Title :
Spam detection using compression and PSO
Author :
Prilepok, Michal ; Jezowicz, T. ; Platos, Jan ; Snasel, Vaclav
Author_Institution :
Dept. of Comput. Sci., VSB-Tech. Univ. of Ostrava, Ostrava, Czech Republic
Abstract :
The problem of spam emails is still growing. Therefore, developing of algorithms which are able to solve this problem is also very active area. This paper presents two different algorithms for spam detection. The first algorithm is based on Bayesian filter, but it is improved using data compression algorithms in case that the Bayesian filter cannot decide. The second algorithm is based on document classification algorithm using Particle Swarm Optimization. Results of presented algorithms are promising.
Keywords :
Bayes methods; data compression; document handling; e-mail filters; particle swarm optimisation; pattern classification; unsolicited e-mail; Bayesian filter; PSO; data compression algorithm; document classification algorithm; particle swarm optimization; spam email detection; Bayesian methods; Electronic mail; Graphics processing units; Measurement; Postal services; Vectors; Bayesian filter; data compression; e-mail; particle-swarm optimization; similarity; spam;
Conference_Titel :
Computational Aspects of Social Networks (CASoN), 2012 Fourth International Conference on
Conference_Location :
Sao Carlos
Print_ISBN :
978-1-4673-4793-8
DOI :
10.1109/CASoN.2012.6412413
