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Chin-Ling Chen

Researcher at Chaoyang University of Technology

Publications -  242
Citations -  2279

Chin-Ling Chen is an academic researcher from Chaoyang University of Technology. The author has contributed to research in topics: Authentication & Mutual authentication. The author has an hindex of 21, co-authored 209 publications receiving 1674 citations. Previous affiliations of Chin-Ling Chen include Xiamen University of Technology & Changchun University of Science and Technology.

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An Improved Network Traffic Classification Model Based on a Support Vector Machine

TL;DR: An improved network traffic classification model based on a support vector machine that achieves higher classification accuracy, lower dimension and shorter elapsed time and performs significantly better than traditional SVM and the other three typical supervised ML algorithms.
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A secure mutual authentication scheme with non‐repudiation for vehicular ad hoc networks

TL;DR: The proposed scheme is proved to achieve the requirements of resist known attacks, non‐repudiation, authentication, availability, integrity, and confidentiality and can resist malicious attacks or prevent illegal users' access via security and performance analysis.
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Design of a secure and effective medical cyber-physical system for ubiquitous telemonitoring pregnancy

TL;DR: A cloud computing platform for all users to access the cloud information at any time in accordance with their own demands and to effectively protect pregnancy‐related privacy is established.
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A Novel Designated Verifier Signature Scheme Based on Bilinear Pairing

TL;DR: A novel designated verifier signature scheme that allows the verifier to maintain a transcript signature of the verifiers' secret key and is vulnerable to replay-attack.
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A Highly Secure IoT Firmware Update Mechanism Using Blockchain

TL;DR: This research proposes a highly secure and efficient protection mechanism that is based on the blockchain technology to improve the above disadvantages and confirms the high security and practical feasibility of the proposed system by comparing with the existing methods.