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Malware Detection on Smart Wearables Using Machine Learning Algorithms de Fadele Ayotunde Alaba

Malware Detection on Smart Wearables Using Machine Learning Algorithms: Studies in Systems, Decision and Control, cartea 549

Autor Fadele Ayotunde Alaba, Alvaro Rocha
en Limba Engleză Hardback – 4 oct 2024
This book digs into the important confluence of cybersecurity and big data, providing insights into the ever-changing environment of cyber threats and solutions to protect these enormous databases. In the modern digital era, large amounts of data have evolved into the vital organs of businesses, providing the impetus for decision-making, creativity, and a competitive edge. Cyberattacks pose a persistent danger to this important resource since they can result in data breaches, financial losses, and harm to an organization's brand.
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Specificații

ISBN-13: 9783031659324
ISBN-10: 3031659325
Pagini: 148
Ilustrații: Approx. 150 p.
Dimensiuni: 160 x 241 x 14 mm
Greutate: 0.34 kg
Ediția:2024
Editura: Springer
Colecția Studies in Systems, Decision and Control
Seria Studies in Systems, Decision and Control

Locul publicării:Cham, Switzerland

Cuprins

1. Introduction.- 2.Security Challenges of Wearable Technology.- 3. Machine Learning Algorithms On Malware Detection Against Smart Wearable Devices.- 4.Implementation Results.- 5. Conclusions, Future Directions, and Recommendations.

Notă biografică

Fadele Ayotunde Alaba (PhD) is a Nigerian computer scientist, academic, and internationally published researcher with over a decade of experience in teaching, research, and academic leadership. He is a full-time lecturer in the Department of Computer Science at the Federal University of Education, Zaria, Nigeria, where he has held several strategic administrative positions, including Head of Department and Director of the Information and Communication Technology (ICT) Unit. He is also a visiting lecturer at St. Francis of Assisi College of Education, Wusasa, Zaria. Currently, Dr. Fadele is a post-doctoral fellow at the Instituto de Estudos e Desenvolvemento de Galicia (IDEGA), Spain. Dr. Fadele holds multiple advanced qualifications in Computer Science, including doctoral degrees from the University of Malaya, Malaysia, and the International University, Bamenda. His academic training and research focus span cybersecurity, Internet of Things (IoT), artificial intelligence, blockchain technology, smart contracts security, big data analytics, and cloud computing. Dr. Ilesanmi G. Ajibola is a distinguished academic at the Federal University of Education, Zaria, Nigeria. He holds a Ph.D. in Systematic Theology from Duquesne University, Pittsburgh, Pa. USA, where he had also served as a teaching assistant and course instructor. For five years, he is been the director of TETFund Centre of Excellence for Technology Enhanced Learning at the institution. His research interests encompass educational diversification, systematic theology, and exploring the intersection of digital technology and educational practices in the humanities. Dr. Ajibola has authored several books, articles, and papers addressing religious education and ICT integration. He advocates for strategic investments in ICT infrastructure, mandatory training for educators and students, with the aim to bridge the digital divide and promote equitable access to educational technologies.

Textul de pe ultima copertă

This book digs into the important confluence of cybersecurity and big data, providing insights into the ever-changing environment of cyber threats and solutions to protect these enormous databases. In the modern digital era, large amounts of data have evolved into the vital organs of businesses, providing the impetus for decision-making, creativity, and a competitive edge. Cyberattacks pose a persistent danger to this important resource since they can result in data breaches, financial losses, and harm to an organization's brand.

Caracteristici

Includes machine learning algorithms to Malware on smart wearers Provides insights into the ever-changing environment of cyber threats and solutions to protect these enormous databases Covers current trends and issues in cybersecurity and gives forward-looking views into the future of big data security