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Comparative Study Between a Swarm Intelligence for Detection and Filtering of SPAM: Social Bees vs. Inspiration From the Human Renal
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Author(s): Mohamed Amine Boudia (Dr. Tahar Moulay University of Saida, Algeria), Mohamed Elhadi Rahmani (Dr. Tahar Moulay University of Saida, Algeria)and Amine Rahmani (GeCoDe Laboratory, Department of Computer Sciences, Dr. Tahar Moulay University of Saida, Algeria)
Copyright: 2018
Pages: 28
Source title:
Handbook of Research on Biomimicry in Information Retrieval and Knowledge Management
Source Author(s)/Editor(s): Reda Mohamed Hamou (Dr. Tahar Moulay University of Saida, Algeria)
DOI: 10.4018/978-1-5225-3004-6.ch003
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Abstract
This chapter is a comparative study between two bio-inspired approaches based on swarm intelligence for detection and filtering of SPAM: social bees vs. inspiration from the human renal. The authors took inspiration from biological model and use two meta-heuristics because the effects allow the authors to detect the characteristics of unwanted data. Messages are indexed and represented by the n-gram words and characters independent of languages (because a message can be received in any language). The results are promising and provide an important way to use this model for solving other problems in data mining. The authors start this paper with a short introduction where they show the importance of IT security. Then they give a little insight into the state of the art, before starting the essential part of a scientific paper, where they explain and experiment with two original meta-heuristics, and explain the natural model. Then they detail the artificial model.
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