Determining the Effective Entropy of A Visual Hash System Public Deposited

http://ir.library.oregonstate.edu/concern/undergraduate_thesis_or_projects/hq37vp87j

An undergraduate thesis pertaining to the viability of fractal images as visual hashes in cryptographic processes.

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  • Fractal visual hashes have the potential to replace traditional hexadecimal hashes for SSH applications with the goal of increasing user recognition of identities of remote computers. Rather than rely on human users manually comparing two hexadecimal hashes as part of SSH's public-private key encryption process, users would compare fractal images generated from the original hexadecimal hashes to determine if the keys match. A visual hash comparison and differentiation game was developed that evaluated the ability of users to differentiate between two images visually. Users were presented with pairs of either flag hashes, t-flag hashes, identicon hashes, hexadecimal hashes, or fractal hashes and were asked to decide if the images were the same or different. The hashes generated were created in a way so that hashes being compared were very similar in their visual characteristics to increase the number of images that were hard to distinguish. The data collected was analyzed through Bayesian analysis wherein the user input and the hash details were evaluated to the find the highest probability effective entropy and user error of the system. The fractal visual hash achieved the highest amount of effective entropy among the tested hash types and provided a foundation for further research to be conducted on visual hash systems and the validity of fractal hashes.
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  • description.provenance : Made available in DSpace on 2015-06-05T15:18:53Z (GMT). No. of bitstreams: 1 Determining the Effective Entropy of a Visual Hash System.pdf: 2665877 bytes, checksum: 40783a65561a6f41c2a93984f15f518a (MD5)
  • description.provenance : Approved for entry into archive by Patricia Black(patricia.black@oregonstate.edu) on 2015-06-05T15:18:53Z (GMT) No. of bitstreams: 1 Determining the Effective Entropy of a Visual Hash System.pdf: 2665877 bytes, checksum: 40783a65561a6f41c2a93984f15f518a (MD5)
  • description.provenance : Submitted by Joshua Montegna (montegnj@onid.orst.edu) on 2015-06-04T18:25:00Z No. of bitstreams: 1 Determining the Effective Entropy of a Visual Hash System.pdf: 2665877 bytes, checksum: 40783a65561a6f41c2a93984f15f518a (MD5)

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