TRADE-OFF ANALYSIS FOR GENERIC-POINT PARALLEL ELLIPTIC CURVE SCA-LAR MULTIPLICATION

Abstract

Several methods have been proposed to accelerate generic- point elliptic curve parallel scalar multiplication, including pre- com-putation-based methods and postcomputation-based methods. The methods proposed in the literature use key partitioning and process the key partitions via parallel processors. However, the best number of key partitions that would yield the best performance has yet to be investigated. Accordingly, this thesis conducts a trade-off analysis of all methods with different key sizes, numbers of processors and numbers of requests for generic- point elliptic curve parallel scalar multiplication. Furthermore, it proposes a new method and tests against the others. This new method demonstrates the best execution time in most cases.