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A Non-Adjacent Form (NAF) Based ECC for Scalar Multiplication that Assure Computation Reduction on Outsourcing

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Proceeding of the International Conference on Computer Networks, Big Data and IoT (ICCBI - 2018) (ICCBI 2018)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 31))

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Abstract

Sustaining privacy and securing the various data sources using lightweight cryptosystem is becoming essential in this digital world. Any sensitive information or resource container in the web that are exposed in the form of url must be preserved using suitable cryptographic techniques. One of the technique that belong to public key cryptography and truly identified for providing security towards digitial resource is Elliptical Curve Cryptography (ECC). ECC is one of the small key sized and fast computation cryptographic model that consumes less power, memory and bandwidth to ensure equivalent security than already existing one. Digital world engaged in on-line data security is the most pressing issues to transaction, have to trust the data disclosure in storage, ensure modification immunity in transit and assures identity among the communicating parties. Hence, the CIA packed computing paradigm that impact towards confidentiality, integrity and authentication is an urgent need. The first one and most important security traits is the confidentiality. This can be achieved by encryption operation. In ECC, encryption and decryption operation is carried using Elliptical curve arithmetic mechanism. This mechanism is based on point multiplication that is performed using repeated point addition and point doubling. The proposed alternative efficient method for point multiplication is binary form or NAF (Non-Adjacent Form). The computation performance with NAF preprocessed and on-the-fly approach ensures optimisation than the binary form of scalar multiplication.

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Correspondence to R. Menaka .

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Menaka, R., Wahida Banu, R.S.D. (2020). A Non-Adjacent Form (NAF) Based ECC for Scalar Multiplication that Assure Computation Reduction on Outsourcing. In: Pandian, A.P., Senjyu, T., Islam, S.M.S., Wang, H. (eds) Proceeding of the International Conference on Computer Networks, Big Data and IoT (ICCBI - 2018). ICCBI 2018. Lecture Notes on Data Engineering and Communications Technologies, vol 31. Springer, Cham. https://doi.org/10.1007/978-3-030-24643-3_38

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  • DOI: https://doi.org/10.1007/978-3-030-24643-3_38

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-24642-6

  • Online ISBN: 978-3-030-24643-3

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