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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 Malrec: Compact Full-Trace Malware Recording for Retrospective Deep Analysis
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    Chapter 2 MemScrimper: Time- and Space-Efficient Storage of Malware Sandbox Memory Dumps
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    Chapter 3 Spearphishing Malware: Do We Really Know the Unknown?
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    Chapter 4 Honey, I Shrunk Your App Security: The State of Android App Hardening
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    Chapter 5 GuardION: Practical Mitigation of DMA-Based Rowhammer Attacks on ARM
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    Chapter 6 BINARM: Scalable and Efficient Detection of Vulnerabilities in Firmware Images of Intelligent Electronic Devices
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    Chapter 7 Update State Tampering: A Novel Adversary Post-compromise Technique on Cyber Threats
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    Chapter 8 Evasive Malware via Identifier Implanting
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    Chapter 9 On the Weaknesses of Function Table Randomization
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    Chapter 10 FraudBuster: Temporal Analysis and Detection of Advanced Financial Frauds
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    Chapter 11 No Random, No Ransom: A Key to Stop Cryptographic Ransomware
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    Chapter 12 Hidden in Plain Sight: Filesystem View Separation for Data Integrity and Deception
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    Chapter 13 Knockin’ on Trackers’ Door: Large-Scale Automatic Analysis of Web Tracking
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    Chapter 14 JaSt: Fully Syntactic Detection of Malicious (Obfuscated) JavaScript
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    Chapter 15 Bytecode Corruption Attacks Are Real—And How to Defend Against Them
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    Chapter 16 ELISA: ELiciting ISA of Raw Binaries for Fine-Grained Code and Data Separation
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    Chapter 17 Symbolic Deobfuscation: From Virtualized Code Back to the Original
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    Chapter 18 Extended Abstract: Toward Systematically Exploring Antivirus Engines
Overall attention for this book and its chapters
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Mentioned by

1 news outlet
4 tweeters


3 Dimensions

Readers on

2 Mendeley
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Detection of Intrusions and Malware, and Vulnerability Assessment
Published by
Springer International Publishing, June 2018
DOI 10.1007/978-3-319-93411-2
978-3-31-993410-5, 978-3-31-993411-2

Cristiano Giuffrida, Sébastien Bardin, Gregory Blanc

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

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 > Master 1 50%
Unknown 1 50%
Readers by discipline Count As %
Computer Science 1 50%
Unknown 1 50%