Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Song, Qige"'
Autor:
Li, Xiang, Guo, Juncheng, Song, Qige, Xie, Jiang, Sang, Yafei, Zhao, Shuyuan, Zhang, Yongzheng
Mobile Internet has profoundly reshaped modern lifestyles in various aspects. Encrypted Traffic Classification (ETC) naturally plays a crucial role in managing mobile Internet, especially with the explosive growth of mobile apps using encrypted commu
Externí odkaz:
http://arxiv.org/abs/2308.16453
Cross-architecture binary similarity comparison is essential in many security applications. Recently, researchers have proposed learning-based approaches to improve comparison performance. They adopted a paradigm of instruction pre-training, individu
Externí odkaz:
http://arxiv.org/abs/2206.12236
The big wave of Internet of Things (IoT) malware reflects the fragility of the current IoT ecosystem. Research has found that IoT malware can spread quickly on devices of different processer architectures, which leads our attention to cross-architect
Externí odkaz:
http://arxiv.org/abs/2206.00219
Binary authorship analysis is a significant problem in many software engineering applications. In this paper, we formulate a binary authorship verification task to accurately reflect the real-world working process of software forensic experts. It aim
Externí odkaz:
http://arxiv.org/abs/2203.04472
Publikováno v:
In Computers & Security February 2024 137
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Poster of paper entailed:BinMLM: Binary Authorship Verification with Flow-aware Mixture-of-Shared Language ModelThe paper is accepted for SANER 2022 Research Track.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0f43a10af02ae206515ebe984443723b
Poster of paper entailed:BinMLM: Binary Authorship Verification with Flow-aware Mixture-of-Shared Language ModelThe paper is accepted for SANER 2022 Research Track.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::61fb3f8144b1332d7e1cf2376e503574