Detection of Malicious Requests on Web Logs Using Data Mining Techniques

被引:0
作者
Sahin, Mehmet Emin [1 ]
Ozdemir, Suat [2 ]
机构
[1] Gazi Univ, Bilisim Enstitusu, Ankara, Turkey
[2] Gazi Univ, Muhendislik Fak, Ankara, Turkey
来源
2019 4TH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND ENGINEERING (UBMK) | 2019年
关键词
malicious web requests; web application security; web access logs; data mining; machine learning;
D O I
10.1109/ubmk.2019.8907087
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The rapid development and deployment of Internet-based applications has created many problems related to web security. Although the number and the variety of the methods that have been developed in order to maintain security of web applications are increasing, every passing day new types of attacking methods that are targeted at these systems emerge. In order to provide a supplement method to rule and signature based security systems for web application security, it becomes more important to detect and classify the malicious web requests using machine learning techniques. In this work, we used various machine learning techniques to discover the patterns on web requests, and classified the malicious requests while comparing different techniques.
引用
收藏
页码:463 / 468
页数:6
相关论文
共 6 条
[1]  
Arslan H, 2008, THESIS
[2]  
Aye T. T., 2011, 2011 3rd International Conference on Computer Research and Development (ICCRD 2011), P490, DOI 10.1109/ICCRD.2011.5764181
[3]  
Calzarossa M. C., 2013, P INT C INF INT WEB
[4]  
Cmar I, 2015, THESIS
[5]   Effective web log mining and online navigational pattern prediction [J].
Guerbas, Abdelghani ;
Addam, Omar ;
Zaarour, Omar ;
Nagi, Mohamad ;
Elhajj, Ahmad ;
Ridley, Mick ;
Alhajj, Reda .
KNOWLEDGE-BASED SYSTEMS, 2013, 49 :50-62
[6]  
Nagappan Meiyappan, 2010, Proceedings of the 2010 7th IEEE Working Conference on Mining Software Repositories (MSR 2010), P114, DOI 10.1109/MSR.2010.5463281