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Trust-Based Classifier Combination for Network Anomaly Detection

AbstractWe present a method that improves the results of network intrusion detection by integrating several anomaly detection algorithms through trust and reputation models. Our algorithm is based on...

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Improving Anomaly Detection Error Rate by Collective Trust Modeling

AbstractCurrent Network Behavior Analysis (NBA) techniques are based on anomaly detection principles and therefore subject to high error rates. We propose a mechanism that deploys trust modeling, a...

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Collaborative Approach to Network Behavior Analysis

AbstractNetwork Behavior Analysis techniques are designed to detect intrusions and other undesirable behavior in computer networks by analyzing the traffic statistics. We present an efficient framework...

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Runtime Monitoring and Dynamic Reconfiguration for Intrusion Detection Systems

AbstractOur work proposes a generic architecture for runtime monitoring and optimization of IDS based on the challenge insertion. The challenges, known instances of malicious or legitimate behavior,...

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Towards Efficient Flow Sampling Technique for Anomaly Detection

AbstractWith increasing amount of network traffic, sampling techniques have become widely employed allowing monitoring and analysis of high-speed network links. Despite of all benefits, sampling...

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Distributed Self-organized Collaboration of Autonomous IDS Sensors

AbstractWe present distributed self-organized model for collaboration of multiple heterogeneous IDS sensors. The adaptation model is based on a game-theoretical approach that optimizes the behavior of...

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Game Theoretical Adaptation Model for Intrusion Detection System - Demo Paper

AbstractWe present a self-adaptation mechanism for Network Intrusion Detection System which uses a game-theoretical mechanism to increase system robustness against targeted attacks on IDS adaptation....

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Game Theoretical Adaptation Model for Intrusion Detection System

AbstractWe present a self-adaptation mechanism for Network Intrusion Detection System which uses a game-theoretical mechanism to increase system robustness against targeted attacks on IDS adaptation....

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Self-organized Collaboration of Distributed IDS Sensors

AbstractWe present a distributed self-organized model for collaboration of multiple heterogeneous IDS sensors. The distributed model is based on a game-theoretical approach that optimizes behavior of...

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Game Theoretical Model for Adaptive Intrusion Detection System

AbstractWe present a self-adaptation mechanism for network intrusion detection system based on the use of game-theoretical formalism. The key innovation of our method is a secure runtime definition and...

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Robust Representation for Domain Adaptation in Network Security

AbstractThe goal of domain adaptation is to solve the problem of different joint distribution of observation and labels in the training and testing data sets. This problem happens in many practical...

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Learning Detector of Malicious Network Traffic from Weak Labels

AbstractWe address the problem of learning a detector of malicious behavior in network traffic. The malicious behavior is detected based on the analysis of network proxy logs that capture malware...

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Learning data discretization via convex optimization

AbstractDiscretization of continuous input functions into piecewise constant or piecewise linear approximations is needed in many mathematical modeling problems. It has been shown that choosing the...

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