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Detecting Malicious Accounts in Online Social Networks


26Jan 2022


  • Zoom
  • Dr. Yang Chen, School of Computer Science at Fudan University



Our daily lives have been immersed in widespread online social networks (OSNs). As an open platform, OSNs typically allow all kinds of users to register accounts. Malicious attackers can easily join and post misleading information, often with the intention of influencing users' decisions in OSNs. To provide reliable information and improve the experience for legitimate users, we leverage emerging deep learning technologies to learn users' dynamic behavior and build models to distinguish between legitimate users and malicious users. Our deep learning-based approaches have been shown useful in different kinds of OSNs, including location-based social networks, online developer communities and online dating apps.



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24Jan 2022


Information Session on Health and Medical Research Fund (HMRF)

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  • Dr Xavier WONG, School of Chinese Medicine

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26Jan 2022


HKBU Distinguished Lecture Series: Traditional Wisdom of Chinese Medicine and its Application: Opportunity and Challenges

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  • by Prof Bian Zhaoxiang, Tsang Shiu Tim Endowed Professor of Chinese Medicine Clinical Studies