Articles liés à Deep Learning Applications for Cyber Security
Synopsis
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.
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À propos de l?auteur
Mamoun Alazab is an Associate Professor in the College of Engineering, IT and Environment at Charles Darwin University, Australia. He received his PhD degree in Computer Science from the Federation University of Australia, School of Science, Information Technology and Engineering. He is a cyber security researcher and practitioner with industry and academic experience. Alazab's research is multidisciplinary that focuses on cyber security and digital forensics of computer systems with a focus on cybercrime detection and prevention. He has more than 100 research papers. He delivered many invited and keynote speeches, 22 events in 2018 alone. He convened and chaired more than 50 conferences and workshops. He works closely with government and industry on many projects. He is an editor on multiple editorial boards of international journals and a Senior Member of the IEEE.
MingJian Tang is a Senior Data Scientist at Singtel Optus, Australia. He received his PhD degree in Computer Science from La Trobe University, Melbourne, Australia, in 2009. Previously he was a Data Scientist at the Commonwealth Bank of Australia. He has participated in several industry-based research projects including unsupervised fraud detection, unstructured threat intelligence, cyber risk analysis and quantification, and big data analysis.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
- ÉditeurSpringer Nature Switzerland AG
- Date d'édition2020
- ISBN 10 3030130592
- ISBN 13 9783030130596
- ReliureBroché
- Langueanglais
- Nombre de pages246
- ÉditeurAlazab Mamoun, Tang MingJian
- Coordonnées du fabricantnon disponible
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Deep Learning Applications for Cyber Security
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Springer International Publishing, 2020
ISBN 10 : 3030130592
ISBN 13 : 9783030130596
Neuf
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Bridges two popular areas (Deep Learning and Cyber Security) with self-contained materialFully self-contained with ample practical examplesProvides wide coverage of popular Deep Learning tools and frameworks enabling the readers . N° de réf. du vendeur 458532912
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Deep Learning Applications for Cyber Security
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ISBN 10 : 3030130592
ISBN 13 : 9783030130596
Neuf
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. N° de réf. du vendeur 9783030130596
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Deep Learning Applications for Cyber Security
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ISBN 13 : 9783030130596
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 268 pp. Englisch. N° de réf. du vendeur 9783030130596
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Deep Learning Applications for Cyber Security
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Taschenbuch. Etat : Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 268 pp. Englisch. N° de réf. du vendeur 9783030130596
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Deep Learning Applications for Cyber Security (Advanced Sciences and Technologies for Security Applications)
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Paperback. Etat : New. New. book. N° de réf. du vendeur ERICA80030301305926
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