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Detection of Intrusions and Malware, and Vulnerability Assessment

Overview of attention for book
Cover of 'Detection of Intrusions and Malware, and Vulnerability Assessment'

Table of Contents

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    Book Overview
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    Chapter 1 Hybrid Pruning: Towards Precise Pointer and Taint Analysis
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    Chapter 2 Establishing the Contaminating Effect of Metadata Feature Inclusion in Machine-Learned Network Intrusion Detection Models
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    Chapter 3 Extended Abstract: Effective Call Graph Fingerprinting for the Analysis and Classification of Windows Malware
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    Chapter 4 COBRA-GCN: Contrastive Learning to Optimize Binary Representation Analysis with Graph Convolutional Networks
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    Chapter 5 Prioritizing Antivirus Alerts on Internal Enterprise Machines
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    Chapter 6 VANDALIR: Vulnerability Analyses Based on Datalog and LLVM-IR
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    Chapter 7 Branch Different - Spectre Attacks on Apple Silicon
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    Chapter 8 MPKAlloc: Efficient Heap Meta-data Integrity Through Hardware Memory Protection Keys
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    Chapter 9 A Human in Every APE: Delineating and Evaluating the Human Analysis Systems of Anti-Phishing Entities
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    Chapter 10 Amplification Chamber: Dissecting the Attack Infrastructure of Memcached DRDoS Attacks
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    Chapter 11 Consistency is All I Ask: Attacks and Countermeasures on the Network Context of Distributed Honeypots
Attention for Chapter 2: Establishing the Contaminating Effect of Metadata Feature Inclusion in Machine-Learned Network Intrusion Detection Models
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9 Mendeley
Summary
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Chapter title
Establishing the Contaminating Effect of Metadata Feature Inclusion in Machine-Learned Network Intrusion Detection Models
Chapter number 2
Book title
Detection of Intrusions and Malware, and Vulnerability Assessment
Published by
Springer, Cham, January 2022
DOI 10.1007/978-3-031-09484-2_2
Book ISBNs
978-3-03-109483-5, 978-3-03-109484-2
Authors

D’hooge, Laurens, Verkerken, Miel, Volckaert, Bruno, Wauters, Tim, De Turck, Filip

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 33%
Student > Bachelor 2 22%
Unknown 4 44%
Readers by discipline Count As %
Computer Science 3 33%
Economics, Econometrics and Finance 1 11%
Unknown 5 56%

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