受强制性开放获取政策约束的文章 - Jaron Mink了解详情
可在其他位置公开访问的文章：8 篇
Sok: History is a vast early warning system: Auditing the provenance of system intrusions
MA Inam, Y Chen, A Goyal, J Liu, J Mink, N Michael, S Gaur, A Bates, ...
2023 IEEE Symposium on Security and Privacy (SP), 2620-2638, 2023
强制性开放获取政策： US National Science Foundation
Beyond Bot Detection: Combating Fraudulent Online Survey Takers
Z Zhang, S Zhu, J Mink, A Xiong, L Song, G Wang
Proceedings of the ACM Web Conference 2022, 699-709, 2022
强制性开放获取政策： US National Science Foundation
On the forensic validity of approximated audit logs
N Michael, J Mink, J Liu, S Gaur, WU Hassan, A Bates
Proceedings of the 36th Annual Computer Security Applications Conference …, 2020
强制性开放获取政策： US National Science Foundation
DeepPhish: Understanding User Trust Towards Artificially Generated Profiles in Online Social Networks
J Mink, L Luo, NM Barbosa, O Figueira, Y Wang, G Wang
31st USENIX Security Symposium (USENIX Security 22), 2022
强制性开放获取政策： US National Science Foundation
“Security is not my field, I’m a stats guy”: A Qualitative Root Cause Analysis of Barriers to Adversarial Machine Learning Defenses in Industry
J Mink, H Kaur, J Schmüser, S Fahl, Y Acar
32nd USENIX Security Symposium (USENIX Security '23), 2023
强制性开放获取政策： US National Science Foundation, Helmholtz Association
Everybody’s Got ML, Tell Me What Else You Have: Practitioners’ Perception of ML-Based Security Tools and Explanations
J Mink, H Benkraouda, L Yang, A Ciptadi, A Ahmadzadeh, D Votipka, ...
IEEE Symposium on Security and Privacy (SP), 2023
强制性开放获取政策： US National Science Foundation
Users Can Deduce Sensitive Locations Protected by Privacy Zones on Fitness Tracking Apps
J Mink, AR Yuile, U Pal, AJ Aviv, A Bates
Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, 2022
强制性开放获取政策： US National Science Foundation
Can you trust what you see online?
G Wang, J Mink
Futurum Careers, 2023
强制性开放获取政策： US National Science Foundation
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