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MalProfiler: Automatic and Effective Classification of Android Malicious Apps in Behavioral Classes Read chapter Read first chapter

2017 | OriginalPaper | Chapter

Multi-Criteria Recommender Approach for Supporting Intrusion Response System

Authors : Tarek Bouyahia, Nora Cuppens-Boulahia, Frédéric Cuppens, Fabien Autrel

Published in: Foundations and Practice of Security

Publisher: Springer International Publishing

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Abstract

Recommender systems are tools for processing and organizing information in order to give assistance to the system users. This assistance is provided by analyzing their own preferences or the preferences of their community. This paper introduces an approach based on content-based recommendation for efficient security administrators assistance in the context of reaction against intrusion detection. The proposed methodology considers the set of active contexts while analyzing the security administrator decisions historic. It provides better recommendation depending on the contexts in which the system is operating. For instance, in an automotive system, given an attack scenario, the fact that a vehicle is operating on downtown or on a highway influences countermeasures selection.

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previous chapter Micro-signatures: The Effectiveness of Known Bad N-Grams for Network Anomaly Detection
next chapter An Optimal Metric-Aware Response Selection Strategy for Intrusion Response Systems
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Metadata
Title
Multi-Criteria Recommender Approach for Supporting Intrusion Response System
Authors
Tarek Bouyahia
Nora Cuppens-Boulahia
Frédéric Cuppens
Fabien Autrel
Copyright Year
2017
Book
Foundations and Practice of Security

Print ISBN: 978-3-319-51965-4

Electronic ISBN: 978-3-319-51966-1

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-51966-1_4

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