19 research outputs found
Performance of Additive Homomorphic EC-ElGamal Encryption for TinyPEDS, Under submission at 6
Data aggregation is a popular approach employed in wireless sensor networks (WSNs) to minimize data transmission and storage. With aggregation techniques, the monitored data is expressed in a condensed form: Therefore, instead of storing all data sensed by several nodes, the network stores a condensed value only such as the sum of these values. However, data aggregation becomes problematic when the data to be aggregated is encrypted. As a solution, we apply an additive homomorphic encryption scheme, namely the elliptic curve ElGamal (EC-ElGamal) cryptosystem, and present the performance results of our implementation for the prominent sensor platform MicaZ mote. 1
Optimized Implementation of Elliptic Curve Based Additive Homomorphic Encryption for Wireless Sensor Networks ABSTRACT
When deploying wireless sensor networks (WSNs) in public environments it may become necessary to secure their data storage and transmission against possible attacks such as node-compromise and eavesdropping. The nodes feature only small computational and energy resources, thus requiring efficient algorithms. As a solution for this problem the TinyPEDS approach was proposed in [7], which utilizes the Elliptic Curve ElGamal (EC-ElGamal) cryptosystem for additive homomorphic encryption allowing concealed data aggregation. This work presents an optimized implementation of EC-ElGamal on a MicaZ mote, which is a typical sensor node platform with 8-bit processor for WSNs. Compared to the best previous result, our implementation is at least 44% faster for fixed-point multiplication. Because most parts of the algorithm are similar to standard Elliptic Curve algorithms, the results may be reused in other realizations on constrained devices as well