
We propose a preimage attack against cryptographic hash functions based on the speedup enabled by quantum computing. Preimage resistance is a fundamental property cryptographic hash functions must possess. The motivation behind this work relies in the lack of conventional attacks against newly introduced hash schemes such as the recently elected SHA-3 standard. The proposed algorithm consists of two parts: a classical one running in O(log |S|), where S represents the searched space, and a quantum part that contains the bulk of the Deutsch-Jozsa circuit. The mixed approach we follow makes use of the quantum parallelism concept to check the existence of an argument (preimage) for a given hash value (image) in the preestablished search space. For this purpose, we explain how a non-unitary measurement gate can be used to determine if S contains the target value. Our method is entirely theoretical and is based on the assumptions that a hash function can be implemented by a quantum computer and the key measurement gate we describe is physically realizable. Finally, we present how the algorithm finds a solution on S.
Comment: Witdrawn by author - Inappropriate format
Quantum Physics, Computer Science - Cryptography and Security
Quantum Physics, Computer Science - Cryptography and Security
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
