DATA MINING TECHNIQUES FOR SECURITY OF WEB SERVICES

Manu Malek, Fotios Harmantzis

2004

Abstract

The Internet, while being increasingly used to provide services efficiently, poses a unique set of security issues due to its openness and ubiquity. We highlight the importance of security in web services and describe how data mining techniques can offer help. The anatomy of a specific security attack is described. We then survey some security intrusions detection techniques based on data mining and point out their shortcomings. Then we provide some novel data mining techniques to detect such attacks, and describe some safeguard against these attacks.

References

  1. . http://www.w3.org/TR/wsdl [2]. Michael J. A. Berry and Gordon Linoff, Data Mining Techniques, Wiley Computer Publishing, 1997 [3]. Computer Emergency Response Team/Coordination Center (CERT/CC) at Carnegie Mellon University's Software Engineering Institute, http://www.cert.org/ [4].www.insecure.org/nmap/nmap-fingerprintingarticle.html [5]. NIST ITL Bulletin, “Computer attacks: what they are and how to defend against them,” May 1999.
  2. . CSI, “2002 CSI/FBI Computer Crime and Security Survey,” http://www.gocsi.com/.
  3. . The SANS Institute (http://www.sans.org/top20/), May 2003 [8]. Douglas Comer, Internetworking with TCP/IP Vol.1: Principles, Protocols, and Architecture (4th Edition), Prentice Hall, 2000 [9]. www.insecure.org/sploits/ping-o-death.html [10]. www.w3c.org? [11]. S. McClure, S. Shah, and S. Shah, Web Hacking: Attacks and Defenses, Addison Wesley, 2003 [12].
  4. . http://packages.debian.org/unstable/net/ippl.html [14]. W. Lee and S. J. Stolfo, “Data Mining Approaches for Intrusion Detection,” Usenix Security Symposium, San Antonio, Texas, July 1998 [15]. Magnus Almgren, Herve Deba, and Marc Dacier, "A Lightweight Tool for Detecting Web Server Attacks," http://www.ce.chalmers.se/almgren/Publications/almgren -ndss00.pdf [16]. S. Forrest, S. A. Hofmeyr, A. Somayaji, and T. A.
  5. . S. A. Hofmeyr, A. Somayaji, and S. Forrest, "Intrusion Detection using Sequences of System Calls," Journal of Computer Security Vol. 6, pp. 151-180, 1998.
  6. . Jeremy Frank, “Artificial Intelligence and Intrusion Detection: Current and Future Directions,” June 1994 (http://citeseer.nj.nec.com/frank94artificial.html) [19]. Zhen Liu, German Florez, and Susan Bridges, “A Comparison of Input Representation in Neural Networks: A Case Study in Intrusion Detection,” Proc. International Joint Conference on Neural Networks, May 12-17, 2002, Honolulu, Hawaii.
  7. . http://www.data-miner.com [21]. S. Weiss and N. Indurkhya, Predictive Data Mining: A Practical Guide, Morgan Kaufmann, 1997.
Download


Paper Citation


in Harvard Style

Malek M. and Harmantzis F. (2004). DATA MINING TECHNIQUES FOR SECURITY OF WEB SERVICES . In Proceedings of the First International Conference on E-Business and Telecommunication Networks - Volume 2: ICETE, ISBN 972-8865-15-5, pages 61-67. DOI: 10.5220/0001382300610067


in Bibtex Style

@conference{icete04,
author={Manu Malek and Fotios Harmantzis},
title={DATA MINING TECHNIQUES FOR SECURITY OF WEB SERVICES},
booktitle={Proceedings of the First International Conference on E-Business and Telecommunication Networks - Volume 2: ICETE,},
year={2004},
pages={61-67},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001382300610067},
isbn={972-8865-15-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on E-Business and Telecommunication Networks - Volume 2: ICETE,
TI - DATA MINING TECHNIQUES FOR SECURITY OF WEB SERVICES
SN - 972-8865-15-5
AU - Malek M.
AU - Harmantzis F.
PY - 2004
SP - 61
EP - 67
DO - 10.5220/0001382300610067