2022-11-19 16:38:59

uAuction: Analysis, Design and Implementation of a Secure Online Auction System

Nazia Majadi Jarrod Trevathan Neil Bergmann

School of ICT School of ICT School of ITEE

Griffith University Griffith University University of Queensland

Queensland, Australia Queensland, Australia Queensland, Australia

Email: Email: Email:

Online auctions are now an immensely popular component of the electronic marketplace. However, there are many fraudulent buying/selling behaviours that can occur during an auction (e.g., shill bidding, bid shielding, etc.). While researchers are proposing methods for combating such fraud, it is extremely difficult to test how effective these countermeasures are. This is primarily due to it being unethical to engage in fraudulent behaviour just for the purpose of testing countermeasures. Furthermore, there is limited commercial auction data available due to the sensitivities of an online auctioneer being willing to admit that fraud has, or is occurring. In order to test fraud countermeasures in a controlled environment, we have created our own online auction server for conducting auction-related research. This paper presents our experiences with designing and implementing our own online auction system which we call uAuction. At present, there is limited useful literature on auction system design. We present an analysis and design of the auction system by employing Unified Modeling Language (UML) to show the architectural model, subsystems, use cases, activity workflows, class diagram, user interfaces, and system sequence diagrams. Our auction model is grounded in object-oriented techniques and is open source so that other researchers can expand upon our approach.

Keywords—Auction fraud; Domain model class diagram; Design class diagram; Shill bidding



Online auction sites, such as eBay and Yahoo! Auctions, are experiencing a dramatic increase in their popularity. The number of auction items hosted by eBay has increased from 110 million to approximately 266 million between July 2010 and September 2014 [8], [15]. A seller lists an item online for a set amount of time and buyers must place a bid higher than the last bid in order to purchase. Online auctions have removed the physical and logistical limitations of geographic proximity, time to organise, physical space, and small target audience.

However, the online environment creates many unique opportunities for people to cheat. Auction fraud can occur prior to an auction (e.g., misrepresentation of items, selling of black market goods, and triangulation), during an auction (e.g., shill bidding), or after the auction terminates (e.g., buyer does not pay for the item). Much research has been conducted around pre and post auction fraud [5], [11]. However, in-auction fraud is typically the hardest to develop effective countermeasures for as it deals with human behaviours and strategies that are somewhat unclear.

Shill bidding is the practice whereby a seller bids on his/her own auction in order to artificially increase the price that the winning bidder must pay. While it is understood that this is a problem, there are multiple strategies a shill bidder can engage in. As such there is much confusion over what actually constitutes shill bidding and how to effectively detect and prevent shill bidding. An even more significant problem is how to test the effectiveness of in-auction fraud counter measure proposals.

A major factor in the difficulty of testing in-auction fraud counter measures is the lack of available commercial online auction data. Online auctioneers do not share their auction data, commonly citing privacy reasons. However, it is more likely due to fear of damage to their public image should it be discovered that fraud is rampant in their auctions. Another significant issue with testing fraud counter measures is due to ethics/legality. For example, it is actually illegal for a researcher to engage in shill bidding in commercial online auctions primarily for the purpose of testing fraud counter measures. Due to these two major impediments, an alternative proposal for in-auction fraud testing must be examined.

We were driven to create our own online auction system due to there being limited useful literature available on auction software design. Moreover, the existing auction software literature are typcially not based on Unified Modeling Language (UML) [6], [7], [14], [16]. Whilethere are vendors who sell auction software [2], such software is expensive and cannot be customised for our research requirements. This paper presents an analysis and design of our auction system which we call uAuction. We employ UML to show the architectural model, subsystems, use cases, domain modeling, activity diagrams, database schema, website navigation, user interface, and system sequence diagrams. uAuction is being used to test the effectiveness of our own shill bidding detection and prevention proposal.


信息和通信技术学院 信息和通信技术学院 ITEE学院

澳大利亚昆士兰州 澳大利亚昆士兰州 澳大利亚昆士兰州


第一章 介绍





Wurmann等人[13]为在线英语拍卖提供软件设计,支持软件和人工代理。他们提出的名为Michigan Internet AuctionBot的拍卖服务器提供了考虑不同参数的灵活拍卖规范,以便代理研究人员可以探索拍卖机制的设计空间。但是,作者没有说明他们是如何开发他们的拍卖系统的。此外,自2000年代初以来,拍卖机构已经退役。








bull;卖家 - 卖家列出要出售的物品(或物品的集合)。卖家通常是以最高价格购买商品。

bull;拍卖人 - 拍卖人负责举办拍卖,提供拍卖所需的资源,并根据拍卖规则进行拍卖程序。拍卖师通常由卖家支付上市费用。在某些情况下,拍卖人可能会根据获胜价格收到佣金。在这种情况下,拍卖人通常希望物品以尽可能高的价格出售。










在主页上,投标人还可以看到uAuction上的所有拍卖清单或其个人拍卖清单中的一部分拍卖清单。 当投标人明确从某些拍卖页面采取行动时,或者当投标人放置他的第一个投标时,竞价人员会隐式地将拍卖添加到投标人的拍卖监视列表中。 从列表,所有拍卖或拍卖监视列表中,投标人可以选择拍卖并访问拍卖产品的描述,查看拍卖规则或投标产品。

本文讨论了我们在设计在线拍卖系统方面的经验。很多现有的拍卖软件文献都是过时的,对研究人员有用。此外,大多数现有的建议不符合健全的UML标准。我们为基于UML的在线拍卖系统提供了一个简单而优雅的设计。我们介绍了使用UML图解说明关键系统组件的拍卖系统的分析和设计。uAuction正在被用于促进我们对实时提价竞标检测的研究。 uAuction为我们提供了使用人类用户,模拟拍卖和/或合成数据进行各种类型测试的能力。


  1. Best Auction software. Available: auction-software/. [Accessed: 22-Jan-2016]
  2. 129–133, 2009.
    1. lt;a id='OLE_LINK24

      F. T. Sheldon, K. Jerath, Y. J. Kwon, and Y. W. Baik, Case study: Implementing a web b



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