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Deep Learning Applications for Cyber Security

Overview of attention for book
Cover of 'Deep Learning Applications for Cyber Security'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Adversarial Attack, Defense, and Applications with Deep Learning Frameworks
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    Chapter 2 Intelligent Situational-Awareness Architecture for Hybrid Emergency Power Systems in More Electric Aircraft
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    Chapter 3 Deep Learning in Person Re-identification for Cyber-Physical Surveillance Systems
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    Chapter 4 Deep Learning-Based Detection of Electricity Theft Cyber-Attacks in Smart Grid AMI Networks
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    Chapter 5 Using Convolutional Neural Networks for Classifying Malicious Network Traffic
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    Chapter 6 DBD: Deep Learning DGA-Based Botnet Detection
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    Chapter 7 Enhanced Domain Generating Algorithm Detection Based on Deep Neural Networks
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    Chapter 8 Intrusion Detection in SDN-Based Networks: Deep Recurrent Neural Network Approach
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    Chapter 9 SeqDroid: Obfuscated Android Malware Detection Using Stacked Convolutional and Recurrent Neural Networks
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    Chapter 10 Forensic Detection of Child Exploitation Material Using Deep Learning
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    Chapter 11 Toward Detection of Child Exploitation Material: A Forensic Approach
Attention for Chapter 8: Intrusion Detection in SDN-Based Networks: Deep Recurrent Neural Network Approach
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Citations

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54 Dimensions

Readers on

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132 Mendeley
Summary Dimensions citations
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Chapter title
Intrusion Detection in SDN-Based Networks: Deep Recurrent Neural Network Approach
Chapter number 8
Book title
Deep Learning Applications for Cyber Security
Published by
Springer, Cham, January 2019
DOI 10.1007/978-3-030-13057-2_8
Book ISBNs
978-3-03-013056-5, 978-3-03-013057-2
Authors

Tuan Anh Tang, Des McLernon, Lotfi Mhamdi, Syed Ali Raza Zaidi, Mounir Ghogho, Tang, Tuan Anh, McLernon, Des, Mhamdi, Lotfi, Zaidi, Syed Ali Raza, Ghogho, Mounir

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 132 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 132 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 18 14%
Student > Ph. D. Student 16 12%
Lecturer 9 7%
Researcher 6 5%
Student > Doctoral Student 6 5%
Other 25 19%
Unknown 52 39%
Readers by discipline Count As %
Computer Science 54 41%
Engineering 12 9%
Unspecified 3 2%
Business, Management and Accounting 3 2%
Earth and Planetary Sciences 1 <1%
Other 3 2%
Unknown 56 42%

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