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Forensic Analysis for Monitoring Database Transactions

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 467))

Abstract

Database forensics aids in the qualification and investigation of databases and facilitates a forensic investigator to prove a suspected crime which can be used to prevent illegitimate banking transactions. The banks deals in public money but unfortunately are becoming vulnerable by receiving illegal money in the form of legitimate business. The absence of any preventive measures in the banks to monitor such scam would be perilous some day. If they violate relevant laws and regulatory guidelines they can unknowingly keep raising Money Laundering practices in their system. In this article we propose a forensic methodology for private banks to have ongoing monitoring system as per Reserve Bank of India (RBI) guidelines for financial transactions which will check their database audit logs on continuous basis for marking suspected transactions if any. These transactions are then precisely analyzed and verified with Dempster Shafer Theory of Evidence to generate suspected reports automatically as required by Financial Intelligence Unit.

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References

  1. Bertino, E., Sandhu, R.: Database Security − Concepts, Approaches, and challenges. IEEE Transactions on Dependable and Secure Computing 2(1), 2–19 (2005)

    Article  Google Scholar 

  2. Richardson, R.: CSI/FBI Computer Crime and Security Survey (2011), http://www.gocsi.com

  3. Raghavan, S.: Digital forensic research: current state of the art. In: CSI Publications. Springer (2012)

    Google Scholar 

  4. Jun, T.: On Developing Intelligent Surveillant System of Suspicious Financial Transaction. IEEE (2010)

    Google Scholar 

  5. Pavlou, K.E., Snodgrass, R.T.: Forensic analysis of database tampering, ACM Transactions on Database Systems (TODS) 33(4), Article 30, 47+25 pages (2008)

    Google Scholar 

  6. Godbole, N., Belapure, S.: Cyber Security, Understanding Computer Forensics and Legal Perspectives. Wiley-India (2011) ISBN: 978-81-265-2179-1

    Google Scholar 

  7. Pavlou, K.E.: Database Forensics in the Service of Information Accountability/ SIGMOD/PODS PhD Poster Session, Poster Presented (2011)

    Google Scholar 

  8. Pavlou, K.E., Snodgrass, R.T.: Dragoon: An Information Accountability System for High-Performance Databases. In: Demonstration. International Conference on Data Engineering, ICDE (2012)

    Google Scholar 

  9. Olivier, M.S.: On metadata context in Database Forensics. Digital Investigation 5(3-4), 115–123 (2009), www.sciencedirect.com

    Article  Google Scholar 

  10. RBI Rules, http://rbidocs.rbi.org.in/rdocs/content/Pdfs/68787.pdf

  11. RBI Rules, http://rbidocs.rbi.org.in/rdocs/notification/PDFs/PM2212A_II.pdf

  12. Sarbanes-Oxley (SOX) Compliance Checklist SOX-Compliance (2011), https://correlog.com/support-public/SOX-Compliance.pdf

  13. Anti Money Laundering Rules, http://www.dor.gov.in/sites/upload_files/revenue/files/PML%20%28Amendment%29%20Act,%202012.pdf

  14. Bhaskaran, R.: CEO, Indian Institute of Banking and Finance. Anti Money Laundering & Know Your Customer (KYC). Macmillan Publisher India (2012) ISBN 13: 978-0230-33196-9

    Google Scholar 

  15. Shafer, G.: Dempster–Shafer theory (2002)

    Google Scholar 

  16. Sentz, K., Ferson, S.: Combination of Evidence in Dempster–Shafer Theory. Sandia National Laboratories (2002)

    Google Scholar 

  17. Dempster, A.P.: Upper and lower probabilities induced by a multivalued mapping. The Annals of Mathematical Statistics 38(2), 325–339 (1967), doi:10.1214/aoms/1177698950

    Google Scholar 

  18. Khanuja, H.K., Adane, D.S.: Database Security Threats and challenges in Database Forensic: A survey. In: Proceedings of 2011 International Conference on Advancements in Information Technology, AIT 2011 (2011), http://www.ipcsit.com/vol20/33-ICAIT2011-A4072.pdf

  19. Khanuja, H.K., Adane, D.S.: A Framework For Database Forensic Analysis. Published in Computer Science & Engineering: An International Journal (CSEIJ) 2(3) (2012)

    Google Scholar 

  20. Khanuja, H.K., Adane, D.S.: Forensic Analysis of Databases by Combining Multiple Evidences. International Journal of Computers & Technology. Council for Innovative Research 7(3) (2013)

    Google Scholar 

  21. Panigrahi, S., Sural, S., Majumdar, A.K.: Detection of Intrusive Activity in Databases by Combining Multiple Evidences and Belief Update. In: IEEE Symposium on Computational Intelligence in Cyber Security (2009)

    Google Scholar 

  22. Wang, X., Dong, G.: Research on Money Laundering Detection Based on Improved Minimum Spanning Tree Clustering and Its Application. In: Proceedings of the 2009 Second International Symposium on Knowledge Acquisition and Modeling, vol. 02, pp. 62–64. IEEE Computer Society (2009)

    Google Scholar 

  23. Lv, L.-T., Ji, N., Zhang, J.-L.: A RBF neural network model for anti-money laundering. In: International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR 2008. IEEE (2008)

    Google Scholar 

  24. Wang, S.-N., Yang, J.-G.: A Money Laundering Risk Evaluation Method Based on Decision Tree. In: International Conference on Machine Learning and Cybernetics. IEEE (2007)

    Google Scholar 

  25. Tang, J., Yin, J.: Developing an intelligent data discriminating system of anti-money laundering based on SVM. In: International Conference on Machine Learning and Cybernetics, Guangzhou, China, vol. 6, pp. 3453–3457. IEEE (2005)

    Google Scholar 

  26. Srivastava, R.P.: The Dempster-Shafer Theory of Belief Functions for Managing Uncertainties: An Introduction and Fraud Risk Assessment Illustration. Australian Accounting Review 21(3), 282–291

    Google Scholar 

  27. Harrison, K., Srivastava, R.P., Plumlee, R.D.: ‘Auditors’ Evaluations of Uncertain Audit Evidence: Belief Functions versus Probabilities. In: Srivastava, R.P., Mock, T. (eds.) Belief Functions in Business Decisions. STUDFUZZ, vol. 88, pp. 161–183. Physica-Verlag, Springer-Verlag Company, Heidelberg (2002)

    Chapter  Google Scholar 

  28. Financial Intelligence Unit- India (FIU-IND), http://fiuindia.gov.in/

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Khanuja, H.K., Adane, D.S. (2014). Forensic Analysis for Monitoring Database Transactions. In: Mauri, J.L., Thampi, S.M., Rawat, D.B., Jin, D. (eds) Security in Computing and Communications. SSCC 2014. Communications in Computer and Information Science, vol 467. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44966-0_19

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  • DOI: https://doi.org/10.1007/978-3-662-44966-0_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-44965-3

  • Online ISBN: 978-3-662-44966-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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