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Detection and Implementation of Web-based Attacks using Attribute Length Method
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 120 - Number 3 |
| Year of Publication: 2015 |
| Authors: Snigdha Agrawal, Priya Gupta, Vanita Jain, Achin Jain |
10.5120/21209-3901
|
Snigdha Agrawal, Priya Gupta, Vanita Jain, Achin Jain . Detection and Implementation of Web-based Attacks using Attribute Length Method. International Journal of Computer Applications. 120, 3 ( June 2015), 25-29. DOI=10.5120/21209-3901
Abstract
With the increasing demand of web-based applications, they have become more prone to be exploited by the attackers. The purpose of this paper is to study the effects of web-based attacks and analyze the log files generated during the attacks. We have implemented Attribute Length Method proposed by Krugel for the detection of web-based attacks. In the implementation of the Attribute Length method, two different phases are used in our system i. e. , learning and detection phase. In the learning phase, our implementation in Java trains the normal dataset and calculates the threshold probability value which is used in the Detection phase for the estimation of web-based attacks. In order to estimate the performance of attribute length method, we have used a log file having three different web attacks, i. e. Cross Site Scripting attack, Path Traversal attack, and Buffer Overflow attack. This method is more effective as we have considered the parameters as fixed-size tokens.
References
- Justin Crist (2007), Web Based Attacks, SANS Institute, As part of the Information Security Reading Room, http://www. sans. org/reading_room/whitepapers/application/web-based- attacks_2053
- OWASP Accessed from - www. owasp. org/index. php/Guide
- R. Sekar, A. Gupta, J. Frullo, T. Shanbhag, S. Zhou, A. Tiwari and H. Yang, (2002) Specification Based Anomaly Detection: A New Approach for Detecting Network Intrusions, ACM CCS.
- C. Kruegel, and G. Vigna. (2003) Anomaly Detection of Web-based Attacks. In 10th ACM Conference on Computer and Communication Security (CCS-03) Washington, DC, USA, October 27-31, pp 251 – 261.
- Bolzoni D, Etalle S, Hartel P. (2006) Poseidon: a 2-tier anomaly-based network intrusion detection system. In: Information Assurance. IWIA 2006. Fourth IEEE International Workshop. Pp 10.
- M. -L. Shyu, S. -C. Chen, K. Sarinnapakorn, L. Chang, (2003) A novel anomaly detection scheme based on principal component classifier, In Proceedings of the 3rd IEEE International Conference on Data Mining, pp. 172–179.
- C. Kruegel, G. Vigna, W. Robertson,(2005) A multi-model approach to the detection of web-based attacks, Computer Networks 48 (5) , pp 717–738
- C. Noble and D. Cook. (2003) Graph-based anomaly detection. In Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp 631–636.
- Maxion RA, Tan KMC (2000) Benchmarking anomaly-based detection systems. In: International Conference on Dependable Systems and Networks. IEEE Computer Society Press, Los Alamitos, pp 623–630.
- Este´vez-Tapiador J. M. , Garc?´a-Teodoro P. , D?´az-Verdejo J. E. (2005) Detection of web-based attacks through Markovian protocol parsing. In: Proc. ISCC05; pp. 457–62
- J. Gomez, D. Dasgupta,(2001) Evolving fuzzy classifiers for intrusion detection, in: Proceedings of IEEE Workshop on Information Assurance, United State Military Academy, West Point, NY, 2001, pp. 68–75.
- J. M. Estévez-Tapiador, P. García-Teodoro, J. E. DíazVerdejo (2004), "Measuring Normality in HTTP Traffic for Anomaly-Based Intrusion Detection", in. Computer Networks, 45(2), pp 145-193.
- Tejinder Singh Mehta , Sanjay Jamwal, (2015) Model To Prevent Websites From XSS Vulnerabilities, (IJCSIT) International Journal of Computer Science and Information Technologies, 6 (2) , pp 1059-1067
- W. Robertson, G. Vigna, C. Kruegel, R. A. Kemmerer (2006), Using generalization and characterization techniques in the anomaly-based detection of web attacks, in: Proceedings of Network and Distributed System Security Symposium Conference, 2006, Internet Society
- Patcha, A. and Park, J. -M. (2007). An overview of anomaly detection techniques: Existingsolutions and latest technological trends. Comput. Networks , 51(12) pp 3448-3470.
- V. Chandola, A. Banerjee, V. Kumar (2009), Anomaly detection: a survey, ACM Computing Surveys 41 (3) 1–58. ISSN: 0360-0300, doi : http://doi. acm. org/10. 1145/1541880. 1541882
- Desmond, Paul (2004). All-out blitz against Web app Attacks Retrieved December 30, 2006, from networkworld. com Web site: http://www. networkworld. com/techinsider/2004/0517techinsidermain. html
- Gartner (2005). Improve IT Security with Vulnerability Management Retrieved February 27, 2007, from Gartner. com Web site: http://www. gartner. com/DisplayDocument?doc_cd=127481
- Singh, N. , Jain, A. , Raw, R. S. , Raman, R. (2014) Detection of Web-Based Attacks by Analyzing Web Server Log Files. In: Mohapatra, D. P. , Patnaik, S. eds. Intelligent Computing, Networking, and Informatics. Springer, Heidelberg, pp. 101-109
- Joshila Grace, L. K. , Maheswari, V. , Nagamalai, D. (2011): Analysis of Weblogs and Web user in Web mining. Int. J. Netw. Secur. Appl. (IJNSA) 3(1)
- Kolaczek, Grzegorz, and Tomasz Kuzemko. (2014) Security Incident Detection Using Multidimensional Analysis of the Web Server Log Files Computational Collective Intelligence. Technologies and Applications. Springer International Publishing. 663-672.
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