
Malware Detection on Smart Wearables Using Machine Learning Algorithms
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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.
Dr. Fadele Ayotunde Alaba is a distinguished academic and researcher with extensive experience in the field of Computer Science. Currently, he serves as a Full-Time Lecturer in the Department of Computer Science at the Federal College of Education, Zaria, Nigeria, a position he has held since 2010. His academic journey includes significant roles such as Research Assistant at the University of Malaya from 2017 to 2019 and Lecturer at the Federal Polytechnic Bauchi, Nigeria. Dr. Alaba holds multiple advanced degrees in computer science, showcasing his dedication to continuous learning and expert development. He earned his second Ph.D. in Computer Science, specializing in Blockchain, from the International University of Bamenda (2020-2023) and his first Ph.D. in Computer Science from the University of Malaya (2016-2019). Additionally, he has a Master of Computer Science from Ahmadu Bello University, Zaria (2011-2014), and a Post Graduate Diploma in Education (PGDE) from Usman Danfodio University, Sokoto (2011-2012). He began his academic pursuit with a Bachelor of Computer Science (First Class Honours) from Nasarawa State University, Keffi (2004-2008). Dr. Alaba's research interests are diverse and cutting-edge, including Big Data, Cloud Computing, the Internet of Things (IoT), Network Security, Blockchain, and Smart Contracts Security. His technical expertise encompasses working with Hadoop MapReduce, Contiki, and Cooja IoT Simulators, as well as data mining, machine learning, and statistical analysis software such as R, SPSS, SAS, and Weka. He has contributed significantly to the academic community through his research publications in high-impact journals, with over 2000 citations. Notable among his works is the "Adaptive Stochastic Conjugate Gradient Optimization for Backpropagation Neural Networks," published in IEEE Access (2024) and various book chapters in Springer Nature Switzerland. His publications address crucial topics like AIoT-enabled smart grids, sustainable transportation through IoT, and smart contracts security. Dr. Alaba has supervised numerous master's theses on subjects ranging from machine learning algorithms for intrusion detection in smart wearable devices to the impact of financial planning on the profitability of small-scale firms. He is also a frequent speaker at national and international conferences, sharing his insights on research and publication practices. In recognition of his contributions, Dr. Alaba has received several awards, including the 2019 JNCA Best Survey Paper Award and the Best Presenter at the Annual Faculty of Computer Science and Information Technology Postgraduate Symposium in Malaysia (2017). He was also the Best Graduating Student from the Department of Mathematical Sciences, Computer Science Unit, Nasarawa State University, Keffi, in 2007/2008. Dr. Alaba is serving as a consultant on the Editorial Board of Standardization at the TeTFund Center of Excellence for Technology Enhanced Learning since 2023. His commitment to academic excellence and innovative research continues to make significant impacts in the fields of computer science and technology.
Produktdetails
- Studies in Systems, Decision and Control 549
- Verlag: Springer / Springer Nature Switzerland / Springer, Berlin
- Artikelnr. des Verlages: 978-3-031-65932-4
- Seitenzahl: 148
- Erscheinungstermin: 4. Oktober 2024
- Englisch
- Abmessung: 241mm x 160mm x 14mm
- Gewicht: 338g
- ISBN-13: 9783031659324
- ISBN-10: 3031659325
- Artikelnr.: 70980174
Herstellerkennzeichnung
Springer-Verlag GmbH
Tiergartenstr. 17
69121 Heidelberg
ProductSafety@springernature.com
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