Han Wang
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Dr. Han Wang is working as a researcher at the Cybersecurity Unit at RISE Research Institutes of Sweden, focusing on the topic of ML for security and cyber threat intelligence. Han received her Ph.D degree in Computer Communication from Uppsala University (Sweden) in 2024. Han received a double MSc in Computer Science, specializing in machine learning, from Uppsala University and National Taiwan Normal University (Taiwan) in 2017. She has vast experience in network security, FL, cyber threat intelligence, and adversarial AI.
Publications:
1. H. Wang, L. Barriga, A. Vahidi and S. Raza, "Machine Learning for Security at the IoT Edge - A Feasibility Study," 2019 IEEE 16th International Conference on Mobile Ad Hoc and Sensor Systems Workshops (MASSW), 2019, pp. 7-12, doi: 10.1109/MASSW.2019.00009.
2. Han Wang, Luis Muñoz-González, David Eklund, and Shahid Raza. 2021. Non-IID data re-balancing at IoT edge with peer-to-peer federated learning for anomaly detection. In Proceedings of the 14th ACM Conference on Security and Privacy in Wireless and Mobile Networks (WiSec '21). Association for Computing Machinery, New York, NY, USA, 153–163. DOI:https://doi.org/10.1145/3448300.3467827
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Publications
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Publications
- Robust and Efficient Federated Learning for IoT Security
- PEDS: Privately Encoded Deep Synthesis to Mitigate Membership Inference Attacks
- Benchmarking LLMS for Threat Level Determination
- Enabling Cyber Threat Intelligence Sharing for Resource Constrained IoT
- BMI : Bounded Mutual Information for Efficient Privacy-Preserving Feature Selec…
- CLEVER : Crafting Intelligent MISP for Cyber Threat Intelligence
- BMI: Bounded Mutual Information for Efficient Privacy-Preserving Feature Select…
- FL4IoT : IoT Device Fingerprinting and Identification Using Federated Learning
- On the Resilience of Machine Learning-Based IDS for Automotive Networks
- SparSFA : Towards robust and communication-efficient peer-to-peer federated lea…