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Cyber Security Cryptography and Machine Learning

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Cover of 'Cyber Security Cryptography and Machine Learning'

Table of Contents

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    Book Overview
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    Chapter 1 Efficient, Reusable Fuzzy Extractors from LWE
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    Chapter 2 GenFace: Improving Cyber Security Using Realistic Synthetic Face Generation
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    Chapter 3 Supervised Detection of Infected Machines Using Anti-virus Induced Labels
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    Chapter 4 Building Regular Registers with Rational Malicious Servers and Anonymous Clients
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    Chapter 5 On the Optimality of the Exponential Mechanism
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    Chapter 6 On Pairing Inversion of the Self-bilinear Map on Unknown Order Groups
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    Chapter 7 Brief Announcement: Anonymous Credentials Secure to Ephemeral Leakage
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    Chapter 8 The Combinatorics of Product Scanning Multiplication and Squaring
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    Chapter 9 Stylometric Authorship Attribution of Collaborative Documents
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    Chapter 10 A Distributed Investment Encryption Scheme: Investcoin
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    Chapter 11 Physical Layer Security over Wiretap Channels with Random Parameters
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    Chapter 12 Assisting Malware Analysis with Symbolic Execution: A Case Study
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    Chapter 13 Brief Announcement: A Consent Management Solution for Enterprises
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    Chapter 14 Brief Announcement: Privacy Preserving Mining of Distributed Data Using a Trusted and Partitioned Third Party
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    Chapter 15 Brief Announcement: A Technique for Software Robustness Analysis in Systems Exposed to Transient Faults and Attacks
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    Chapter 16 Symmetric-Key Broadcast Encryption: The Multi-sender Case
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    Chapter 17 A Supervised Auto-Tuning Approach for a Banking Fraud Detection System
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    Chapter 18 Scalable Attack Path Finding for Increased Security
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    Chapter 19 Learning Representations for Log Data in Cybersecurity
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    Chapter 20 Attack Graph Obfuscation
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    Chapter 21 Malware Triage Based on Static Features and Public APT Reports
Overall attention for this book and its chapters
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Mentioned by

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1 patent

Citations

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Title
Cyber Security Cryptography and Machine Learning
Published by
Springer, Cham, January 2017
DOI 10.1007/978-3-319-60080-2
ISBNs
978-3-31-960079-6, 978-3-31-960080-2
Editors

Shlomi Dolev, Sachin Lodha

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 100%
Readers by discipline Count As %
Engineering 1 100%

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