Performance and Maintainability Evaluation of Anti-Spyware System {tag} {/tag} International Journal of Computer Applications Foundation of Computer Science (FCS), NY, USA Volume 150 Number 4 Year of Publication: 2016 Authors: Aboelseoud M. Mohamed Adel Sheta, Mohamed Zaki, Kamel Abd El Salam El Hadad, H. 10.5120/ijca2016911493 Abstract {bibtex}2016911493.bib{/bibtex} 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 1/3 Performance and Maintainability Evaluation of Anti-Spyware System 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. 2/3 Performance and Maintainability Evaluation of Anti-Spyware System 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. Computer Science Index Terms Information Sciences Keywords Spyware, Data mining, Design patterns. 3/3