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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 Driving in the Cloud: An Analysis of Drive-by Download Operations and Abuse Reporting
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    Chapter 2 ProVeX : Detecting Botnets with Encrypted Command and Control Channels
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    Chapter 3 Exploring Discriminatory Features for Automated Malware Classification
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    Chapter 4 PeerRush: Mining for Unwanted P2P Traffic
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    Chapter 5 Early Detection of Outgoing Spammers in Large-Scale Service Provider Networks
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    Chapter 6 PreparedJS: Secure Script-Templates for JavaScript
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    Chapter 7 Securing Legacy Firefox Extensions with SENTINEL
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    Chapter 8 Weaknesses in Defenses against Web-Borne Malware
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    Chapter 9 SMS-Based One-Time Passwords: Attacks and Defense
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    Chapter 10 Towards the Protection of Industrial Control Systems – Conclusions of a Vulnerability Analysis of Profinet IO
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    Chapter 11 HeapSentry: Kernel-Assisted Protection against Heap Overflows
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    Chapter 12 Preventing Backdoors in Server Applications with a Separated Software Architecture
Overall attention for this book and its chapters
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Mentioned by

patent
2 patents

Citations

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4 Dimensions

Readers on

mendeley
53 Mendeley
Summary Patents Dimensions citations
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Title
Detection of Intrusions and Malware, and Vulnerability Assessment
Published by
Springer Berlin Heidelberg, July 2013
DOI 10.1007/978-3-642-39235-1
ISBNs
978-3-64-239234-4, 978-3-64-239235-1
Editors

Rieck, Konrad, Stewin, Patrick, Seifert, Jean-Pierre

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 53 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 4%
Unknown 51 96%
Readers by discipline Count As %
Computer Science 1 2%
Materials Science 1 2%
Unknown 51 96%

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