Abstract
Unique-Bid auction sites are gaining popularity on the Internet in recent years. We have managed to extract dynamic temporal bidding data from such a site, using a back-propagation algorithm for analysis of side signals. This offered us rare insights on actual bidding strategies used by actual bidders, such as bidding-bursts, late-bidding and position-targeted bidding. We constructed an agent-based model simulating these behaviors, and validated it using the extracted bidding data. This model allowed us to experiment with different strategies of our own. We devised a set of automated winning strategies that performed well on our simulated environment. Finally, we demonstrated some of our strategies against a commercial auction site, achieving a 91% win rate and over 1000 UK pounds profit.
| Original language | English |
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| State | Published - 2013 |
| Event | 20th Annual Network and Distributed System Security Symposium, NDSS 2013 - San Diego, United States Duration: 24 Feb 2013 → 27 Feb 2013 |
Conference
| Conference | 20th Annual Network and Distributed System Security Symposium, NDSS 2013 |
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| Country/Territory | United States |
| City | San Diego |
| Period | 24/02/13 → 27/02/13 |