Deep learning applications for cyber security. ([2019])

• Record Type: Book
• Further Information: Note: Mamoun Alazeb, MingJian Tang, editors.
• Editors: Alazab, Mamoun; Tang, MingJian
• Contents: Adversarial Attack, Defense, and Applications with Deep Learning Frameworks -- Intelligent Situational-Awareness Architecture for Hybrid Emergency Power Systems in More Electric Aircraft -- Deep Learning in Person Re-identication for Cyber-Physical Surveillance Systems -- Deep Learning-based Detection of Electricity Theft Cyber-attacks in Smart Grid AMI Networks -- Using Convolutional Neural Networks for Classifying Malicious Network Traffic -- DBD: Deep Learning DGA-based Botnet Detection -- Enhanced Domain Generating Algorithm Detection Based on Deep Neural Networks -- Intrusion Detection in SDN-based Networks: Deep Recurrent Neural Network Approach -- SeqDroid: Obfuscated Android Malware Detection using Stacked Convolutional and Recurrent Neural Networks -- Forensic Detection of Child Exploitation Material using Deep Learning -- Toward Detection of Child Exploitation Material: A Forensic Approach.
• Publisher Details: Cham, Switzerland : Springer
• Publication Date: 2019
• Copyright Date: 2019
• Extent: 1 online resource (xx, 246 pages), illustrations
• Subjects: 005.8; Computer security
• Languages: English
• ISBNs: 9783030130572; 3030130576; 9783030130565; 3030130568; 9783030130589; 3030130584; 9783030130596; 3030130592
• Notes: Note: Includes bibliographical references.; Note: Description based on online resource (SpringerLink, viewed October 17, 2019).
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.