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The implication of cyberattacks on big data and how to mitigate the risk

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	The implication of cyberattacks on big data and how to mitigate the risk/ by Fadele Ayotunde Alaba, Alvaro Rocha.
作者:	Alaba, Fadele Ayotunde.
其他作者:	Rocha, Álvaro.
出版者:	Cham :Springer Nature Switzerland : : 2025.,
面頁冊數:	ix, 111 p. :ill. (chiefly color), digital ; : 24 cm.;
Contained By:	Springer Nature eBook
標題:	Artificial Intelligence. -
電子資源:	https://doi.org/10.1007/978-3-031-88570-9
ISBN:	9783031885709

The implication of cyberattacks on big data and how to mitigate the risk
Alaba, Fadele Ayotunde.

The implication of cyberattacks on big data and how to mitigate the risk[electronic resource] /by Fadele Ayotunde Alaba, Alvaro Rocha. - Cham :Springer Nature Switzerland :2025. - ix, 111 p. :ill. (chiefly color), digital ;24 cm. - Information systems engineering and management,v. 393004-9598 ;. - Information systems engineering and management ;v. 1..

INTRODUCTION -- CYBER ATTACKS -- IDENTITY AND ACCESS MANAGEMENT WITH SYMMETRIC DATA ENCRYPTION AND NETWORK SEGMENTATION IN SOLVING CYBER ATTACKS ON BIG DATA -- RESULT IMPLEMENTATION AND DISCUSSION -- SUMMARY, CONCLUSION AND RECOMMENDATION.

This comprehensive book explores the challenges posed by cyberattacks on big data systems and their corresponding mitigation strategies. The book is organized into logical chapters, each focusing on specific aspects of the subject, ensuring clarity and depth in addressing the multifaceted nature of the problem. The introductory chapter provides a clear overview of the problem, introducing the prevalence of cyberattacks on big data systems, the motivation for addressing these risks, and the goals of the book. It also outlines the goals of the book, such as identifying vulnerabilities, evaluating mitigation strategies, and proposing integrated solutions. The second chapter provides a detailed examination of cyberattacks, emphasizing their implications for big data systems. It systematically categorizes tools and techniques available for mitigating these risks, including identity and access management (IAM), symmetric data encryption, network firewalls, IDPS, data loss prevention (DLP), SIEM, DDoS protection, and big data backup and recovery strategies. The book focuses on key mitigation techniques, such as IAM, encryption methods, network segmentation, firewalls, and intrusion detection systems. It also proposes an integrated cybersecurity model, combining these solutions for enhanced effectiveness against cyberattacks. The book also identifies research gaps and suggests areas for future research, such as adapting to emerging technologies and improving scalability in big data security frameworks. The book is a valuable resource for cybersecurity professionals, researchers, and practitioners aiming to address the unique challenges posed by cyberattacks on big data systems. The book aims to equip various professionals with the knowledge and strategies necessary to address the vulnerabilities associated with cyberattacks on big data environments.

ISBN: 9783031885709

Standard No.: 10.1007/978-3-031-88570-9doiSubjects--Topical Terms:

646849
Artificial Intelligence.

LC Class. No.: QA76.9.A25

Dewey Class. No.: 005.8

The implication of cyberattacks on big data and how to mitigate the risk
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520 $a This comprehensive book explores the challenges posed by cyberattacks on big data systems and their corresponding mitigation strategies. The book is organized into logical chapters, each focusing on specific aspects of the subject, ensuring clarity and depth in addressing the multifaceted nature of the problem. The introductory chapter provides a clear overview of the problem, introducing the prevalence of cyberattacks on big data systems, the motivation for addressing these risks, and the goals of the book. It also outlines the goals of the book, such as identifying vulnerabilities, evaluating mitigation strategies, and proposing integrated solutions. The second chapter provides a detailed examination of cyberattacks, emphasizing their implications for big data systems. It systematically categorizes tools and techniques available for mitigating these risks, including identity and access management (IAM), symmetric data encryption, network firewalls, IDPS, data loss prevention (DLP), SIEM, DDoS protection, and big data backup and recovery strategies. The book focuses on key mitigation techniques, such as IAM, encryption methods, network segmentation, firewalls, and intrusion detection systems. It also proposes an integrated cybersecurity model, combining these solutions for enhanced effectiveness against cyberattacks. The book also identifies research gaps and suggests areas for future research, such as adapting to emerging technologies and improving scalability in big data security frameworks. The book is a valuable resource for cybersecurity professionals, researchers, and practitioners aiming to address the unique challenges posed by cyberattacks on big data systems. The book aims to equip various professionals with the knowledge and strategies necessary to address the vulnerabilities associated with cyberattacks on big data environments.
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