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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

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Analyzing Memory Accesses in Obfuscated x86 Executables
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    Chapter 2 Hybrid Engine for Polymorphic Shellcode Detection
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    Chapter 3 Experiences Using Minos as a Tool for Capturing and Analyzing Novel Worms for Unknown Vulnerabilities
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    Chapter 4 A Pointillist Approach for Comparing Honeypots
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    Chapter 5 Automatic Detection of Attacks on Cryptographic Protocols: A Case Study
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    Chapter 6 METAL – A Tool for Extracting Attack Manifestations
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    Chapter 7 Flow-Level Traffic Analysis of the Blaster and Sobig Worm Outbreaks in an Internet Backbone
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    Chapter 8 A Learning-Based Approach to the Detection of SQL Attacks
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    Chapter 9 Masquerade Detection via Customized Grammars
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    Chapter 10 A Prevention Model for Algorithmic Complexity Attacks
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    Chapter 11 Detecting Malicious Code by Model Checking
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    Chapter 12 Improving the Efficiency of Misuse Detection
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    Chapter 13 Enhancing the Accuracy of Network-Based Intrusion Detection with Host-Based Context
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    Chapter 14 TCPtransform: Property-Oriented TCP Traffic Transformation
Attention for Chapter 6: METAL – A Tool for Extracting Attack Manifestations
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Citations

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6 Dimensions

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6 Mendeley
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Chapter title
METAL – A Tool for Extracting Attack Manifestations
Chapter number 6
Book title
Detection of Intrusions and Malware, and Vulnerability Assessment
Published by
Springer, Berlin, Heidelberg, July 2005
DOI 10.1007/11506881_6
Book ISBNs
978-3-54-026613-6, 978-3-54-031645-9
Authors

Ulf Larson, Emilie Lundin-Barse, Erland Jonsson

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 50%
Student > Bachelor 1 17%
Other 1 17%
Student > Doctoral Student 1 17%
Readers by discipline Count As %
Computer Science 6 100%

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