Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Fraud Detection for Information Reliability from the Internet in Forensic Accounting

Authors
Kim, YeogLee, Sang JinLim, Jong In
Issue Date
May-2010
Publisher
NATIONAL DONG HWA UNIV
Keywords
Forensic accounting; Fraud detection; Digital forensics
Citation
JOURNAL OF INTERNET TECHNOLOGY, v.11, no.3, pp.323 - 331
Indexed
SCIE
SCOPUS
Journal Title
JOURNAL OF INTERNET TECHNOLOGY
Volume
11
Number
3
Start Page
323
End Page
331
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/116521
ISSN
1607-9264
Abstract
Internet is a main factor in a flood of information. There is great concerning about reliability of information from the Internet. Financial statements are opened annually and anybody can obtain them from the Internet. A company manipulates its accounting data in order to look like financially stable. An institutional or individual investor considers the company has a good state in finance part or in business activity from its financial reports. That makes investors failed due to faulty information. Therefore, personal, companies or even countries can become a very dangerous state by usage of incorrect information. To modify accounting data as false is an antisocial action. In forensic accounting, an investigation is conducted to find evidence relevant to accounting scandals that involve making money for use in secret, embezzling company funds, or evading taxes on purpose [1]. But most existing techniques are used for evidence discovery rather than fraud prevention Fraud prevention in accounting part means to pre-detect frauds by analyzing financial statements. It helps information reliability from the Internet In this paper, an algorithm is suggested for the detection of financial fraud via financial statements analysis and the test results using this algorithm will be presented.
Files in This Item
There are no files associated with this item.
Appears in
Collections
School of Cyber Security > Department of Information Security > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher LEE, SANG JIN photo

LEE, SANG JIN
Department of Information Security
Read more

Altmetrics

Total Views & Downloads

BROWSE