โ Scribed by Mamoun Alazab, MingJian Tang
No coin nor oath required. For personal study only.
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.
Front Matter ....Pages i-xx
Adversarial Attack, Defense, and Applications with Deep Learning Frameworks (Zhizhou Yin, Wei Liu, Sanjay Chawla)....Pages 1-25
Intelligent Situational-Awareness Architecture for Hybrid Emergency Power Systems in More Electric Aircraft (Gihan J. Mendis, Mohasinina Binte Kamal, Jin Wei)....Pages 27-44
Deep Learning in Person Re-identification for Cyber-Physical Surveillance Systems (Lin Wu, Brian C. Lovell, Yang Wang)....Pages 45-72
Deep Learning-Based Detection of Electricity Theft Cyber-Attacks in Smart Grid AMI Networks (Mahmoud Nabil, Muhammad Ismail, Mohamed Mahmoud, Mostafa Shahin, Khalid Qaraqe, Erchin Serpedin)....Pages 73-102
Using Convolutional Neural Networks for Classifying Malicious Network Traffic (Kyle Millar, Adriel Cheng, Hong Gunn Chew, Cheng-Chew Lim)....Pages 103-126
DBD: Deep Learning DGA-Based Botnet Detection (R. Vinayakumar, K. P. Soman, Prabaharan Poornachandran, Mamoun Alazab, Alireza Jolfaei)....Pages 127-149
Enhanced Domain Generating Algorithm Detection Based on Deep Neural Networks (Amara Dinesh Kumar, Harish Thodupunoori, R. Vinayakumar, K. P. Soman, Prabaharan Poornachandran, Mamoun Alazab et al.)....Pages 151-173
Intrusion Detection in SDN-Based Networks: Deep Recurrent Neural Network Approach (Tuan Anh Tang, Des McLernon, Lotfi Mhamdi, Syed Ali Raza Zaidi, Mounir Ghogho)....Pages 175-195
SeqDroid: Obfuscated Android Malware Detection Using Stacked Convolutional and Recurrent Neural Networks (William Younghoo Lee, Joshua Saxe, Richard Harang)....Pages 197-210
Forensic Detection of Child Exploitation Material Using Deep Learning (Mofakharul Islam, Abdun Nur Mahmood, Paul Watters, Mamoun Alazab)....Pages 211-219
Toward Detection of Child Exploitation Material: A Forensic Approach (Mofakharul Islam, Paul Watters, Abdun Nur Mahmood, Mamoun Alazab)....Pages 221-246
Computer Science; Big Data; Cybercrime; Mathematical Models of Cognitive Processes and Neural Networks; Security Science and Technology
๐ SIMILAR VOLUMES
"This book explores the use of machine learning and deep learning applications in the areas of cyber security and cyber-attack handling mechanisms"--
As the advancement of technology continues, cyber security continues to play a significant role in today's world. With society becoming more dependent on the internet, new opportunities for virtual attacks can lead to the exposure of critical information. Machine and deep learning techniques to prev
<p><span>Without mathematics no science would survive. This especially applies to the engineering sciences which highly depend on the applications of mathematics and mathematical tools such as optimization techniques, finite element methods, differential equations, fluid dynamics, mathematical model
<div>The three-volume proceedings set LNCS 13655,13656 and 13657 constitutes the refereed</div><div>proceedings of the 4th International Conference on Machine Learning for Cyber Security, ML4CS 2022, which taking place during December 2-4, 2022, held in Guangzhou, China.</div><div></div><div>The 100
The three-volume proceedings set LNCS 13655,13656 and 13657 constitutes the refereed<div>proceedings of the 4th International Conference on Machine Learning for Cyber Security, ML4CS 2022, which taking place during December 2-4, 2022, held in Guangzhou, China.</div><div> </div><div>The 100 full pape
<p>This book shows how machine learning (ML) methods can be used to enhance cyber security operations, including detection, modeling, monitoring as well as defense against threats to sensitive data and security systems. Filling an important gap between ML and cyber security communities, it discusses