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Cybersecurity and Data Science Innovations for Sustainable Development of HEICC

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  • Дата: 19-12-2024, 05:40
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Название: Cybersecurity and Data Science Innovations for Sustainable Development of HEICC: Healthcare, Education, Industry, Cities, and Communities
Автор: Thangavel Murugan, W. Jai Singh
Издательство: CRC Press
Год: 2025
Страниц: 496
Язык: английский
Формат: pdf (true), epub
Размер: 35.0 MB

Cybersecurity and Data Science Innovations for Sustainable Development of HEICC: Healthcare, Education, Industry, Cities, and Communities brings together a collection of chapters that explore the intersection of cybersecurity, Data Science, and sustainable development across key sectors: healthcare, education, industry, cities, and communities. It delves into cybersecurity advancements and examines how innovations in cybersecurity are shaping the landscape of healthcare, education, industry, and urban environments. Data Science advancements take center stage, showcasing the transformative power of data analytics in improving outcomes across HEICC sectors. Whether it’s optimizing resource allocation in healthcare, protecting patient privacy, personalizing learning experiences in education, enhancing efficiency in industry, or fostering sustainable development in cities and communities, Data Science offers unprecedented opportunities for innovation and progress.

In the healthcare sector, cybersecurity is indispensable for safeguarding sensitive patient information, ensuring the integrity of medical records, and protecting against cyber threats that could compromise patient safety. Furthermore, data science plays a crucial role in healthcare by enabling predictive analytics for early disease detection, personalized treatment plans, and optimizing healthcare delivery systems for better patient outcomes.

In education, cybersecurity measures are essential for protecting student and faculty data, securing online learning platforms, and preventing cyber-attacks that disrupt educational processes. Data science, on the other hand, empowers educators with tools for personalized learning, adaptive assessments, and data-driven decision-making to enhance the quality of education and student success rates.

In the industrial sector, cybersecurity is imperative for safeguarding proprietary information, trade secrets, and critical infrastructure from cyber threats that could disrupt operations or compromise industrial processes. Data Science innovations enable predictive maintenance, supply chain optimization, and real-time monitoring of industrial systems, leading to increased efficiency, reduced downtime, and sustainable resource management.

In urban environments, cybersecurity is vital for protecting smart city infrastructure, IoT devices, and public services from cyber-attacks that could disrupt essential services or compromise citizen safety. Data science plays a pivotal role in urban planning, traffic management, energy optimization, and resource allocation, fostering sustainable development and improving the quality of life for residents.

The significance of Machine Learning in cybersecurity is further underscored by its capacity to handle the complexity and scale of modern cyber threats. Traditional rule-based systems often struggle to keep pace with the rapidly evolving tactics employed by cybercriminals. Machine Learning, on the other hand, excels in adapting to new and previously unseen threats, making it a valuable asset in the ongoing battle against cybercrime. Beyond its technical prowess, the application of Machine Learning in cybersecurity has profound social implications. As our reliance on digital technologies continues to grow, ensuring the security and privacy of individuals becomes a collective responsibility. Machine Learning algorithms contribute to this collective defense by providing scalable and efficient means of detecting, preventing, and mitigating cyber threats.

Key points:

Healthcare system security and privacy, protecting patient data, and enabling development of novel healthcare solutions.
Securing educational data, improving online learning security, and harnessing data analytics for tailored education approaches.
Manufacturing, finance, and transportation. Diving into critical infrastructure security, detecting and mitigating cyber threats, and using data‑driven insights for better industrial operations.
Helping cities and communities develop sustainably, smart city security challenges, data privacy in urban environments, data analytics for urban planning, and community cybersecurity awareness.

This book serves as a comprehensive guide for researchers, practitioners, policymakers, and stakeholders navigating the complex landscape of cybersecurity and Data Science in the pursuit of sustainable development across HEICC domains.

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