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Future-proof your digital infrastructure with this essential book, which provides a comprehensive exploration of both traditional and advanced machine and deep learning models to implement resilient and intelligent intrusion detection systems for securing complex cloud-IoT environments.
The rapid growth of cloud computing and the Internet of Things has transformed industry by enabling real-time data collection, processing, and automation. However, this increasing interconnectivity also introduces significant security challenges, including data breaches, unauthorized access, and cyber threats. Ensuring the security and privacy of cloud-IoT environments requires advanced intrusion detection mechanisms, privacy-preserving strategies, and efficient resource management. This book explores various advanced methods to achieve these goals, including machine and deep learning models, to protect cloud-IoT systems against cyber threats. This book covers both traditional and advanced techniques to implement intrusion detection systems and provides detailed comparative analysis. By offering practical insights, readers will gain a deeper understanding of how to effectively implement intelligent security solutions, ensuring resilience, privacy, and protection against evolving cyber threats in cloud-IoT environments.
Readers will find the volume:
Audience
Research scholars and industry professionals in information technology, artificial intelligence and cybersecurity looking to innovate cybersecurity for cloud computing and IoT.
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