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2016 | OriginalPaper | Chapter

2. Machine Learning-Based System for Detecting Unseen Malicious Software

Authors : Federica Bisio, Paolo Gastaldo, Claudia Meda, Stefano Nasta, Rodolfo Zunino

Published in: Applications in Electronics Pervading Industry, Environment and Society

Publisher: Springer International Publishing

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Abstract

In the Internet age, malicious software (malware) represents a serious threat to the security of information systems. Malware-detection systems to protect computers must perform a real-time analysis of the executable files. The paper shows that machine-learning methods can support the challenging, yet critical, task of unseen malware recognition, i.e., the classification of malware variants that were not included in the training set. The experimental verification involved a publicly available dataset, and confirmed the effectiveness of the overall approach.

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Metadata
Title
Machine Learning-Based System for Detecting Unseen Malicious Software
Authors
Federica Bisio
Paolo Gastaldo
Claudia Meda
Stefano Nasta
Rodolfo Zunino
Copyright Year
2016
DOI
https://doi.org/10.1007/978-3-319-20227-3_2