Visible to the public Distributed Solution of Scalar Multiplication on Elliptic Curves over Fp for Resource-constrained Networks

TitleDistributed Solution of Scalar Multiplication on Elliptic Curves over Fp for Resource-constrained Networks
Publication TypeConference Paper
Year of Publication2018
AuthorsRamdani, Mohamed, Benmohammed, Mohamed, Benblidia, Nadjia
Conference NameProceedings of the 2Nd International Conference on Future Networks and Distributed Systems
PublisherACM
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-6428-7
KeywordsElliptic curve cryptography, Elliptic curve cryptography (ECC), energy consumption, execution time, Metrics, pubcrawl, Resiliency, Scalability, scalar multiplication, wireless sensor networks (WSN)
AbstractElliptic curve cryptography (ECC) is an approach to public-key cryptography used for data protection to be unintelligible to any unauthorized device or entity. The encryption/decryption algorithm is publicly known and its security relies on the discrete logarithm problem. ECC is ideal for weak devices with small resources such as phones, smart cards, embedded systems and wireless sensor networks (WSN), largely deployed in different applications. The advantage of ECC is the shorter key length to provide same level of security than other cryptosystems like RSA. However, cryptographic computations such as the multiplication of an elliptic curve point by a scalar value are computationally expensive and involve point additions and doublings on elliptic curves over finite fields. Much works are done to optimize their costs. Based on the result of these works, including parallel processing, we propose two new efficient distributed algorithms to reduce the computations in resource-constrained networks having as feature the cooperative processing of data. Our results are conclusive and can provide up to 125% of reduction of consumed energy by each device in a data exchange operation.
URLhttp://doi.acm.org/10.1145/3231053.3231130
DOI10.1145/3231053.3231130
Citation Keyramdani_distributed_2018