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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

  1. Altmetric Badge
    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
  5. Altmetric Badge
    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 4: Deep Learning-Based Detection of Electricity Theft Cyber-Attacks in Smart Grid AMI Networks
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Citations

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40 Mendeley
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Chapter title
Deep Learning-Based Detection of Electricity Theft Cyber-Attacks in Smart Grid AMI Networks
Chapter number 4
Book title
Deep Learning Applications for Cyber Security
Published by
Springer, Cham, January 2019
DOI 10.1007/978-3-030-13057-2_4
Book ISBNs
978-3-03-013056-5, 978-3-03-013057-2
Authors

Mahmoud Nabil, Muhammad Ismail, Mohamed Mahmoud, Mostafa Shahin, Khalid Qaraqe, Erchin Serpedin, Nabil, Mahmoud, Ismail, Muhammad, Mahmoud, Mohamed, Shahin, Mostafa, Qaraqe, Khalid, Serpedin, Erchin

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 40 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 9 23%
Student > Ph. D. Student 7 18%
Lecturer 5 13%
Student > Master 4 10%
Student > Doctoral Student 1 3%
Other 3 8%
Unknown 11 28%
Readers by discipline Count As %
Computer Science 13 33%
Unspecified 9 23%
Engineering 3 8%
Social Sciences 1 3%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Other 0 0%
Unknown 13 33%

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