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Zhihong Tian
Researcher at Guangzhou University
Publications - 240
Citations - 5231
Zhihong Tian is an academic researcher from Guangzhou University. The author has contributed to research in topics: Computer science & Deep learning. The author has an hindex of 26, co-authored 185 publications receiving 2548 citations. Previous affiliations of Zhihong Tian include China Academy of Engineering Physics & Chinese Academy of Sciences.
Papers
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CorrAUC: A Malicious Bot-IoT Traffic Detection Method in IoT Network Using Machine-Learning Techniques
TL;DR: A new framework model based on a novel feature selection metric approach named CorrAUC is proposed, and a new feature selection algorithm based on the wrapper technique to filter the features accurately and select effective features for the selected ML algorithm by using the area under the curve (AUC) metric.
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A Distributed Deep Learning System for Web Attack Detection on Edge Devices
TL;DR: This article proposes a web attack detection system that takes advantage of analyzing URLs, designed to detect web attacks and is deployed on edge devices, and is competitive in detecting web attacks.
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A Survey on Access Control in the Age of Internet of Things
TL;DR: This article aims to provide theoretical, methodological, and technical guidance for IoT search access control mechanisms in large-scale dynamic heterogeneous environments based on a literature review and analyzed the future development direction of access control in the age of IoT.
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Selection of effective machine learning algorithm and Bot-IoT attacks traffic identification for internet of things in smart city
TL;DR: A new framework model and a hybrid algorithm to solve the problem of selecting an effective ML algorithm for cyber attacks detection system for IoT security and results show that the proposed model with the algorithm is effective for the selection ML algorithm out of numbers of ML algorithms.
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Block-DEF: A secure digital evidence framework using blockchain
TL;DR: This work proposes a secure digital evidence framework using blockchain (Block-DEF) with a loose coupling structure in which the evidence and the evidence information are maintained separately and the multi-signature technique is adopted for evidence submission and retrieval.