Use of elliptic curves in cryptography
Lecture notes in computer sciences; 218 on Advances in cryptology---CRYPTO 85
Fast Algorithms for Common-Multiplicand Multiplication and Exponentiation by Performing Complements
AINA '03 Proceedings of the 17th International Conference on Advanced Information Networking and Applications
Guide to Elliptic Curve Cryptography
Guide to Elliptic Curve Cryptography
Trading Inversions for Multiplications in Elliptic Curve Cryptography
Designs, Codes and Cryptography
An Efficient Elliptic Curves Scalar Multiplication for Wireless Network
NPC '07 Proceedings of the 2007 IFIP International Conference on Network and Parallel Computing Workshops
Elliptic curve cryptography-based access control in sensor networks
International Journal of Security and Networks
IITA '08 Proceedings of the 2008 Second International Symposium on Intelligent Information Technology Application - Volume 02
Efficient and secure elliptic curve point multiplication using double-base chains
ASIACRYPT'05 Proceedings of the 11th international conference on Theory and Application of Cryptology and Information Security
Hi-index | 0.00 |
Elliptic curve cryptosystems have been the focus of much attention as the benefits of elliptic curve cryptography (ECC) become many such as a small software footprint, low hardware implementation costs, linear scalability, low bandwidth requirements, and high performance, which have been drawn great attentions in particular wireless sensor networks. Many papers have investigated various algorithms for fast calculations due to the wireless sensor networks are always limited power energy, constrict computing capacity, and other tighten resources such as storage capacity limited, etc. In this paper a novel algorithm is first presented, with which the hamming weight will be minimized therefore the calculation cost will be dropped and the cryptographic algorithm has gained the natures of ECC. This makes ECC more suitable for use in constrained environment such as mobile sensor information applications, where computing resources and power availability are limited. The final results show that, in comparison with popular algorithms, such as NAF, MOF and complementary algorithms, the proposed algorithm significantly improved (average about 12.5% decreasing comparing with complementary algorithms).