Cryptographic hash functions are one of the widely used cryptographic primitives with a purpose to ensure the integrity of the system or data. Hash functions are also utilized in conjunction with digital signatures to provide authentication and non-repudiation services. Secure Hash Algorithms are developed over time by the National Institute of Standards and Technology (NIST) for security, optimal performance, and robustness. The most known hash standards are SHA-1, SHA-2, and SHA-3.
The secure hash algorithms are considered weak if security requirements have been broken. The main security attacks that threaten the secure hash standards are collision and length extension attacks. The collision attack works by finding two different messages that lead to the same hash. The length extension attack extends the message payload to produce an eligible hash digest. Both attacks already broke some hash standards that follow the Merkle-Damgrard construction. This dissertation proposes methodologies to improve and strengthen weak hash standards against collision and length extension attacks. We propose collision-detection approaches that help to detect the collision attack before it takes place. Besides, a proper replacement, which is supported by a proper construction, is proposed. The collision detection methodology helps to protect weak primitives from any possible collision attack using two approaches. The first approach employs a near-collision detection mechanism that was proposed by Marc Stevens. The second approach is our proposal. Moreover, this dissertation proposes a model that protects the secure hash functions from collision and length extension attacks. The model employs the sponge structure to construct a hash function. The resulting function is strong against collision and length extension attacks. Furthermore, to keep the general structure of the Merkle-Damgrard functions, we propose a model that replaces the SHA-1 and SHA-2 hash standards using the Merkle-Damgrard construction. This model employs the compression function of the SHA-1, the function manipulators of the SHA-2, and the $10*1$ padding method. In the case of big data over the cloud, this dissertation presents several schemes to ensure data security and authenticity. The schemes include secure storage, anonymous privacy-preserving, and auditing of the big data over the cloud.
| Identifer | oai:union.ndltd.org:ndsu.edu/oai:library.ndsu.edu:10365/32058 |
| Date | January 2020 |
| Creators | Al-Odat, Zeyad Abdel-Hameed |
| Publisher | North Dakota State University |
| Source Sets | North Dakota State University |
| Detected Language | English |
| Type | text/dissertation |
| Format | application/pdf |
| Rights | NDSU policy 190.6.2, https://www.ndsu.edu/fileadmin/policy/190.pdf |
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