Full metadata record
| DC pole | Hodnota | Jazyk |
|---|---|---|
| dc.contributor.author | Turčaník, Michal | |
| dc.contributor.editor | Pinker, Jiří | |
| dc.date.accessioned | 2019-10-17T05:20:46Z | |
| dc.date.available | 2019-10-17T05:20:46Z | |
| dc.date.issued | 2017 | |
| dc.identifier.citation | 2017 International Conference on Applied Electronics: Pilsen, 5th – 6th September 2017, Czech Republic, p.253-256. | en |
| dc.identifier.isbn | 978–80–261–0641–8 (Print) | |
| dc.identifier.isbn | 978–80–261–0642–5 (Online) | |
| dc.identifier.issn | 1803–7232 (Print) | |
| dc.identifier.issn | 1805–9597 (Online) | |
| dc.identifier.uri | http://hdl.handle.net/11025/35448 | |
| dc.format | 4 s. | cs |
| dc.format.mimetype | application/pdf | |
| dc.language.iso | en | en |
| dc.publisher | Západočeská univerzita v Plzni | cs |
| dc.rights | © Západočeská univerzita v Plzni | cs |
| dc.subject | hashovací funkce | cs |
| dc.subject | opakující se neuronová síť | cs |
| dc.title | Using recurrent neural network for hash function generation | en |
| dc.type | konferenční příspěvek | cs |
| dc.type | conferenceObject | en |
| dc.rights.access | openAccess | en |
| dc.type.version | publishedVersion | en |
| dc.description.abstract-translated | Effective generation of hash function is very important for an achievement of a security of today networks. A cryptographic hash function is a transformation that takes an input and returns a fixed-size value, which is called the hash value. A recurrent neural network, as a possible approach, could be used for the hash function generation. The performance of the recurrent neural network (RNN) was validated by software implementation of RNN for given network configuration. The principles of recurrent neural networks and the possibility of using recurrent neural network for hashing are presented in the article. For analysis of RNN were created testing sets on the base of several examples of general texts. In the paper were tested RNNs with three layers. | en |
| dc.subject.translated | hash function | en |
| dc.subject.translated | recurrent neural network | en |
| dc.type.status | Peer-reviewed | en |
| Vyskytuje se v kolekcích: | Applied Electronics 2017 Applied Electronics 2017 | |
Soubory připojené k záznamu:
| Soubor | Popis | Velikost | Formát | |
|---|---|---|---|---|
| Turčaník.pdf | Plný text | 358,39 kB | Adobe PDF | Zobrazit/otevřít |
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