Optimizing anti-spam filters with evolutionary algorithms

Date

2013-01-18

Advisors

Journal Title

Journal ISSN

ISSN

Volume Title

Publisher

Elsevier

Type

Article

Peer reviewed

Yes

Abstract

This work is devoted to the problem of optimising scores for anti-spam filters, which is essential for the accuracy of any filter based anti-spam system, and is also one of the biggest challenges in this research area. In particular, this optimisation problem is considered from two different points of view: single and multiobjective problem formulations. Some of existing approaches within both formulations are surveyed, and their advantages and disadvantages are discussed. Two most popular evolutionary multiobjective algorithms and one single objective algorithm are adapted to optimisation of the anti-spam filters’ scores and compared on publicly available datasets widely used for benchmarking purposes. This comparison is discussed, and the recommendations for the developers and users of optimising anti-spam filters are provided.

Description

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.

Keywords

Anti-spam filters, Multiobjective optimisation, Evolutionary computation, Genetic algorithms

Citation

Yevseyeva I., Basto-Fernandes V., Ruano-Ordás D., Mendez J.R. (2013) Optimizing anti-spam filters with evolutionary algorithms. Expert Systems with Applications. 40, (10), pp. 4010-4021

Rights

Research Institute

Cyber Technology Institute (CTI)