1. Fraud Examination, 3E Chapter 17: Fraud in E-Commerce COPYRIGHT © 2009 South-Western, a part of Cengage Learning

2. Learning Objectives Understand e-commerce fraud risk. Take measures to prevent fraud in e- commerce. Detect e-business fraud. 2

3. E-commerce Fraud Risk Pressures to Commit E-commerce Fraud Dramatic growth, which has created tremendous cash flow needs. Merger or acquisition activity, which creates pressures to “improve the reported financial results.” Borrowing or issuing stock, additional pressures to “cook the books.” 3

4. E-commerce Fraud Risk Opportunities to Commit E-commerce Fraud New and innovative technologies for which security developments often lag transaction developments. Complex information systems that make installing controls difficult. The transfer of large amounts of information, a factor that poses theft and identity risks such as illegal monitoring and unauthorized access. 4

5. E-commerce Fraud Risk Rationalization to Commit E-commerce Fraud The perceived distance that decreases the personal contact between customer and supplier. Transactions between anonymous or unknown buyers and sellers—you can’t see who you are hurting. New economy thinking contends that traditional methods of accounting no longer apply. 5

6. E-commerce Fraud Risk Risks Inside an Organization Data theft Social engineering Sniffing Wartrapping Vandalism Employee laptops 6

7. E-commerce Fraud Risk Risks Outside an Organization Computer viruses Spyware Phishing Spoofing Falsified identity Database query (SQL) injections Bust-out E-mail and Web visits 7

8. Preventing Fraud in E-commerce Security Through Obscurity Keeping security holes, encryption algorithms, and processes secret in an effort to confuse attackers. Appealing, yet ineffective Rather than take chances with security through obscurity, employ robust, time- tested security methods 8

9. Detecting E-commerce Fraud Data-driven Fraud Detection 1.Endeavor to understand the business or operations of the organization 2.Identify what frauds can occur in the operation 3.Determine the symptoms that the most likely frauds would generate 4.Use databases and information systems to search for those symptoms 9

10. Detecting E-commerce Fraud Data-driven Fraud Detection 5.Analyze the results 6.Investigate the symptoms to determine if they are being caused by actual fraud or by other factors 10