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Reseach Article

Performance and Maintainability Evaluation of Anti-Spyware System

by Mohamed Adel Sheta, Mohamed Zaki, Kamel Abd El Salam El Hadad, H. Aboelseoud M.
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 150 - Number 4
Year of Publication: 2016
Authors: Mohamed Adel Sheta, Mohamed Zaki, Kamel Abd El Salam El Hadad, H. Aboelseoud M.
10.5120/ijca2016911493

Mohamed Adel Sheta, Mohamed Zaki, Kamel Abd El Salam El Hadad, H. Aboelseoud M. . Performance and Maintainability Evaluation of Anti-Spyware System. International Journal of Computer Applications. 150, 4 ( Sep 2016), 31-39. DOI=10.5120/ijca2016911493

@article{ 10.5120/ijca2016911493,
author = { Mohamed Adel Sheta, Mohamed Zaki, Kamel Abd El Salam El Hadad, H. Aboelseoud M. },
title = { Performance and Maintainability Evaluation of Anti-Spyware System },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2016 },
volume = { 150 },
number = { 4 },
month = { Sep },
year = { 2016 },
issn = { 0975-8887 },
pages = { 31-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume150/number4/26085-2016911493/ },
doi = { 10.5120/ijca2016911493 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:55:03.567120+05:30
%A Mohamed Adel Sheta
%A Mohamed Zaki
%A Kamel Abd El Salam El Hadad
%A H. Aboelseoud M.
%T Performance and Maintainability Evaluation of Anti-Spyware System
%J International Journal of Computer Applications
%@ 0975-8887
%V 150
%N 4
%P 31-39
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Spyware is somewhat of a silent killer, because its essential task is secretly and quietly monitoring or sending victim's sensitive information to a separate third party. Unfortunately, existing anti-spyware systems lack the ability to cope with the rapid changes in the spyware signatures and programs. The main challenge in recent anti-spyware systems is to design efficient system that able to detect new and unknown spywares in a reasonable time. Furthermore, lack of interest in existing anti-spyware systems reusability. This paper introduces an adaptive anti-spyware system that able to deal with unpredictable discovered spywares on run time and improves the detection accuracy. The proposed system adopts design patterns approach in detecting and classifying spyware, in the sense that, reuse existing systems components in detecting new or unknown spywares without performing changes on these systems’ designs. The proposed anti-spyware system can be considered as an engineering product that needs to be verified in terms of performance and maintainability. The aim here is to guarantee the performance of the designed system by defining evaluation methods for assessing the performance and maintainability of this design. Thus, the performance of the proposed system has been evaluated through the adopted data mining evaluation metrics. While, amount of reuse and reusability metrics have been defined to evaluate the proposed system maintainability.

References
  1. Jyoti Landage, and Wankhade “Malware and Malware Detection Techniques: A Survey”, International Journal of Engineering Research & Technology (IJERT), Vol. 2, pp. 61-68, India, 2013.
  2. G. Padmavathi, and S. Divya “A Survey on Various Security Threats and Classification of Malware Attacks, Vulnerabilities and Detection Techniques”, The International Journal of Computer Science & Applications (TIJCSA), Vol. 2, pp. 66-72, India, 2013.
  3. Mohamad Fadli Zolkipli, and Aman Jantan “A Framework for Malware Detection Using Combination Technique and Signature Generation”, IEEE International Conference on Computer Research and Development, pp. 61-68, Malaysia, 2010.
  4. Mohammad Wazid, Avita Katal, R.H. Goudar, D.P. Singh, and Asit Tyagi “A Framework for Detection and Prevention of Novel Keylogger Spyware Attacks”, IEEE International Conference on Intelligent Systems and Control (ISCO), pp. 433-438, India, 2012.
  5. Karan Sapra, Benafsh Husain, Richard Brooks, and Melissa Smith “Circumventing Keyloggers and Screendumps”, IEEE International Conference on Malicious and Unwanted Software, pp. 103-105, USA, 2013.
  6. E. Gamma, R. Helm, R. Johnson, and J. Vlissides “Design Patterns: Elements of Reusable Object-Oriented Software”, Boston, Massachusetts, Addison-Wesley Longman Publishing Co., Inc., USA, 1995.
  7. E. B. Fernandez “A Methodology for Secure Software Design”, International Conference on Software Engineering Research and Practice, USA, 2004.
  8. Raja Khurram Shazhad, Syed Imran Haider, and Niklas Lavesson “Detection of Spyware by Mining Executable Files”, IEEE International Conference on Availability, Reliability and Security (ARES), pp. 295-302, Sweden, 2010.
  9. Raja Khurram Shahzad, Niklas Lavesson, and Henric Johnson “Accurate Adware Detection using Opcode Sequence Extraction”, IEEE International Conference on Availability, Reliability and Security (ARES), pp. 189-195, Czech Republic, 2011.
  10. Zongqu Zhao, Junfeng Wang, and Jinrong Bai1 “Malware detection method based on the control-flow construct feature of software”, International Journal of The Institution of Engineering and Technology (IET) on Information Security, Vol. 8, pp. 18-24, England, 2013.
  11. J. Yoder and J. Barcalow “Architectural patterns for enabling application security”, In Proceedings of the 4th Conference on Patterns Language of Programming (PLoP’97), USA, 1997.
  12. Schumacher and U. Roedig “Security engineering with patterns”, In Proceedings of the 8th Conference on Patterns Language of Programming (PLoP’01), USA, 2001.
  13. M. Hafiz, P. Adamczyk, and R. E. Johnson “Towards an Organization of Security Patterns”, IEEE International Conference on Software, Vol. 24, pp. 52-60, USA, 2007.
  14. Mohamed Adel Sheta, Mohamed Zaki, Kamel AbdEl Salam El Hadad, and H. Aboelseoud M. “Design and Implementation of Anti Spyware System using Design Patterns”, International Journal of Computer Applications, Vol.123, No.2, pp.9-13, USA, 2015.
  15. VX Heavens, http://vx.netlux.org, accessed 01-10-15.
  16. Ian H. Witten, Eibe Frank, and Mark A. Hall, Data Mining: Practical Machine Learning Tools and Techniques, 3rd edition, San Francisco, CA, Morgan Kaufmann Publishers, Inc., USA, 2011.
  17. Mohamed Adel Sheta, Kamel Abd El Salam El Hadad, and H. Aboelseoud M. “Data Mining-basedAnti-spyware System Using a Hybrid of Common Feature-based Extraction And Frequency-based Feature Extraction Approaches”, International Journal of Applied Engineering Research (IJAER), Vol. 10, No. 24, pp. 45597-45605, India, 2015.
  18. Saoussen Rekhis, Hela Marouane, Rafik Bouaziz, Claude Duvallet, and Bruno Sadeg “Metrics for Measuring Quality of Real-time Design Patterns”, In the 8th International Conference on Software Engineering Advances (ICSEA), pp. 163-168, France, 2013.
Index Terms

Computer Science
Information Sciences

Keywords

Spyware Data mining Design patterns.