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Zeliang Kan
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2020 – today
- 2024
- [i2]Zeliang Kan, Shae McFadden, Daniel Arp, Feargus Pendlebury, Roberto Jordaney, Johannes Kinder, Fabio Pierazzi, Lorenzo Cavallaro:
TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time (Extended Version). CoRR abs/2402.01359 (2024) - 2023
- [c6]Theo Chow, Zeliang Kan, Lorenz Linhardt, Lorenzo Cavallaro, Daniel Arp, Fabio Pierazzi:
Drift Forensics of Malware Classifiers. AISec@CCS 2023: 197-207 - [c5]Shae McFadden, Zeliang Kan, Lorenzo Cavallaro, Fabio Pierazzi:
Poster: RPAL-Recovering Malware Classifiers from Data Poisoning using Active Learning. CCS 2023: 3561-3563 - [c4]Zhi Chen, Zhenning Zhang, Zeliang Kan, Limin Yang, Jacopo Cortellazzi, Feargus Pendlebury, Fabio Pierazzi, Lorenzo Cavallaro, Gang Wang:
Is It Overkill? Analyzing Feature-Space Concept Drift in Malware Detectors. SP (Workshops) 2023: 21-28 - 2021
- [c3]Zeliang Kan, Feargus Pendlebury, Fabio Pierazzi, Lorenzo Cavallaro:
Investigating Labelless Drift Adaptation for Malware Detection. AISec@CCS 2021: 123-134
2010 – 2019
- 2019
- [c2]Zeliang Kan, Haoyu Wang, Lei Wu, Yao Guo, Guoai Xu:
Deobfuscating Android native binary code. ICSE (Companion Volume) 2019: 322-323 - [i1]Zeliang Kan, Haoyu Wang, Lei Wu, Yao Guo, Daniel Xiapu Luo:
Automated Deobfuscation of Android Native Binary Code. CoRR abs/1907.06828 (2019) - 2018
- [c1]Zeliang Kan, Haoyu Wang, Guoai Xu, Yao Guo, Xiangqun Chen:
Towards Light-Weight Deep Learning Based Malware Detection. COMPSAC (1) 2018: 600-609
Coauthor Index
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last updated on 2024-10-07 22:16 CEST by the dblp team
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