Secure Electronic Voting System using Swarm Intelligence

Abstract

One of the important systems for society today is the electronic voting system. All the people around the world are looking for transparency and integrity, and they afraid of voting fraud. Electronic voting system is looking for confirming the true identity of a person. Fingerprint identification may be preferred over traditional methods (e.g. passwords, smart-cards) because its information is virtually impossible to steal. This paper introduces secure election system depending on swarm intelligence techniques, especially PSO and firefly algorithms. The proposed system is successful within 500 iterations for PSO to find best features for fingerprint. Best steganographic positions are found by firefly algorithm. PSO has been reduced the time for features extraction of one fingerprint from (1.1 sec) to (0.36 sec). Firefly algorithm has been raised the PSNR of the stegocovers up to (66.246-69.447)dB. The percentage matching of all bands at receiver side is 100%.