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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 Using File Relationships in Malware Classification
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    Chapter 2 Understanding DMA Malware
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    Chapter 3 Large-Scale Analysis of Malware Downloaders
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    Chapter 4 Juxtapp: A Scalable System for Detecting Code Reuse among Android Applications
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    Chapter 5 ADAM: An Automatic and Extensible Platform to Stress Test Android Anti-virus Systems
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    Chapter 6 A Static, Packer-Agnostic Filter to Detect Similar Malware Samples
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    Chapter 7 Experiments with Malware Visualization
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    Chapter 8 Tracking Memory Writes for Malware Classification and Code Reuse Identification
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    Chapter 9 System-Level Support for Intrusion Recovery
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    Chapter 10 NetGator: Malware Detection Using Program Interactive Challenges
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    Chapter 11 SmartProxy: Secure Smartphone-Assisted Login on Compromised Machines
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    Chapter 12 BISSAM: Automatic Vulnerability Identification of Office Documents
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    Chapter 13 Self-organized Collaboration of Distributed IDS Sensors
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    Chapter 14 Shedding Light on Log Correlation in Network Forensics Analysis
Attention for Chapter 7: Experiments with Malware Visualization
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Citations

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Chapter title
Experiments with Malware Visualization
Chapter number 7
Book title
Detection of Intrusions and Malware, and Vulnerability Assessment
Published in
Lecture notes in computer science, July 2012
DOI 10.1007/978-3-642-37300-8_7
Book ISBNs
978-3-64-237299-5, 978-3-64-237300-8
Authors

Yongzheng Wu, Roland H. C. Yap

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 2 100%
Malaysia 1 50%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 300%
Researcher 2 100%
Student > Master 2 100%
Student > Bachelor 1 50%
Other 1 50%
Other 0 0%
Readers by discipline Count As %
Computer Science 13 650%

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