Abstract
Web application attack detection is one of the popular research areas during these years. Security for web application is necessary and it will be effective to study and analyze how malicious patterns occur in web server log. This system analyzes web server log file, which includes normal and malicious users’ access patterns with their relevant links. This uses web server log file dataset for the detection of web application attacks. This system intends to analyze normal and attack behaviors from web server log and then classify attack types which are included in the dataset. In this system, three types of attacks are detected namely, SQL injection, XSS and directory traversal attacks. Attack analysis stage is done by request length module and regular expressions for various attack patterns.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Vamsidhar, T., Ashok, R., Venkat, R.: Intrusion Detection System For Web Applications With Attack Classification. Journal of Global Research in Computer Science (2012)
Kruegel, C., Vigna, G., Robertson, W.: A multi-model approach to the detection of web-based attacks. Reliable Software Group. University of California, Santa Barbara (2005)
Meyer, R., Cid, C.: Detecting Attacks on Web Applications from Log Files. SANS Institute (2008)
Kruegel, C., Vigna, G.: Anomaly detection of Web-based attacks. In: Proceedings of the 10th ACM Conference on Computer and Communication Security(CCS 2003), Washington, DC, October 2003, pp. 251–261. ACM Press, New York (2003)
Mookhey, K.K., Burghate, N.: Detection of SQLInjection and CrosssiteScriptingAttacks (2004). http://www.blackhat.com/presentations/bhusa04/bhus04mookhey/old/bhus04mookhey_whitepaper.pdf
Robertson, W., Vigna, G., Kruegel, C., Kemmerer, R.: Using generalization and characterization techniques in the anomaly based detection of web attacks. In: 13th Annual Network and Distributed System Security Symposium, San Diego (2006)
Gallagher, B., Eliassi-Rad, T.: Classification of http attacks: A studyon the ecml/pkdd 2007 discovery challenge (2009)
Faradzhullaev, R.: Analysis of Web Server Log Files and Attack Detection. Institute of Information Technologies, Academy of Sciences of Azerbaijan (2007)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Han, E.E. (2016). Detection of Web Application Attacks with Request Length Module and Regex Pattern Analysis. In: Zin, T., Lin, JW., Pan, JS., Tin, P., Yokota, M. (eds) Genetic and Evolutionary Computing. GEC 2015. Advances in Intelligent Systems and Computing, vol 388. Springer, Cham. https://doi.org/10.1007/978-3-319-23207-2_16
Download citation
DOI: https://doi.org/10.1007/978-3-319-23207-2_16
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-23206-5
Online ISBN: 978-3-319-23207-2
eBook Packages: EngineeringEngineering (R0)