Online Auction Fraud Detection in Privacy-Aware Reputation Systems
AbstractWith a privacy-aware reputation system, an auction website allows the buyer in a transaction to hide his/her identity from the public for privacy protection. However, fraudsters can also take advantage of this buyer-anonymized function to hide the connections between themselves and their accomplices. Traditional fraudster detection methods become useless for detecting such fraudsters because these methods rely on accessing these connections to work effectively. To resolve this problem, we introduce two attributes to quantify the buyer-anonymized activities associated with each user and use them to reinforce the traditional methods. Experimental results on a dataset crawled from an auction website show that the proposed attributes effectively enhance the prediction accuracy for detecting fraudsters, particularly when the proportion of the buyer-anonymized activities in the dataset is large. Because many auction websites have adopted privacy-aware reputation systems, the two proposed attributes should be incorporated into their fraudster detection schemes to combat these fraudulent activities. View Full-Text
- Supplementary File 1:
Supplementary (XLSX, 1268 KB)
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Lin, J.-L.; Khomnotai, L. Online Auction Fraud Detection in Privacy-Aware Reputation Systems. Entropy 2017, 19, 338.
Lin J-L, Khomnotai L. Online Auction Fraud Detection in Privacy-Aware Reputation Systems. Entropy. 2017; 19(7):338.Chicago/Turabian Style
Lin, Jun-Lin; Khomnotai, Laksamee. 2017. "Online Auction Fraud Detection in Privacy-Aware Reputation Systems." Entropy 19, no. 7: 338.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.