Zobrazeno 1 - 7 of 7 pro vyhledávání: '"Jangseong Bae"'
1
Akademický článek
Korean Semantic Role Labeling with Bidirectional Encoder Representations from Transformers and Simple Semantic Information
Autor: Jangseong Bae, Changki Lee
Publikováno v: Applied Sciences, Vol 12, Iss 12, p 5995 (2022)
State-of-the-art semantic role labeling (SRL) performance has been achieved using neural network models by incorporating syntactic feature information such as dependency trees. In recent years, breakthroughs achieved using end-to-end neural network m
Externí odkaz: https://doaj.org/article/a37b28465292499f9f4767b8e542d8f5
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2
Akademický článek
Attention-Based Automated Feature Extraction for Malware Analysis
Autor: Sunoh Choi, Jangseong Bae, Changki Lee, Youngsoo Kim, Jonghyun Kim
Publikováno v: Sensors, Vol 20, Iss 10, p 2893 (2020)
Every day, hundreds of thousands of malicious files are created to exploit zero-day vulnerabilities. Existing pattern-based antivirus solutions face difficulties in coping with such a large number of new malicious files. To solve this problem, artifi
Externí odkaz: https://doaj.org/article/1dfeb0247ecc4ae2af8be86a611a9ae5
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6
Easy Data Augmentation for Improved Malware Detection: A Comparative Study
Autor: Changki Lee, Jangseong Bae
Publikováno v: BigComp
Artificial data generation is important for improving research outcomes when using deep learning. As one of the most popular and promising generative models, the variational auto-encoder (VAE) model generates synthetic data for training classifiers m
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c6be946c2dbabdb31e0f7ec0ffd1a37f
https://doi.org/10.1109/bigcomp51126.2021.00048
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7
Attention-Based Automated Feature Extraction for Malware Analysis
Autor: Changki Lee, Sunoh Choi, Jangseong Bae, Jonghyun Kim, Youngsoo Kim
Publikováno v: Sensors, Vol 20, Iss 2893, p 2893 (2020)
Sensors
Volume 20
Issue 10
Sensors (Basel, Switzerland)
Every day, hundreds of thousands of malicious files are created to exploit zero-day vulnerabilities. Existing pattern-based antivirus solutions face difficulties in coping with such a large number of new malicious files. To solve this problem, artifi
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::49224b6d40e6ac9086d722dff038ba1c
https://www.mdpi.com/1424-8220/20/10/2893
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