Yazan Otoum | Heart Disease | Best Researcher Award

Education:

Dr. Yazan Otoum holds a Ph.D. in Electrical and Computer Engineering from the University of Ottawa, Canada, where he focused on developing AI-based intrusion detection systems to enhance the security of the Internet of Things (IoT). He earned his M.Sc. in Networks Engineering and Management from DePaul University in the USA in 2009 and a B.Sc. in Software Engineering from Philadelphia University in Jordan in 2006. Dr. Otoum’s diverse educational background equips him with a robust understanding of network security, software development, and emerging technologies, allowing him to contribute significantly to research and teaching in his field.

Professional Experience:

 

Dr. Yazan Otoum is an Assistant Professor of Cybersecurity at Algoma University in Brampton, Ontario, Canada, since 2024. He teaches graduate courses such as Data Structures I, Data Structures II, and Introduction to Cybersecurity. Prior to this, he was a part-time professor at the University of Ottawa and Algonquin College, where he instructed courses in data structures, algorithms, and digital forensics. Dr. Otoum has a solid background in research and teaching, having guided master’s students in developing security frameworks focused on IoT and Federated Learning during his tenure as a Research Assistant at the University of Ottawa. Previously, he was a lecturer at Majmaah University in Saudi Arabia, where he initiated the “Digital Citizenship” project under Saudi Vision 2030, enhancing digital literacy and responsible technology use. His early career included significant roles in system administration for educational projects in Jordan, where he managed platforms serving over 2 million users and led efforts in disaster recovery and cybersecurity analysis.

 

Honours and Awards:

 

Dr. Yazan Otoum has received several accolades for his contributions to cybersecurity education and community engagement. In 2023, he was awarded the Cybersecurity Career Mentor Badge by the EC-Council, recognizing his efforts in mentoring aspiring cybersecurity professionals. He also earned the Cisco Instructor 5 Years of Service Badge in 2019 for his impactful teaching in the Cisco Networking Academy. Notably, in 2018, he received an Award and Certificate of Appreciation from “Saudi Vision 2030” for his role in the “Digital Citizenship” project, which won the best project award. His other recognitions include multiple certificates of appreciation from Majma’ah University for his significant contributions to ABET accreditation, organizing a nationwide robotics competition, and conducting a national cybersecurity boot camp. Additionally, he was acknowledged by the University of Jadara in 2011 for delivering an impactful presentation on eLearning in education.

Graduate Co-Supervision:

Dr. Yazan Otoum has supervised several innovative research projects in the field of cybersecurity and healthcare technology. In 2023, he guided Pratish Pushparaj in developing an Intrusion Detection System Model using LLaMA 2 with generative dataset augmentation. Chaosheng Hu’s project focused on heart disease prediction through federated learning and blockchain integration, while Siddhant Tiwari explored a differential privacy-driven framework for enhancing heart disease prediction. Navya Gottimukkala investigated the application of machine learning in metaverse security. Earlier, in the 2022-2023 academic year, Paritosh Singh worked on deep collaborative learning for robust healthcare security. Dr. Otoum also supervised Yue Wan’s research on a federated transfer learning-based IDS for the Internet of Medical Things (IoMT) and Sai Yadlapalli’s framework for securing IoT through federated transfer learning during the 2020-2021 academic year.

Graduate Courses:

Dr. Yazan Otoum’s teaching portfolio includes advanced topics in cybersecurity, focusing on the integration of machine learning and artificial intelligence for practical applications. He covers wireless ad-hoc networking and the innovative frameworks of software-defined networks (SDN) and cloud computing, which are essential for modern network management. Additionally, his courses explore multimedia communication, emphasizing the importance of secure data transmission in diverse formats. Dr. Otoum also introduces students to deep learning (DL) and reinforcement learning (RL), equipping them with the skills needed to leverage these cutting-edge technologies in cybersecurity.

Conclusion:

Dr. Yazan Otoum’s extensive experience in cybersecurity education, research, and practical applications positions him as a pivotal figure in shaping the next generation of cybersecurity professionals. His commitment to integrating advanced technologies such as machine learning, blockchain, and cloud computing into his curriculum reflects a forward-thinking approach to education. Through his mentorship and innovative teaching methods, Dr. Otoum not only imparts critical knowledge but also inspires students to tackle emerging challenges in the field. His contributions to projects like “Digital Citizenship” under the Saudi Vision 2030 initiative and recognition from prestigious organizations further underscore his dedication to enhancing cybersecurity awareness and education globally. As he continues to lead initiatives and mentor future experts, Dr. Otoum plays a crucial role in advancing cybersecurity practices and fostering a secure digital environment.

Top Notable Publications:

Enhancing Heart Disease Prediction with Federated Learning and Blockchain Integration

Authors: Chaosheng Hu, Yazan Otoum, et al.

Year: 2024

Journal: Future Internet

DOI: 10.3390/fi16100372

Machine Learning in Metaverse Security: Current Solutions and Future Challenges

Authors: Yazan Otoum, et al.

Year: 2024

Journal: ACM Computing Surveys

DOI: 10.1145/3654663

DL-IDS: a deep learning–based intrusion detection framework for securing IoT

Authors: Yazan Otoum, et al.

Year: 2022

Journal: Transactions on Emerging Telecommunications Technologies

DOI: 10.1002/ett.3803

FTLIoT: A Federated Transfer Learning Framework for Securing IoT

Authors: Yazan Otoum, et al.

Year: 2022

Conference: IEEE Global Communications Conference

DOI: 10.1109/GLOBECOM48099.2022.10001461

WOSUID: WOS:000922633501029

Transfer Learning-Driven Intrusion Detection for Internet of Vehicles (IoV)

Authors: Yazan Otoum, et al.

Year: 2022

Conference: International Wireless Communications and Mobile Computing Conference

DOI: 10.1109/IWCMC55113.2022.9825115

WOSUID: WOS:001058917600060

AS-IDS: Anomaly and Signature Based IDS for the Internet of Things

Authors: Yazan Otoum, et al.

Year: 2021

Journal: Journal of Network and Systems Management

DOI: 10.1007/s10922-021-09589-6

On securing IoT from Deep Learning perspective

Authors: Yazan Otoum, et al.

Year: 2021

ISBN: 978-1-7281-8087-8