NDLI: A Web Intrusion Detection Mechanism based on Feature based Data Clustering

Content Provider	IEEE Xplore Digital Library
Author	Das, D. Sharma, U. Bhattacharyya, D.K.
Copyright Year	2009
Description	Author affiliation: Department of Computer Science & Engineering, Tezpur University, Tezpur, INDIA, utpal@tezu.ernet.in (Sharma, U.) \|\| Department of Computer Science & Engineering, Tezpur University, Tezpur, INDIA, dkb@tezu.ernet.in (Bhattacharyya, D.K.) \|\| Department of Computer Science & Engineering, Tezpur University, Tezpur, INDIA, ddas@tezu.ernet.in (Das, D.)
Abstract	Web is one of the most popular internet services in today's world. In today's world, web servers and web based applications are the popular corporate applications and become the targets of the attackers. A Large number of Web applications, especially those deployed for companies to e-business operation involve high reliability, efficiency and confidentiality. Such applications are written in script languages like PHP embedded in HTML allowing establish the connection to databases, retrieving data and putting them in WWW site. In order to detect known attacks, misuse detection of web based attacks consists of attack rules and descriptions. As misuse detection considers predefined signatures for intrusion detection, here we have proposed two phases of intrusion detection mechanism. In the first phase we have used web host based intrusion detection with matching mechanism using `Hamming Edit Distance'. We have considered here. the web layer log file for matching. This phase has been tested with our university intranet web server's log file. We have tested successfully the SQL injection for unauthorized access. We proposed a `Query based projected clustering' for unsupervised anomaly detection and also a `packet arrival factor' for intrusion detection in the second phase. We tested the scheme in this phase using KDD CUP99. In this phase while testing our scheme, we have extracted the feature dataset with protocol `tcp' and services `http'. Both the phases of our scheme found working successfully and an evaluated threshold has been proposed for better result.
Starting Page	1124
Ending Page	1129
File Size	3414431
Page Count	6
File Format	PDF
ISBN	9781424429271
DOI	10.1109/IADCC.2009.4809172
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-03-06
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Information retrieval World Wide Web HTML Phase detection web layer log matching query based projected clustering Databases Web and internet services Intrusion detection Web intrusion Feature extraction attack labeling sql injection Web server Testing
Content Type	Text
Resource Type	Article

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