Financial Cryptography and Data Security: 16th International by Hyoungshick Kim, John Tang, Ross Anderson (auth.), Angelos

By Hyoungshick Kim, John Tang, Ross Anderson (auth.), Angelos D. Keromytis (eds.)

This ebook constitutes the completely refereed post-conference court cases of the sixteenth foreign convention on monetary Cryptography and knowledge defense (FC 2012), held in Kralendijk, Bonaire, February 27–March 1, 2012. The 29 revised complete papers offered have been conscientiously chosen and reviewed from 88 submissions. The papers hide all points of securing transactions and platforms, together with details insurance within the context of finance and commerce.

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Extra resources for Financial Cryptography and Data Security: 16th International Conference, FC 2012, Kralendijk, Bonaire, Februray 27-March 2, 2012, Revised Selected Papers

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2 PIN Selection Strategies We invited the 1,108 respondents with a PIN of exactly 4 digits to identify their PIN selection method. This was the most sensitive part of the survey, and users were able to not provide this information without penalty, removing a further 27% of respondents and leaving us with 805 responses from which to estimate PIN strength. We presented users with detailed descriptions and examples for each of the selection strategies identified in our regression model. Users were also able to provide free-form feedback on how they chose their PIN.

Canadian banks use a mix of 4-digit and 6-digit PINs. We assume any reasonable denied PIN list would include 1234 and allowing this PIN indicates no restrictions exist. 28 J. Bonneau, S. Preibusch, and R. Anderson Zieli´ nski developed further decimalisation-based attacks in 2003 [5]. Both attacks can be improved with knowledge of human tendencies in PIN selection. 2 Quantifying Resistance to Guessing We consider abstractly the probability distribution5 of PINs X over the set {0000, . . , 9999}.

Therefore, we presume that the amounts being invested reflect the initial opinion of the aggregator about the prospects for the HYIP. If there was some kind of universal conspiracy then we would expect to see consistency here, but the aggregators invest the same amount of money into HYIPs in only 10% of cases. Naturally, even when there isn’t unanimous agreement across aggregators, it could still be the case that almost all of aggregators report the same values. Consequently, the two tables also report Simpson’s diversity index [1] for each attribute.

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