Showing papers by "Wayne Read published in 2009"

Detecting shill bidding in online English auctions

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. While shilling is recognized as a problem, presently there is little or no established means of defense against shills. This chapter presents an algorithm to detect the presence of shill bidding in online auctions. It observes bidding patterns over a series of auctions, providing each bidder a score indicating the likelihood of his/her potential involvement in shill behavior. The algorithm has been tested on data obtained from a series of realistic simulated auctions, and commercial online auctions. The algorithm is able to prune the search space required to detect which bidders are likely to be shills. This has significant practical and legal implications for commercial online auctions where shilling is considered a major threat. This chapter presents a framework for a feasible solution, which acts as a detection mechanism and a deterrent.

A Proactive Approach to Preventing Phishing Attacks Using Pshark

Abstract: Phishing is an online scam used to dupe people out of their personal information for the purpose of defrauding them. This paper presents a conceptual design for removing phishing pages that have been uploaded on a website, potentially without knowledge of the website owner or host server. Initially the system is alerted to the presence of a phishing page upon receiving the Phisher’s solicitation e-mail. Next the system retrieves the location, IP address and contact information of the host server using a tracking program. Finally, the system sends notification to the Administrator about the phishing page on its server. It is then up to the host server Administrator to remove the phishing page from its server, or face the possibility of criminals continuing to use their site. This approach acts as the basis for further development into proactively (or aggressively) attacking Phishers directly, rather than being a reactionary approach that is common to most email filters and anti-virus software.

Online Payments Using Handwritten Signature Verification

Abstract: Making payments online is inherently insecure, especially those involving credit cards where a handwritten signature is normally required to be authenticated. This paper describes a system for enhancing the security of online payments using automated handwritten signature verification. Our system combines complementary statistical models to analyse both the static features of a signature (e.g., shape, slant, size), and its dynamic features (e.g., velocity, pen-tip pressure, timing) to form a judgment about the signer's identity. This approach's novelty lies in combining output from existing Neural Network and Hidden Markov Model based signature verification systems to improve the robustness of any specific approach used alone. The system can be used to authenticate signatures for online credit card payments using an existing model for remote authentication. The system performs reasonably well and achieves an overall error rate of 2.1% in the best case.

A Software Tool for Collecting Data from Online Auctions

Abstract: Online auctions are increasingly becoming the platform of choice for dubious sellers to engage anonymously in fraudulent behaviour. While researchers are noble in their efforts to devise mechanisms to counter auction fraud, they are often frustrated by the lack of available auction data. Such data is an invaluable tool to gain insight about fraudulent traits and for testing proposed security remedies. This is compounded by online auction sources being non-cooperative in providing auction data, usually citing "security and privacy'' as reasons for not wanting to help. This paper presents a software tool that can extract data from various online auction sources. The system is able to collect all the data for a given search criteria on auctions that have completed, and also returns later to collect the data from ongoing auctions once they have completed (without user intervention). We share our experiences from the development process and describe the challenges that must be overcome to successfully set up such a system. The data collected is used to analyse the behaviour and bidding patterns of sellers and buyers that are engaged in online auctions. The work presented in this paper represents the first serious attempt at creating an openly available software tool and establishing a repository of online auction data that will be free for use by other researchers.

Analysing Bidding Trends in Online Auctions

Abstract: Online auctions such as eBay are becoming increasingly more important mechanisms for people to buy and sell items online. In general, e-commerce is becoming fundamental to transacting business around the globe. With the added convenience of online transactions also comes the risk of electronic fraud. Although companies such as eBay have operated for the last 10 - 15 years, very little auction data has been collected and made publicly available or analysed, to the knowledge of the authors. Before any assertions about the amount of fraud in online auctions can be made, the underlying nature and structure of online auctions must be understood. In this paper we present definitions of a good auction from the viewpoints of the stake holders of the auction (e.g., bidder, seller, auctioneer, etc.) and then provide an analysis of auction data methodically collected from live eBay auctions. We collected data from 1005 auctions for three commonly available electronic devices. We show that the number of bids per auction is independent of the duration of the auction, and that the proportion of proxy bids is also approximately constant, for the duration of the auction. However, the final bid price achieved during the auction is shown to be related to the duration. Although these results are preliminary, we believe that they provide a significant insight into online auction behaviour.

Computational aspects of accurately modelling salt advection beneath aquaculture ponds

Abstract: Aquaculture is becoming an important primary industry in Australia and the Asian region Environmental concerns are raised when above ground saline ponds are introduced over fresh groundwater The flow field can be simply modelled using series solutions for the hydraulic potential However, extracting the advection fronts and isochrones can be much more challenging, particularly when solutions are sought using a laptop or desktop computer We present an efficient and accurate way to calculate the advection front and the isochrones for a realistic problem These methods use the analytic nature of the flow field solution and are an efficient and accurate alternative to the traditional methods used References J R Philip, Travel Times From Buried and Surface Infiltration Point Sources, Water Resources Research 20 (7) 990--994, 1984 doi:101029/WR020i007p00990 W L Powers, D Kirkham, G Snowden, Orthonormal Function Tables and the Seepage of Steady Rain through Soil Bedding, Journal of Geophysical Research 72 (24) 6225--6237, 1967 doi:101029/JZ072i024p06225 W W Read, Hillside Seepage and the Steady Water Table I: Theory, Advances in Water Resources 19 (2) (1996) 63--73 doi:101016/0309-1708(95)00034-8 W W Read, Hillside Seepage and the Steady Water Table II: Applications, Advances in Water Resources 19 (2) (1996) 75--81 doi:101016/0309-1708(95)00035-6

An application tool for collecting real auction data

Abstract: Online auctions are a rapidly growing platform to exchange items of just about anything, from common to collectors' items in different region around the world. Researchers continue their efforts to understand further the real behaviour and bidding patterns of buyers and sellers, the fraudulent traits and even devise countermeasures to prevent auction fraud. Most often, the researchers' noble work ends with frustration due to unavailability of real auction data. Online auction sources are unwilling to provide the real auction data and often cite "commercial, security and privacy" as reasons. This paper presents an application tool that collects real auction data from an ongoing auction for a given criteria, and automatically returns later to collect the data from a recently completed auction. From the knowledge of the authors, the work presented here is the first serious attempt to create an openly available application tool that will be free for use by other researchers.