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Deep Learning Applications for Cyber Security

  • Mamoun Alazab
  • MingJian Tang
Book

Table of contents

  1. Front Matter
    Pages i-xx
  2. Mahmoud Nabil, Muhammad Ismail, Mohamed Mahmoud, Mostafa Shahin, Khalid Qaraqe, Erchin Serpedin
    Pages 73-102
  3. Kyle Millar, Adriel Cheng, Hong Gunn Chew, Cheng-Chew Lim
    Pages 103-126
  4. R. Vinayakumar, K. P. Soman, Prabaharan Poornachandran, Mamoun Alazab, Alireza Jolfaei
    Pages 127-149
  5. Amara Dinesh Kumar, Harish Thodupunoori, R. Vinayakumar, K. P. Soman, Prabaharan Poornachandran, Mamoun Alazab et al.
    Pages 151-173
  6. Tuan Anh Tang, Des McLernon, Lotfi Mhamdi, Syed Ali Raza Zaidi, Mounir Ghogho
    Pages 175-195
  7. Mofakharul Islam, Abdun Nur Mahmood, Paul Watters, Mamoun Alazab
    Pages 211-219
  8. Mofakharul Islam, Paul Watters, Abdun Nur Mahmood, Mamoun Alazab
    Pages 221-246

About this book

Introduction

Cybercrime remains a growing challenge in terms of security and privacy practices. Working together, deep learning and cyber security experts have recently made significant advances in the fields of intrusion detection, malicious code analysis and forensic identification. This book addresses questions of how deep learning methods can be used to advance cyber security objectives, including detection, modeling, monitoring and analysis of as well as defense against various threats to sensitive data and security systems. Filling an important gap between deep learning and cyber security communities, it discusses topics covering a wide range of modern and practical deep learning techniques, frameworks and development tools to enable readers to engage with the cutting-edge research across various aspects of cyber security. The book focuses on mature and proven techniques, and provides ample examples to help readers grasp the key points. 


Keywords

Big data Cyber crime Intrusion Detection Malware Analysis Image and Video detection Phishing Emails and Spams Detection Threat Intelligence and Cyber Criminology Adversarial Neural Networks Adversarial Machine Learning Deep neural networks Machine learning and cybersecurity

Editors and affiliations

  • Mamoun Alazab
    • 1
  • MingJian Tang
    • 2
  1. 1.Charles Darwin UniversityCasuarinaAustralia
  2. 2.Singtel OptusSydneyAustralia

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-030-13057-2
  • Copyright Information Springer Nature Switzerland AG 2019
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-030-13056-5
  • Online ISBN 978-3-030-13057-2
  • Series Print ISSN 1613-5113
  • Series Online ISSN 2363-9466
  • Buy this book on publisher's site
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