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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 MAMBO – V: Dynamic Side-Channel Leakage Analysis on RISC – V
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    Chapter 2 The Finger in the Power: How to Fingerprint PCs by Monitoring Their Power Consumption
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    Chapter 3 PwrLeak : Exploiting Power Reporting Interface for Side-Channel Attacks on AMD SEV
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    Chapter 4 Madvex : Instrumentation-Based Adversarial Attacks on Machine Learning Malware Detection
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    Chapter 5 Honey, I Chunked the Passwords: Generating Semantic Honeywords Resistant to Targeted Attacks Using Pre-trained Language Models
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    Chapter 6 White-Box Concealment Attacks Against Anomaly Detectors for Cyber-Physical Systems
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    Chapter 7 A Security Analysis of CNC Machines in Industry 4.0
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    Chapter 8 A Deep Dive into the VirusTotal File Feed
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    Chapter 9 Attackers as Instructors: Using Container Isolation to Reduce Risk and Understand Vulnerabilities
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    Chapter 10 Extended Abstract: Towards Reliable and Scalable Linux Kernel CVE Attribution in Automated Static Firmware Analyses
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    Chapter 11 Divak: Non-invasive Characterization of Out-of-Bounds Write Vulnerabilities
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    Chapter 12 CEFI : Command Execution Flow Integrity for Embedded Devices
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    Chapter 13 Untangle : Aiding Global Function Pointer Hijacking for Post-CET Binary Exploitation
Attention for Chapter 5: Honey, I Chunked the Passwords: Generating Semantic Honeywords Resistant to Targeted Attacks Using Pre-trained Language Models
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Readers on

mendeley
3 Mendeley
Summary
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Chapter title
Honey, I Chunked the Passwords: Generating Semantic Honeywords Resistant to Targeted Attacks Using Pre-trained Language Models
Chapter number 5
Book title
Detection of Intrusions and Malware, and Vulnerability Assessment
Published by
Springer, Cham, January 2023
DOI 10.1007/978-3-031-35504-2_5
Book ISBNs
978-3-03-135503-5, 978-3-03-135504-2
Authors

Yu, Fangyi, Martin, Miguel Vargas

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 1 33%
Unknown 2 67%
Readers by discipline Count As %
Computer Science 1 33%
Unknown 2 67%

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