Skip to main content
SpringerLink
Log in
Book cover

Science and Information Conference

SAI 2014: Intelligent Systems in Science and Information 2014 pp 57–76Cite as

Detection of Privilege Abuse in RBAC Administered Database

  • Conference paper
  • First Online:

Part of the book series: Studies in Computational Intelligence ((SCI,volume 591))

Abstract

In this paper, we propose an approach for detection of database privilege abuse in Role Based Access Control (RBAC) administered database. The proposed approach extracts the data dependencies among the attributes of relations of the database. Role based data dependency rule miner (RBDDRM) algorithm is used to mine role-wise data dependencies from database log. These data dependencies are considered as role profiles, which are used to detect the misuse of privileges by database users.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD   169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. 22 million user IDs may have been stolen from Yahoo Japane. http://www.infosecurity-magazine.com/view/32498/22-million-user-ids-may-havebeen-stolen-fromyahoojapan?utm_medium=twitterutm_source=twitterfeed (2013) [Online; Accessed July 2013]

  2. 2010 Data Breach Investigations Report. http://www.verizonenterprise.com/resources/reports/rp_2010-data-breach-report_en_xg.pdf (2013) [Online; Accessed July 2013]

  3. Hu, Y., Panda, B.: A data mining approach for database intrusion detection. In: Proceedings of the 2004 ACM Symposium on Applied Computing, pp. 711–716. ACM (2004)

    Google Scholar 

  4. Bertino, E., Sandhu, R.: Database security-concepts, approaches, and challenges. Dependable Secure Comput. IEEE Trans. 2(1), 2–19 (2005)

    Article  Google Scholar 

  5. Javidi, M.M., Rafsanjani, M.K., Hashemi, S., Sohrabi, M.: An overview of anomaly based database intrusion detection systems. Ind. J. Sci. Technol. 5(10), 3550–3559 (2012)

    Google Scholar 

  6. Chung, C.Y., Gertz, M., Levitt, K.: Demids: a misuse detection system for database systems. In: Integrity and Internal Control in Information Systems, pp. 159–178. Springer, Berlin (2000)

    Google Scholar 

  7. Lee, V.C., Stankovic, J.A., Son, S.H.: Intrusion detection in real-time database systems via time signatures. In: Real-Time Technology and Applications Symposium, 2000. RTAS 2000. Proceedings of Sixth IEEE, pp. 124–133. IEEE (2000)

    Google Scholar 

  8. Lee, S.Y., Low, W.L., Wong, P.Y.: Learning fingerprints for a database intrusion detection system. In: Computer Security ESORICS 2002, pp. 264–279. Springer, Berlin (2002)

    Google Scholar 

  9. Vieira, M., Madeira, H.: Detection of malicious transactions in dbms. In: Dependable Computing, 2005. Proceedings of 11th Pacific Rim on International Symposium on IEEE, p. 8. IEEE (2005)

    Google Scholar 

  10. Bertino, E., Terzi, E., Kamra, A., Vakali, A.: Intrusion detection in RBAC-administered databases. In: Computer Security Applications Conference, 21st Annual, p. 10. IEEE (2005)

    Google Scholar 

  11. Kamra, A., Terzi, E., Bertino, E.: Detecting anomalous access patterns in relational databases. VLDB J. 17(5), 1063–1077 (2008)

    Article  Google Scholar 

  12. Srivastava, A., Sural, S., Majumdar, A.K.: Weighted intra-transactional rule mining for database intrusion detection. In: Advances in Knowledge Discovery and Data Mining, pp. 611–620. Springer, Berlin (2006)

    Google Scholar 

  13. Mathew, S., Petropoulos, M., Ngo, H.Q., Upadhyaya, S.: A data-centric approach to insider attack detection in database systems. In: Recent Advances in Intrusion Detection, pp. 382–401. Springer, Berlin (2010)

    Google Scholar 

  14. Rao, U.P., Sahani, G.J., Patel, D.R.: Detection of malicious activity in role based access control (RBAC) enabled databases. J. Inf. Assur. Sec. 5(6), 611–617 (2010)

    Google Scholar 

  15. Rao, U.P., Patel, D.R.: Incorporation of application specific information for recovery in database from malicious transactions. Inf. Secur. J. Glob. Perspect. 22(1), 35–45 (2013)

    Article  Google Scholar 

  16. Kamra, A., Bertino, E.: Design and implementation of an intrusion response system for relational databases. Knowl. Data Eng. IEEE Trans. 23(6), 875–888 (2011)

    Article  Google Scholar 

  17. Codd, E.F.: A relational model of data for large shared data banks. Commun. ACM 13(6), 377–387 (1970)

    Article  MATH  Google Scholar 

  18. Ferraiolo, D.F., Barkley, J.F., Kuhn, D.R.: A role-based access control model and reference implementation within a corporate intranet. ACM Trans. Inf. Syst. Secur. 2(1), 34–64 (1999)

    Article  Google Scholar 

  19. Agrawal, R., Srikant, R.: Mining sequential patterns. In: Data Engineering, 1995. Proceedings of the Eleventh International Conference on IEEE, pp. 3–14 (1995)

    Google Scholar 

  20. TPC Council-TPC Benchmark C Standard Specification Version 5.1

    Google Scholar 

Download references

Acknowledgment

This research work is supported by Institute Research Grant (Ref. No.: Dean (R&C)/1503/2013-14, dated: 17-02-2014) of S.V. National Institute of Technology Surat (Gujarat) 395007-India.

Author information

Authors and Affiliations

  1. Department of Computer Engineering, S. V. National Institute of Technology, Surat, 395007, Gujarat, India

    Udai Pratap Rao & Nikhil Kumar Singh

Authors
  1. Udai Pratap Rao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nikhil Kumar Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Udai Pratap Rao .

Editor information

Editors and Affiliations

  1. Graduate School of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

  2. The Science and Information (SAI) Organization, London, United Kingdom

    Supriya Kapoor

  3. The Science and Information (SAI) Organization, London, United Kingdom

    Rahul Bhatia

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Rao, U.P., Singh, N.K. (2015). Detection of Privilege Abuse in RBAC Administered Database. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Systems in Science and Information 2014. SAI 2014. Studies in Computational Intelligence, vol 591. Springer, Cham. https://doi.org/10.1007/978-3-319-14654-6_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-14654-6_4

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14653-9

  • Online ISBN: 978-3-319-14654-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation