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Dong-Chan Kim

dblp:44/10733 · DBLP profile ↗
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3ranked-venue papers
0as first author
0since 2021 · last 2020
0000-0001-8870-3605ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2Graphics, computer vision, multimedia, augmented reality and games · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
1 paper
Cryptographic primitives and cryptanalysis · 100%

Topics — the 1 heaviest of 1, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Cryptographic primitives and cryptanalysis › cryptographic implementation
white-box cryptography		 0.412020
Cryptanalysis of the obfuscated round boundary technique for whitebox cryptography · Sci. China Inf. Sci. 2020
YearPublicationVenuePosition
2020 Cryptanalysis of the obfuscated round boundary technique for whitebox cryptography
Yongjin Yeom, Dong-Chan Kim, Chung Hun Baek, Jun-Bum Shin
 Sci. China Inf. Sci.2
2020 Internal Calibration System Using Learning Algorithm With Gradient Descent
abstract
We present a novel approach to internal calibration of a radar system. A Ku-band radar system with internal calibration paths is designed. Thermal drift of a system is mainly caused by active components, which are a high-power amplifier (HPA) and a low-noise amplifier (LNA). We aimed to reduce the drift using a learning algorithm with a gradient-descent method. Hardware offset factors and calibration factors are introduced for the process. In the learning algorithm, a penalty term is formed based on the analysis of local minimum points. The result verifies the proposed internal calibration method. Maximum deviations of gain are 0.0477 dB for the HPA and 0.0132 dB for the LNA. In addition, the maximum deviations of phase are 0.2481° for HPA and 0.0722° for LNA, respectively.
Chanyong Jung, Kyung-Bin Bae, Dong-Chan Kim, Seong-Ook Park
 IEEE Geosci. Remote. Sens. Lett.3
2016 Improved preimage attacks on hash modes of 8-round AES-256
Deukjo Hong, Dong-Chan Kim, Daesung Kwon, Jongsung Kim
 Multim. Tools Appl.2