Analysis of RSA and ELGAMAL Algorithm for Wireless Sensor Network
Journal: International Journal of Computer Techniques (Vol.2, No. 4)Publication Date: 2015-07-01
Authors : Surekha J; Anita Madona M;
Page : 25-31
Keywords : Asymmetric cryptography; ELGAMAL; RSA; security; wireless sensor network (WSN);
Abstract
Wireless sensor network (WSN) is primarily designed for real-time collection and analysis of data in hostile environments. One of the major challenges of WSN is security. Network security is the most vital component in information security, because it is responsible for securing all information passed through the networks. The security of WSN poses challenges because of the criticality of the data sensed by a node and in turn the node meets severe constraints, such as minimal power, computational, and communicational capabilities. An identification of a suitable cryptographic algorithm for WSN is an important challenge due to the computational time, computation capability, and storage resources of the sensor nodes. Many symmetric algorithms have been implemented for sensor networks. In earlier studies, it is found that asymmetric algorithms, such as ELGAMAL and RSA, have not been implemented due to high-power constraint and for memory constraints. In this paper, it can be implemented for wireless sensor in an efficient manner using optimized computation. In this paper, the performance of the RSA cryptography algorithm is compared with the ELGAMAL algorithm by evaluating the cluster-based wireless network topology environment. The simulation results of both RSA and ELGAMAL show the comparative study using the NS2 simulation tool. The result shows that the RSA algorithm consumes a less computational time, data transmitting, and has a good storage capacity than the ELGAMAL.
Other Latest Articles
- Using change point analysis to determine perception accuracyinsocial media opinions
- Техника актёра (проблемы сценического движения и пластики)
- Instruments supporting selfemployment
- Теоретический анализ подходов к определению феномена саморегуляции
- The master of craniofacial orchestra: Homeobox genes and neural crest cells
Last modified: 2015-07-18 13:47:56