Techniques Used for Detection of Mobile Spyware
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International Journal of Computer Trends and Technology (IJCTT) |  |
| © 2014 by IJCTT Journal | ||
| Volume-11 Number-5 |
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| Year of Publication : 2014 | ||
| Authors : Neelam Kaur | ||
| DOI : 10.14445/22312803/IJCTT-V11P146 |
Neelam Kaur."Techniques Used for Detection of Mobile Spyware". International Journal of Computer Trends and Technology (IJCTT) V11(5):217-219, May 2014. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract -
Spyware is an unwanted software that steals bank account details and other confidential information and sends back to the attacker from where the spyware originated. The attacker makes use of this information to send spam messages according to the location of the user. They can also cause a financial loss to the user. The spyware attack on Smartphone has increased with the drastic increase in the number of Smartphone users. Smartphone is widely used all over the world for communication, banking transactions and for many other purposes. These phones have lots of functionality to support user’s demand and this is one of the main reasons which make it difficult to detect the spyware. There are different types of techniques available to detect the spyware. The different techniques are signature based, behavioral based and data mining based. In this paper, pros and cons of each technique have been discussed.
References
[1] R. Shams, M. Farhan, S. khan, F. Hashmi, Comparing Anti Spyware Products – A different Approach, IEEE, 2011, 75-80.
[2] T. Weil, A. Jengi, H. Lee, C. Chen, C. Tien, Android Privacy, International Conference on Machine Learning and Cybernetics, 2012, 1830-1837.
[3] J. Mu, A. Cui1, J. Rao, Android Mobile Security – Threats and Protection,International Conference on Computer, Networks and Communication Engineering, 2013, 683-686.
[4] H. Rui, J. Gang, W. Liang , Security Mechanism Analysis of Open-Source Andriod OS & Symbian OS, IEEE, 2012, 3497-3501.
[5] S. Datta, C. Bonnet, N. Nikaein, Android Power Management: Current and Future Trends, IEEE, 2012, 48-53.
[6] D. Venugopal, G. Hu, Efficient signature based malware detection on mobile devices, Mobile Information Systems, 4(1), 2008, 33-40.
[7] A. Shabtai, U. Kanonov, Y. Elovici , C. Glezer, Y. Weiss, Andromaly: a behavioral malware detection framework for android devices, Springer, 2012, 161–190.
[8] A. Bose, X. Kang, G. Shin, T. Park, Behavioral Detection of Malware on Mobile Handsets, ACM, 2008, 225-238.
[9] S. Shirbhate, Dr V. Thakare, Dr S. Sherekar, Data Mining Approaches For Network Intrusion Detection System, International Journal of Computer Technology and Electronics Engineering (IJCTEE) National Conference on Emerging Trends in Computer Science and Information Technology, 2011, 41-44.
Keywords
Smartphone, Spyware