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DC Field | Value | Language |
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dc.contributor.author | Charan K.S. | |
dc.contributor.author | Nakkina H.V. | |
dc.contributor.author | Chandavarkar B.R. | |
dc.date.accessioned | 2021-05-05T10:15:50Z | - |
dc.date.available | 2021-05-05T10:15:50Z | - |
dc.date.issued | 2020 | |
dc.identifier.citation | 2020 11th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2020 , Vol. , , p. - | en_US |
dc.identifier.uri | https://doi.org/10.1109/ICCCNT49239.2020.9225280 | |
dc.identifier.uri | http://idr.nitk.ac.in/jspui/handle/123456789/14829 | - |
dc.description.abstract | In a highly secure and robust key generation process, a key role is played by randomness and random numbers when current real-world cryptosystems are observed. Most present-day cryptographic protocols depend upon the Random Number Generators (RNG), Pseudo-Random Number Generator (PRNG). These protocols often use noisy channels such as Disk seek time, CPU temperature, Mouse pointer movement, Fan noise to obtain actual random values. Despite being cost-effective, these noisy channels may need additional hardware devices to communicate with them continuously. On the other hand, Hash functions are Pseudo-Random (because of their requirements) in nature. So, they are a suitable replacement for these noisy channels and have low hardware requirements. This paper discusses some of the key generation methodologies and their drawbacks. Further, it explains how hash functions can be used in key generation, how to combine Key Derivation Function (KDF)s with hash functions. © 2020 IEEE. | en_US |
dc.title | Generation of Symmetric Key Using Randomness of Hash Function | en_US |
dc.type | Conference Paper | en_US |
Appears in Collections: | 2. Conference Papers |
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