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pro vyhledávání: '"Chung, Jin"'
Tokenization is a crucial step that bridges human-readable text with model-readable discrete tokens. However, recent studies have revealed that tokenizers can be exploited to elicit unwanted model behaviors. In this work, we investigate incomplete to
Externí odkaz:
http://arxiv.org/abs/2410.23684
Autor:
Cui, Jian, Kim, Hanna, Jang, Eugene, Yim, Dayeon, Kim, Kicheol, Lee, Yongjae, Chung, Jin-Woo, Shin, Seungwon, Liao, Xiaojing
Twitter is recognized as a crucial platform for the dissemination and gathering of Cyber Threat Intelligence (CTI). Its capability to provide real-time, actionable intelligence makes it an indispensable tool for detecting security events, helping sec
Externí odkaz:
http://arxiv.org/abs/2409.08221
Autor:
Jang, Eugene, Cui, Jian, Yim, Dayeon, Jin, Youngjin, Chung, Jin-Woo, Shin, Seungwon, Lee, Yongjae
Cybersecurity information is often technically complex and relayed through unstructured text, making automation of cyber threat intelligence highly challenging. For such text domains that involve high levels of expertise, pretraining on in-domain cor
Externí odkaz:
http://arxiv.org/abs/2403.10576
Autor:
Lee, Jisun, Kwon, Jay Hyoun, Park, Chang Yong, Kim, Huidong, Choi, In-Mook, Chung, Jin Wan, Lee, Won-Kyu
Relativistic redshift correction should be accurately considered in frequency comparisons between frequency standards. In this study, we evaluated the relativistic redshift at Korea Research Institute of Standards and Science (KRISS) using three diff
Externí odkaz:
http://arxiv.org/abs/2401.04943
Recent research has suggested that there are clear differences in the language used in the Dark Web compared to that of the Surface Web. As studies on the Dark Web commonly require textual analysis of the domain, language models specific to the Dark
Externí odkaz:
http://arxiv.org/abs/2305.08596
DRAINCLoG: Detecting Rogue Accounts with Illegally-obtained NFTs using Classifiers Learned on Graphs
Autor:
Kim, Hanna, Cui, Jian, Jang, Eugene, Lee, Chanhee, Lee, Yongjae, Chung, Jin-Woo, Shin, Seungwon
As Non-Fungible Tokens (NFTs) continue to grow in popularity, NFT users have become targets of phishing attacks by cybercriminals, called \textit{NFT drainers}. Over the last year, \$100 million worth of NFTs were stolen by drainers, and their presen
Externí odkaz:
http://arxiv.org/abs/2301.13577
Publikováno v:
Mathematics (2227-7390). Nov2024, Vol. 12 Issue 21, p3316. 11p.
The hidden nature and the limited accessibility of the Dark Web, combined with the lack of public datasets in this domain, make it difficult to study its inherent characteristics such as linguistic properties. Previous works on text classification of
Externí odkaz:
http://arxiv.org/abs/2204.06885
Publikováno v:
In International Journal of Hydrogen Energy 11 November 2024 90:961-971