A Simple Shill Bidding Agent

Trevathan, Jarrod; Read, Wayne

doi:10.1109/itng.2007.20

Cited by 17 publications

(16 citation statements)

References 8 publications

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“…The agent ceases bidding when the desired profit from shilling has been attained, or in the case that it is too risky to continue bidding (e.g., during slow bidding, or near the auction's end). (See [7] for implementation specific details regarding the simple shill agent.) In general, the risky the shill agent, the more profit it an attain, but the higher the likelihood that it will win the auction.…”

Section: Performancementioning

confidence: 99%

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Investigating Shill Bidding Behaviour Involving Colluding Bidders

Trevathan

Read²

2007

JCP

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Abstract-Shill bidding is where spurious bids are introduced into an auction to drive up the final price for the seller, thereby defrauding legitimate bidders. Trevathan and Read presented an algorithm to detect the presence of shill bidding in online auctions. The algorithm observes bidding patterns over a series of auctions, and gives each bidder a shill score to indicate the likelihood that they are engaging in shill behaviour. While the algorithm is able to accurately identify those with suspicious behaviour, it is designed for the instance where there is only one shill bidder. However, there are situations where there may be two or more shill bidders working in collusion with each other. Colluding shill bidders are able to engage in more sophisticated strategies that are harder to detect. This paper proposes a method for detecting colluding shill bidders, which is referred to as the collusion score. The collusion score, either detects a colluding group, or forces the colluders to act individually like a single shill, in which case they are detected by the shill score algorithm. The collusion score has been tested on simulated auction data and is able to successfully identify colluding shill bidders.

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Section: Performancementioning

confidence: 99%

“…The number of shills used varied with the type of test being conducted. The shill agent's target price was set to $6.50 and programmed to bid in a moderately risk-adverse manner (see [7]). All tests were repeated, and standard results are given.…”

Section: Performancementioning

confidence: 99%

Investigating Shill Bidding Behaviour Involving Colluding Bidders

Trevathan

Read²

2007

JCP

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“…Furthermore, we generate a simulated auction dataset using a shill bidding agent [21]. The dataset contains 10 sellers, 51 bidders (including a shill bidder (e.g., 'Shill a')), and 30 auctions.…”

Section: Comparison Between Baseline Shill Scores and Recalculated Shmentioning

confidence: 99%

Detecting Collusive Shill Bidding

Trevathan

Read

2007

Fourth International Conference on Information Technology (ITNG'07)

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“…In an agent-based online auction system, a bidding agent can automatically place bids on behalf of a human user according to a user-specified bidding strategy [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Visual Specification of Layered Bidding Strategies for Autonomous Bidding Agents

Ford

Bates

et al. 2010

JCP

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Abstract-In an agent-based online auction system, a bidding agent can automatically place bids on behalf of a human user according to a user-specified bidding strategy. Current implementations of bidding agents only support a set of simple predefined bidding strategies. In this paper, we introduce a formal bidding strategy model that supports specification of complex bidding strategies for autonomous bidding agents. The formal model is defined as a layered bidding strategy model (LBSM), which can be represented using notations adapted from UML activity diagrams. For real-time and efficient reasoning, the formal model is converted into a rule-based bidding strategy model (RBSM) represented in bidding strategy language (BSL), which can be directly executed by a reasoning module of an autonomous bidding agent. We present an algorithm for converting an LBSM to a rule-based bidding strategy model, and an algorithm to drive the reasoning engine. Finally, we develop a prototype agent-based online auction system using JADE, and demonstrate how layered bidding strategies can be precisely specified, and how our approach may support analysis of impacts on bidding histories by using different bidding strategies in agent-based online auctions.

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A Simple Shill Bidding Agent

Cited by 17 publications

References 8 publications

Investigating Shill Bidding Behaviour Involving Colluding Bidders

Investigating Shill Bidding Behaviour Involving Colluding Bidders

Detecting Collusive Shill Bidding

Visual Specification of Layered Bidding Strategies for Autonomous Bidding Agents

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