Highly scalable on-line payments via task decoupling

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Abstract

Several digital payment systems have been described which attempt to simulate or extend already existing payment mechanisms so as to make them suitable for electronic commerce. Such mechanisms or instruments include cash or coins (e.g., DigiCash, NetCash), checks (e.g., NetCheque), and credit cards (e.g., CyberCash). The anonymity, off-line, and peer-to-peer aspects of some of these systems can introduce security weaknesses and major scalability problems. One approach to security, as taken by the Millicent architecture, is to only allow very low cost transactions. True security, unlike the approach taken by First Virtual, requires clear delineation of the customer and merchant roles. The goal of this paper is to outline an approach which is inexpensive enough to allow for very low value transactions but secure enough to allow for intermediate value transactions, while providing true customer anonymity with respect to merchants and electronic handling of refund requests. Unlike NetBill and the GC Tech GlobelD system, under the default operation of the system the customer in no way authenticates or identifies itself to the merchant, pseudonymously or otherwise. This is an example of the decoupling of tasks used as a basic design principle: Each system component deals directly with only those aspects in its narrowly defined scope of responsibilities, and within this asynchronous system time-consuming or time-varying issues not directly related to the payment flow, such as actual delivery of digital goods, are handled outside of the basic payment flow. After presenting a high-level comparison of our approach to those of two other instant debit systems, GlobelD and NetBill, we give a more detailed explanation of the design criteria and characteristics exhibited by this new approach to on-line payments.

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APA

Kravitz, D. W. (2015). Highly scalable on-line payments via task decoupling. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1318, pp. 355–373). Springer Verlag. https://doi.org/10.1007/3-540-63594-7_91

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