using Data Mining Techniques," Journal of Systemics, Cybernetics and Informatics, vol. 6, no. 6, pp. 48-53, 2009..
[16] R. Veeramani and Rai Nitin, "Windows API based Malware Detection and Framework Analysis," International Journal of Scientific & Engineering Research, vol. 3, no. 3, March 2012.
[17] N. Ye, “The Handbook of Data Mining”. Lawrence Erlbaum Associates, Inc, 2003.
[18] T. Wang et al., "A Surveillance Spyware Detection System Based on Data Mining Methods," 2006.
[19] D. Olson and D. Delen, Advanced data mining techniques. Springer-Verlag Berlin Heidelberg, 2008.
[20] A. Sami, H. Rahimi, B. Yadegari, and S. Hashemi, "Malware Detection Based on Mining API Calls," ACM Symposium on Applied Computing, April 2010.

Keywords
Spyware , Data Mining .