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Recent Advances in Intrusion Detection

This book constitutes the refereed proceedings of the 9th International Symposium on Recent Advances in Intrusion Detection, RAID 2006;

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Recent Advances in Intrusion Detection

On behalf of the Program Committee, it is our pleasure to present the p- ceedings of the 13th International Symposium on Recent Advances;

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Intrusion Detection

With the number of intrusion and hacking incidents around the world on the rise, the importance of having dependable intrusion detection;

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The Practical Intrusion Detection Handbook

Intrusion detection systems are increasingly recognized as a key weapon in the war against computer crime. In The Practical Intrusion;

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State Of The Art In Intrusion Prevention

The State of the Art in Intrusion Prevention and Detection analyzes the latest trends and issues surrounding intrusion detection systems;

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The State of the Art in Intrusion Prevention and Detection

The State of the Art in Intrusion Prevention and Detection analyzes the latest trends and issues surrounding intrusion detection systems;

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Data Analytics and Decision Support for Cybersecurity

. This contributed volume comprises nine chapters, written by leading international researchers, covering a compilation of recent advances;

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Intrusion Detection Networks

intrusion detection network (IDN). Using overlay networks that allow an intrusion detection system (IDS) to exchange information, IDNs can;

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Security, Privacy and Reliability in Computer Communications and Networks

advances reflecting the state-of-the-art research achievements in novel cryptographic algorithm design, intrusion detection, privacy preserving;

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Metrics for Intrusion Detection in Wireless Sensor Networks

attacks. In this book a novel approach for intrusion detection in wireless sensor networks is developed. Common performance and network metrics;

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Network Intrusion Detection

Written to be both a training aid and a technical reference for intrusion detection analysts, Northcutt's book contains unparalleled;

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Vapor Intrusion Simulations and Risk Assessments

feature the recent advances in vapor intrusion studies and practices, including analytical and numerical modeling of vapor intrusion, statistical;

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Network Security: Issues, Challenges and Techniques

, this volume discusses the design of effective Intrusion Detection Systems (IDS), clustering techniques in designing anomaly based IDS, network;

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Implementing Intrusion Detection Systems

Configuring an Intrusion Detection System (IDS) is very challenging, and if improperly configured, an IDS is rendered ineffective. Packed;

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Intrusion Detection using Feature Selection and Hybridized

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Stateful intrusion detection in high-speed networks

The present work is aimed to develop and analyze a novel model for distributed stateful intrusion detection able to scale in order to keep;

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Erstellung eines Intrusion Detection Systems fur eine Firewall

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Viable Network Intrusion Detection

Network intrusion detection systems (NIDS) continuously monitor network traffic for malicious activity, raising alerts when detecting;

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An intrusion detection system using machine learning algorithm

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Network Anomaly Detection

, network intrusion detection has become increasingly important. Anomaly-based network intrusion detection refers to finding exceptional or;

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Advances in Security Information Management

management (SIEM) then appears as the new paradigm to reconcile traditional intrusion detection systems along with recently advanced techniques such;

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Evaluation of Some Windows and Linux Intrusion Detection Tools

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Practical Intrusion Analysis

, Cofounder, Stratum Security The Only Definitive Guide to New State-of-the-Art Techniques in Intrusion Detection and Prevention;

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Configure intrusion detection and alerts - Reduce security risks using Azure Security Service

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Distributed Intrusion

may be due to System software flaws, improper system administration procedures or failure of the Authentication module. Intrusion detection;

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Intrusion Detection with Artificial Neural Networks

Intrusion detection system is a detection mechanism that detects unauthorized, malicious presents in the computer systems. The purpose;

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Online and Adaptive Signature Learning for Intrusion Detection

This thesis presents the case of dynamically and adaptively learning signatures for network intrusion detection using genetic based machine;

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