Výsledky vyhledávání - "Zhenzhou Tian"

Akademický článek

Preparation and Biotoxicity of Coal-Based Carbon Dot Nanomaterials

Autor: Zhenzhou Tian, Jinyao Li, Yanming Miao, Jinzhi Lv

Publikováno v: Nanomaterials, Vol 13, Iss 24, p 3122 (2023)

Coal-based Carbon Dots (C-CDs) have gradually become a research focus due to the abundant raw materials and low preparation cost. Still, before coal-based carbon dots are widely used, a systematic biological toxicity study is the basis for the safe u

Externí odkaz: https://doaj.org/article/1127134916d84242b04018b540a55b34

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Akademický článek

Fine-Grained Compiler Identification With Sequence-Oriented Neural Modeling

Autor: Zhenzhou Tian, Yaqian Huang, Borun Xie, Yanping Chen, Lingwei Chen, Dinghao Wu

Publikováno v: IEEE Access, Vol 9, Pp 49160-49175 (2021)

Different compilers and optimization levels can be used to compile the source code. Revealed in reverse from the produced binaries, these compiler details facilitate essential binary analysis tasks, such as malware analysis and software forensics. Mo

Externí odkaz: https://doaj.org/article/8eb6cc2434674fb2b21bc345170ec157

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Akademický článek

Plagiarism Detection of Multi-Threaded Programs via Siamese Neural Networks

Autor: Zhenzhou Tian, Qing Wang, Cong Gao, Lingwei Chen, Dinghao Wu

Publikováno v: IEEE Access, Vol 8, Pp 160802-160814 (2020)

Widespread intentional or unintentional software plagiarisms have posed serious threats to the healthy development of software industry. In order to detect such evolving software plagiarism, software dynamic birthmark techniques of better anti-obfusc

Externí odkaz: https://doaj.org/article/f7c91b0aa22f4a0d97a65019547331dd

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Learning and Fusing Multi-View Code Representations for Function Vulnerability Detection

Autor: Chen, Zhenzhou Tian, Binhui Tian, Jiajun Lv, Lingwei

Publikováno v: Electronics; Volume 12; Issue 11; Pages: 2495

The explosive growth of vulnerabilities poses a significant threat to the security of software systems. While various deep-learning-based vulnerability detection methods have emerged, they primarily rely on semantic features extracted from a single c

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=multidiscipl::c2a513cd37bebbbd0c3bbc5f857037c5

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