在线拍卖系统网站外文翻译资料

 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: nazia.majadi@griffithuni.edu.au Email: j.trevathan@griffith.edu.au Email: bergmann@itee.uq.edu.au

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

SECTION I

Introduction

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.

uAuction:安全在线拍卖系统的分析,设计和实施

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

在线拍卖现在是电子市场中非常受欢迎的组成部分。然而,在拍卖过程中会出现很多欺诈性的买/卖行为(例如,抬价,投标屏蔽等)。虽然研究人员提出了打击这种欺诈的方法,但要测试这些对策的有效性是非常困难的。这主要是因为仅仅为了测试对策而进行欺诈行为是不道德的。此外,由于在线拍卖人愿意承认欺诈已经发生或正在发生,所以可用的商业拍卖数据有限。为了在受控环境中测试欺诈对策,我们创建了自己的在线拍卖服务器,进行与拍卖相关的研究。本文介绍了我们设计和实施我们自己的在线拍卖系统的经验,我们称之为uAuction。目前,关于拍卖制度设计的有用文献数量有限。我们通过使用统一建模语言(UML)来展示架构模型,子系统,用例,活动工作流,类图,用户界面和系统顺序图,从而对拍卖系统进行分析和设计。我们的拍卖模式基于面向对象的技术,并且是开源的,所以其他研究人员可以扩展我们的方法。

第一章 介绍

然而,在线环境为人们作弊创造了许多独特的机会。拍卖欺诈可以在拍卖之前(例如,物品的虚假陈述,黑市货物的销售和三角测量),拍卖期间(例如,抬价拍卖)或拍卖终止之后发生(例如,买方不支付物品)。围绕拍卖前和拍卖后欺诈进行了大量研究[5,11]。然而,在处理人类行为和策略时,拍卖欺诈通常是最难开发的有效对策。

测试拍卖中的欺诈对策措施难度的一个主要因素是缺乏可用的商业在线拍卖数据。在线拍卖商不会共享他们的拍卖数据,通常引用隐私的原因。然而,如果发现欺诈行为在拍卖中猖獗,恐怕更可能是因为害怕损害公众形象。测试欺诈对策措施的另一个重要问题是道德/合法性。例如,研究人员在商业在线拍卖中进行提价竞标实际上是非法的,主要是为了测试欺诈对策措施。由于这两个主要障碍,必须检查另一种拍卖欺诈测试方案。

本文结构如下:第二部分讨论了在线拍卖系统设计的相关工作和本研究的动机。第三章描述了网上拍卖和拍卖形式的主要参与者。第四章描述了uAuction的设计。最后,第五章总结以及对未来的工作提供结论性意见。

本章介绍一些现有的在线拍卖系统和设计和实施uAuction的动机。

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。

Rumpe等人[1]描述了开发基于网络的实时在线拍卖系统的体系结构。本文还讨论了开发标准软件和自主开发组件的拍卖系统的功能和技术要求。虽然作者在很大程度上使用UML组件来实现他们的拍卖系统,但他们的UML图是不完整的,并且不严格遵循UML标准。

Trevathanetal[10]设计一个促进拍卖研究的在线拍卖服务器(称为研究拍卖服务器)。本文介绍了在线拍卖软件的设计,提供了一个基本的在线模型,并解决了主要拍卖流程,网络导航,初步安全性,数据库模式以及交易和时间问题。作者还展示了他们提出的模型如何与软件投标代理进行交互。他们的拍卖设计是基于面向对象的技术开发的,并且是一个开源工具。然而,作者并没有提供任何UML图来描述他们的拍卖系统。

B.问题动机

开发这个拍卖系统的原因如下:

bull;获得管理拍卖服务器和参与在线拍卖的经验;

bull;教育拍卖用户有关欺诈/拍卖行为。

A.在线拍卖参与者/利益相关者

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。

有不同类型的拍卖,如英语,维克瑞,荷兰,连续双拍卖等[2],[12]。英国拍卖是一种公开招标,即上升价格拍卖,其中投标人为了购买拍卖的物品而与其他投标人竞争投标。当给定时间到期时,最高出价者赢得拍卖,并且必须支付等于获胜出价的金额。这种类型的拍卖通常用于房地产。除了拍卖在预定的结束时间结束之外,许多网上拍卖都是在英国拍卖上建模的。

本章讨论uAuction的设计。详细讨论了设计类图和uAuction设计接口。

用于在uAuction中执行在线拍卖的高级软件模型。主要有两方:用户(投标人或卖方)和拍卖人。通信链接用于加入双方。

1.用户:用户可以是投标人或卖家。竞价人使用HTML浏览器与拍卖人交互。双向通信链接用于与拍卖人通信以进行投标或从拍卖人处获得诸如拍卖状态的信息。

1.拍卖人:拍卖人运行网络服务器(例如,MySQL服务器)和脚本语言如PHP。拍卖人负责从投标人和卖方处获取信息。拍卖人提供注册服务,日志服务,访问控制服务,数据持久化服务等。

B.界面设计

1)用户界面

这两个用户界面的其他附加功能将在本节中讨论。

bull;投标人界面:每个气泡都会显示一个网页,并且从一个页面到另一个页面的弧线表明热链接可以从第一页到第二页。双向通信链接表示可以浏览第一页到第二页,也可以从第二页返回到第一页。

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。

参考文献

  1. Best Auction software. Available: http://www.capterra.com/ 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

      剩余内容已隐藏,支付完成后下载完整资料


      资料编号:[23383],资料为PDF文档或Word文档,PDF文档可免费转换为Word

原文和译文剩余内容已隐藏,您需要先支付 30元 才能查看原文和译文全部内容!立即支付

以上是毕业论文外文翻译,课题毕业论文、任务书、文献综述、开题报告、程序设计、图纸设计等资料可联系客服协助查找。