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Industrial Internet of Things Security: Protecting AI-Enabled Engineering Systems in Cloud and Edge Environments

Edited by Sunil Kumar Chawla, Edited by Neha Sharma, Edited by Ahmed A. Elngar, Edited by Prasenjit Chatterjee, Edited by P. Naga Srinivasu





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| book description |

The industrial landscape is changing rapidly, and so is global society. This change is driven by the growing adoption of the Industrial Internet of Things (IIoT) and artificial intelligence (AI) technologies. IIoT and AI are transforming the way industrial engineering is done, enabling new levels of automation, productivity, and efficiency. However, as IIoT and AI become more pervasive in the industrial world, they also offer new security risks that must be addressed to ensure the reliability and safety of critical systems. Industrial Internet of Things Security: Protecting AI-Enabled Engineering Systems in Cloud and Edge Environments provides a comprehensive guide to IIoT security, covering topics such as network architecture, risk management, data security, and compliance. It addresses the unique security challenges that the cloud and edge environments pose, providing practical guidance for securing IIoT networks in these contexts. It includes numerous real-world case studies and examples, providing readers with practical insights into how IIoT security and AI-enabled industrial engineering are being implemented in various industries. Best practices are emphasized for the readers to ensure the reliability, safety, and security of their systems while also learning the latest developments in IIoT security for AI-enabled industrial engineering systems in this rapidly evolving field. By offering step-by-step guidance for the implantation process along with best practices, this book becomes a valuable resource for practitioners and engineers in the areas of industrial engineering, IT, computer engineering, and anyone looking to secure their IIoT network against cyber threats.

| product details |



Normally shipped | Enquiries only
Publisher | Taylor & Francis Ltd
Published date | 28 Oct 2024
Language |
Format | Digital (delivered electronically)
Pages | 246
Dimensions | 0 x 0 x 0mm (L x W x H)
Weight | 0g
ISBN | 978-1-0401-4675-0
Readership Age |
BISAC | computers / artificial intelligence


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