Methodologies for detecting covert database

Keun G. Lee, Antonio Savoldi, Paolo Gubian, Kyung Soo Lim, Seokhee Lee, Sangjin Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Forensic Accounting has recently gained great attention in the accounting and computer forensic fields since government regulations such as Health Insurance Portability and Accountability Act (HIPAA), Gramm-Leach-Bliley Act (GLBA), Sarbanes-Oxley Act [1] (SOX) were introduced in the United States. Although these regulations force corporations to provide financial transparency, they still commit accounting frauds such as slush fund or tax evasion. Moreover, companies have substituted paper-work with IT systems such as DBMS (Database Management System), EDMS (Electronic Document Management System), and ERP (Enterprise Resource Planning) system. Since the majority of corporations use DBMS we should focus our attention on discovering financial information in a database server. However, frauds are difficult to observe and detect because the perpetrators did their best to conceal their fraudulent activities. In particular, we need to consider the case of a covert database server. This paper proposes a methodology for detecting covert database server, which would be helpful for forensic investigators. Therefore, we describe an example of covert database server and suggest several detection techniques. Finally, we provide our methodology according to classification of investigation cooperation.

Original languageEnglish
Title of host publicationProceedings - 2008 4th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2008
Pages538-541
Number of pages4
DOIs
Publication statusPublished - 2008 Oct 22
Event2008 4th International Conference on Intelligent Information Hiding and Multiedia Signal Processing, IIH-MSP 2008 - Harbin, China
Duration: 2008 Aug 152008 Aug 17

Other

Other2008 4th International Conference on Intelligent Information Hiding and Multiedia Signal Processing, IIH-MSP 2008
CountryChina
CityHarbin
Period08/8/1508/8/17

Fingerprint

Servers
Computer forensics
Health insurance
Industry
Enterprise resource planning
Taxation
Transparency

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Graphics and Computer-Aided Design
  • Signal Processing

Cite this

Lee, K. G., Savoldi, A., Gubian, P., Lim, K. S., Lee, S., & Lee, S. (2008). Methodologies for detecting covert database. In Proceedings - 2008 4th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2008 (pp. 538-541). [4604115] https://doi.org/10.1109/IIH-MSP.2008.258

Methodologies for detecting covert database. / Lee, Keun G.; Savoldi, Antonio; Gubian, Paolo; Lim, Kyung Soo; Lee, Seokhee; Lee, Sangjin.

Proceedings - 2008 4th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2008. 2008. p. 538-541 4604115.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Lee, KG, Savoldi, A, Gubian, P, Lim, KS, Lee, S & Lee, S 2008, Methodologies for detecting covert database. in Proceedings - 2008 4th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2008., 4604115, pp. 538-541, 2008 4th International Conference on Intelligent Information Hiding and Multiedia Signal Processing, IIH-MSP 2008, Harbin, China, 08/8/15. https://doi.org/10.1109/IIH-MSP.2008.258
Lee KG, Savoldi A, Gubian P, Lim KS, Lee S, Lee S. Methodologies for detecting covert database. In Proceedings - 2008 4th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2008. 2008. p. 538-541. 4604115 https://doi.org/10.1109/IIH-MSP.2008.258
Lee, Keun G. ; Savoldi, Antonio ; Gubian, Paolo ; Lim, Kyung Soo ; Lee, Seokhee ; Lee, Sangjin. / Methodologies for detecting covert database. Proceedings - 2008 4th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2008. 2008. pp. 538-541
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