Modeling Elliptical Curve Cryptography Keys using Back Propagation Algorithm
Ekta Narwal1, Sumeet Gill2
1Ekta Narwal, Department of Mathematics, M.D. University, Rohtak, Haryana, India.
2Sumeet Gill, Department of Mathematics, M.D.University, Rohtak, Haryana, India.
Manuscript received on 10 July 2019 | Revised Manuscript received on 22 July 2019 | Manuscript Published on 23 August 2019 | PP: 1525-1529 | Volume-8 Issue-9S3 August 2019 | Retrieval Number: I33180789S319/2019©BEIESP | DOI: 10.35940/ijitee.I3318.0789S319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Vehicular Ad Hoc Networks (VANETs) are the newest for of Ad Hoc Networks in which moving vehicles act as routers and nodes to form a network. VANETs use many cryptographic approaches like symmetric key approaches, public key approaches, certificate revocation, pseudonym based approaches, identity-based cryptography, identity-based signature, Elliptical Curve Cryptography (ECC) etc. for secure communication. These techniques use public and private keys for enhancing the security of messages and all these keys are stored on hardware devices like TPDs (Temper Proof Devices) in VANETs. TPDs are protected by the cryptographic algorithms. In this present era of technology these algorithms and their online simulators are freely available on internet and can be easily intruded. There is a potential need to enhance the security of these keys. In this paper we worked on enhancing the security of ECC keys stored in TPDs of VANETs using a specific network of Artificial Neural Networks.
Keywords: VANETs (Vehicular Ad Hoc Networks), TPD (Temper Proof Devices), ECC (Elliptical Curve Cryptography), ANN (Artificial Neural Networks)
Scope of the Article: Cryptography and Applied Mathematics