Moonseong Kim
Seoul Theological University
135 Papers
574 Citations
Moonseong Kim is an academic researcher from Seoul Theological University. The author has contributed to research in topics: Wireless sensor network & Multicast. The author has an hindex of 14, co-authored 114 publications. Previous affiliations of Moonseong Kim include Michigan State University & Korean Intellectual Property Office.
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Papers
Efficient and Anonymous Two-Factor User Authentication in Wireless Sensor Networks: Achieving User Anonymity with Lightweight Sensor Computation
TL;DR: This paper presents a new SCA-WSN scheme that not only achieves user anonymity but also is efficient in terms of the computation loads for sensors.
A Provably-Secure ECC-Based Authentication Scheme for Wireless Sensor Networks
TL;DR: This paper devise a security model for the analysis of SUA-WSN schemes by extending the widely-accepted model of Bellare, Pointcheval and Rogaway (2000), which provides formal definitions of authenticated key exchange and user anonymity while capturing side-channel attacks, as well as other common attacks.
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Route Optimization in Nested NEMO: Classification, Evaluation, and Analysis from NEMO Fringe Stub Perspective
TL;DR: It is suggested that, when choosing a solution for deploying NEMO, the designer has to balance his choices between the different pros and cons, and the different cases of application that are derived in this paper.
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Patent
Multi-path routing method in wireless sensor network
Soyoung Hwang,Bongsoo Kim,Cheol-Sig Pyo,Jong-Suk Chae,Moonseong Kim,Eui-Hoon Jeong,Young-Cheol Bang +6 more
- 30 Jul 2008
TL;DR: In this article, a multi-path routing method for selecting appropriate multiple paths when information sensed from a source node is transmitted to a sink node in wireless sensor networks is provided, where priorities can be provided to lifetime of the source node, average energy consumption and the shortest path by adjusting the respective weights when routing the plurality of paths.
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MCBT: Multi-Hop Cluster Based Stable Backbone Trees for Data Collection and Dissemination in WSNs.
TL;DR: A distributed algorithm to create a stable backbone by selecting the nodes with higher energy or degree as the cluster heads for wireless sensor networks (WSNs) increases the overall network lifetime.
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