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Date of Award
2018
Document Type
Restricted Thesis: Campus only access
Degree Name
Bachelor of Science
Department
Computer Science
Abstract
Traditional encryption methods operate on arbitrary binary plaintext strings and produce arbitrary binary ciphertexts. In applications, however, we may need ciphertexts which are not arbitrary binary strings but rather strings conforming to a particular format. For example, if we want to communicate over a network, we may want our ciphertext to be a particular packet type. If we are storing the ciphertext in a database, there are often specic data types or formats in which the entries must be stored. In these and other cases, we may also be interested in obscuring the original type of data: the format in which the ciphertext is encoded may or may not be the same as the format of the original plaintext. The idea of format-transforming encryption is to generate ciphertexts that conform to a specic format while providing cryptographic security at least as good as we would get from standard encryption methods.
While FTE can be a useful privacy tool, we must still consider various tradeoffs. For example, we must balance accuracy to the intended ciphertext format, computational resources to recognize the ciphertext format based on known examples, and the capacity of the encryption scheme in terms of how many ciphertext bits are required to represent a single plaintext bit.
Recommended Citation
Clayton, David, "Format-transforming encryption : regular language and machine learning techniques for obfuscating ciphertexts" (2018). Honors Theses. 1324.
https://scholarship.richmond.edu/honors-theses/1324