机读格式显示(MARC)
- 000 02902cam a2200361 i 4500
- 008 240402s2024 enka b 001 0 eng
- 020 __ |a 9781032259574 |q (hardback)
- 020 __ |a 9781032259581 |q (paperback)
- 020 __ |z 9781003285854 |q (ebook)
- 040 __ |a DLC |b eng |e rda |c DLC |d OCLCF |d OCLCO
- 050 00 |a HD38.7 |b .C93 2024
- 082 00 |a 658.4/72 |2 23/eng/20230719
- 245 00 |a Cyber security and business intelligence : |b innovations and machine learning for cyber risk management / |c edited by Mohammad Zoynul Abedin and Petr Hajek.
- 260 __ |a Abingdon, Oxon ; |a New York, NY : |b Routledge, |c 2024.
- 300 __ |a xii, 222 pages : |b illustrations ; |c 24 cm.
- 336 __ |a text |b txt |2 rdacontent
- 337 __ |a unmediated |b n |2 rdamedia
- 338 __ |a volume |b nc |2 rdacarrier
- 490 0_ |a Routledge studies in innovation, organizations and technology
- 504 __ |a Includes bibliographical references and index.
- 520 __ |a "To cope with the competitive worldwide marketplace, organizations rely on business intelligence to an increasing extent. Cyber security is an inevitable practice to protect the entire business sector and its customer. This book presents the significance and application of cyber security for safeguarding organizations, individuals' personal information and government. The book provides both practical and managerial implications of cyber security that also supports business intelligence and discusses the latest innovations in cyber security. It offers a roadmap to master's degree students and Ph.D. researchers for cyber security analysis in order to minimize the cyber security risk and protect customers from cyber-attack. The book also introduces the most advanced and novel machine learning techniques including, but not limited to, Support Vector Machine, Neural Networks, Extreme Learning Machine, Ensemble Learning, and Deep Learning Approaches, with a goal to apply those on cyber risk management datasets. It will also leverage real-world financial instances to practice business product modelling and data analysis. The contents of this book will be useful for a wide audience who are involved in managing network systems, data security, data forecasting, cyber risk modelling, fraudulent credit risk detection, portfolio management, and data regulatory bodies. It will be particularly beneficial to academics as well as practitioners who are looking to protect their IT system, reduce data breaches and cyber-attack vulnerabilities"-- |c Provided by publisher.
- 650 _0 |a Business intelligence.
- 650 _0 |a Computer security.
- 650 _0 |a Risk management.
- 650 _0 |a Computer networks |x Security measures.
- 650 _0 |a Computer crimes |x Prevention.
- 700 1_ |a Abedin, Mohammad Zoynul, |e editor.
- 700 1_ |a Hajek, Petr, |e editor.