Improving malware detection by applying multi-inducer ensemble

@article{Menahem2009ImprovingMD,
  title={Improving malware detection by applying multi-inducer ensemble},
  author={Eitan Menahem and Asaf Shabtai and Lior Rokach and Yuval Elovici},
  journal={Computational Statistics & Data Analysis},
  year={2009},
  volume={53},
  pages={1483-1494}
}
Detection of malicious software (malware) using ma chine learning methods has been explored extensively to enable fas t detection of new released malware. The performance of these classifiers depen ds on the induction algorithms being used. In order to benefit from mul tiple different classifiers, and exploit their strengths we suggest using an ens emble method that will combine the results of the individual classifiers i nto one final result to achieve overall higher detection accuracy. In… CONTINUE READING
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