Please use this identifier to cite or link to this item: https://idr.l4.nitk.ac.in/jspui/handle/123456789/7444
Title: Bad signature identification in a batch using error detection codes
Authors: Kittur, A.S.
Kauthale, S.
Pais, A.R.
Issue Date: 2019
Citation: Communications in Computer and Information Science, 2019, Vol.939, , pp.53-66
Abstract: In today�s digital communication world, authentication of data and the sender is very important before processing. Digital Signatures are the best way for verifying the authenticity of the message or document. When multiple signatures need to be verified together, we use batch signature verification. There are multiple batch verification algorithms for various digital signature schemes such as ECDSA, RSA, DSS and others. Most of the batch verification techniques fail to locate the position of the invalid signature/s in a batch. Hence there are multiple bad signature identification algorithms available to locate the bad signatures. The existing algorithms are inefficient in identifying position of bad signature, if the number of bad signatures increases in the batch or if the number of bad signatures are not known before verification. Hence such schemes are practically not suitable for real time environment. Our proposed CRC based verifier scheme overcomes these disadvantages, as well as outperforms the existing schemes in efficiently identifying the bad signature/s. The comparative analysis of the proposed scheme and the existing schemes, is also discussed in the paper. � Springer Nature Singapore Pte Ltd. 2019.
URI: http://idr.nitk.ac.in/jspui/handle/123456789/7444
Appears in Collections:2. Conference Papers

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