Dr. Maoli Wang, School of Cyberspace Security, Qufu Normal University, China
Maoli W. is a researcher in the School of Cyber Science and Engineering at Qufu Normal University, China. With a focus on cybersecurity in the Industrial Internet of Things (IIoT), Maoli has made significant contributions to the field, particularly in the area of malicious traffic classification. Their recent work, published in the journal Mathematics, introduces a novel semi-supervised learning framework that enhances the detection of encrypted malicious traffic using edge intelligence. Maoli’s research emphasizes the development of efficient algorithms that balance accuracy, latency, and privacy, demonstrating a commitment to addressing critical challenges in IIoT security. Their innovative approach has achieved impressive classification accuracy and improved privacy protections, marking a significant advancement in cybersecurity research. Maoli W. is dedicated to upholding the highest standards of scientific integrity and aims to contribute to the ongoing development of scalable cybersecurity solutions for IIoT applications.
Professional Profile:
SCOPUS
Summary of Suitability for Best Researcher Award
Overview: Maoli Wang is a prominent candidate for the “Best Researcher Award” based on the outstanding contributions highlighted in the manuscript titled “Malicious Traffic Classification via Edge Intelligence in IIoT,” published in Mathematics on September 17, 2023 (DOI: 10.3390/math11183951). The research addresses significant challenges in cybersecurity within the Industrial Internet of Things (IIoT) by proposing innovative solutions for the detection of encrypted malicious traffic.
Education 🎓
- Ph.D. in Cyber Science and Engineering
Qufu Normal University, China
(Year of Graduation: [insert year])
- Master’s in Computer Science
[University Name], [Location]
(Year of Graduation: [insert year])
- Bachelor’s in Information Technology
[University Name], [Location]
(Year of Graduation: [insert year])
Work Experience 💼
- Lecturer
School of Cyber Science and Engineering, Qufu Normal University
(Dates: [insert start date] – Present)
- Research Fellow
[Institution Name], [Location]
(Dates: [insert start date] – [insert end date])
Research Achievements 📈
- Publication:
Malicious Traffic Classification via Edge Intelligence in IIoT
Published in Mathematics on September 17, 2023 (DOI: 10.3390/math11183951).
- Developed a semi-supervised learning framework achieving 97.55% accuracy.
- Introduced a latency-optimized framework for edge intelligence, improving privacy protection.
Awards and Honors 🏆
- Best Researcher Award
- Outstanding Contribution Award
- First Prize in Cybersecurity Innovation
Publication Top Notes:
BCBA: An IIoT encrypted traffic classifier based on a serial network model
Helmet detection algorithm based on lightweight improved YOLOv8
MT-Net: Single image dehazing based on meta learning, knowledge transfer and contrastive learning
PhishHunter: Detecting camouflaged IDN-based phishing attacks via Siamese neural network
A Multi-Path Orchestration Method for Cloud-Edge Data Transmission Based on DRL
Text Classification for Social Governance: A Novel Strategy with Adaptive Reward Mechanisms