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Wanlei Zhou
Researcher at University of Technology, Sydney
Publications - 545
Citations - 11892
Wanlei Zhou is an academic researcher from University of Technology, Sydney. The author has contributed to research in topics: Computer science & Differential privacy. The author has an hindex of 50, co-authored 504 publications receiving 9526 citations. Previous affiliations of Wanlei Zhou include Guangzhou University & University of Sydney.
Papers
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Journal ArticleDOI
Low-Rate DDoS Attacks Detection and Traceback by Using New Information Metrics
Yang Xiang,Ke Li,Wanlei Zhou +2 more
TL;DR: Two new information metrics such as the generalized entropy metric and the information distance metric are proposed to detect low-rate DDoS attacks by measuring the difference between legitimate traffic and attack traffic.
Journal ArticleDOI
Trust mechanisms in wireless sensor networks: Attack analysis and countermeasures
TL;DR: Various types of attacks and countermeasures related to trust schemes in WSNs are categorized, the development of trust mechanisms are provided, a short summarization of classical trust methodologies are given and an open field and future direction with trust mechanisms in W SNs is provided.
Journal ArticleDOI
Robust network traffic classification
TL;DR: The proposed RTC scheme has the capability of identifying the traffic of zero-day applications as well as accurately discriminating predefined application classes and is significantly better than four state-of-the-art methods.
Book Chapter
Teaching and learning online with wikis
TL;DR: This paper presents wikis as a useful tool for facilitating online education and illustrates how e-learning practitioners can and are moving beyond their comfort zone by using wikis to enhance the process of teaching and learning online.
Journal ArticleDOI
Network Traffic Classification Using Correlation Information
TL;DR: A novel nonparametric approach for traffic classification is proposed which can improve the classification performance effectively by incorporating correlated information into the classification process and its performance benefit from both theoretical and empirical perspectives.