Investigation of 3-D Secure's Model for Fraud Detection
This work provides insights into the operational mechanics of a widely used online payment security protocol, which is incremental as it empirically tests existing factors without proposing new methods.
The study quantified how factors like machine_data, value, and region affect fraud detection decisions in the 3-D Secure 2.0 protocol, finding that changes in these factors increased the likelihood of being challenged by 5-7 times, but overall challenge rates only reached 60%, while decline rates varied from <5% to near-certain depending on region and other changes.
Background. 3-D Secure 2.0 (3DS 2.0) is an identity federation protocol authenticating the payment initiator for credit card transactions on the Web. Aim. We aim to quantify the impact of factors used by 3DS 2.0 in its fraud-detection decision making process. Method. We ran credit card transactions with two Web sites systematically manipulating the nominal IVs \textsf{machine\_data}, \textsf{value}, \textsf{region}, and \textsf{website}. We measured whether the user was \textsf{challenged} with an authentication, whether the transaction was \textsf{declined}, and whether the card was \textsf{blocked} as nominal DVs. Results. While \textsf{website} and \textsf{card} largely did not show a significant impact on any outcome, \textsf{machine\_data}, \textsf{value} and \textsf{region} did. A change in \textsf{machine\_data}, \textsf{region} or \textsf{value} made it 5-7 times as likely to be challenged with password authentication. However, even in a foreign region with another factor being changed, the overall likelihood of being challenged only reached $60\%$. When in the card's home region, a transaction will be rarely declined ($< 5\%$ in control, $40\%$ with one factor changed). However, in a region foreign to the card the system will more likely decline transactions anyway (about $60\%$) and any change in \textsf{machine\_data} or \textsf{value} will lead to a near-certain declined transaction. The \textsf{region} was the only significant predictor for a card being blocked ($\mathsf{OR}=3$). Conclusions. We found that the decisions to challenge the user with a password authentication, to decline a transaction and to block a card are governed by different weightings. 3DS 2.0 is most likely to decline transactions, especially in a foreign region. It is less likely to challenge users with password authentication, even if \textsf{machine\_data} or \textsf{value} are changed.