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Detection of Intrusions and Malware

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

Table of Contents

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    Book Overview
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    Chapter 1 Using Type Qualifiers to Analyze Untrusted Integers and Detecting Security Flaws in C Programs
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    Chapter 2 Using Static Program Analysis to Aid Intrusion Detection
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    Chapter 3 An SVM-Based Masquerade Detection Method with Online Update Using Co-occurrence Matrix
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    Chapter 4 Network–Level Polymorphic Shellcode Detection Using Emulation
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    Chapter 5 Detecting Unknown Network Attacks Using Language Models
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    Chapter 6 Using Labeling to Prevent Cross-Service Attacks Against Smart Phones
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    Chapter 7 Using Contextual Security Policies for Threat Response
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    Chapter 8 Detecting Self-mutating Malware Using Control-Flow Graph Matching
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    Chapter 9 Digital Forensic Reconstruction and the Virtual Security Testbed ViSe
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    Chapter 10 A Robust SNMP Based Infrastructure for Intrusion Detection and Response in Tactical MANETs
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    Chapter 11 A Fast Worm Scan Detection Tool for VPN Congestion Avoidance
Attention for Chapter 10: A Robust SNMP Based Infrastructure for Intrusion Detection and Response in Tactical MANETs
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Citations

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Chapter title
A Robust SNMP Based Infrastructure for Intrusion Detection and Response in Tactical MANETs
Chapter number 10
Book title
Detection of Intrusions and Malware & Vulnerability Assessment
Published by
Springer, Berlin, Heidelberg, July 2006
DOI 10.1007/11790754_10
Book ISBNs
978-3-54-036014-8, 978-3-54-036017-9
Authors

Marko Jahnke, Jens Tölle, Sascha Lettgen, Michael Bussmann, Uwe Weddige, Jahnke, Marko, Tölle, Jens, Lettgen, Sascha, Bussmann, Michael, Weddige, Uwe

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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 %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 100%
Other 1 50%
Readers by discipline Count As %
Computer Science 3 150%

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