Artikel dengan mandat akses publik - Alina OpreaPelajari lebih lanjut
Tidak tersedia di mana pun: 3
Poisoning attacks and data sanitization mitigations for machine learning models in network intrusion detection systems
S Venkatesan, H Sikka, R Izmailov, R Chadha, A Oprea, MJ De Lucia
MILCOM 2021-2021 IEEE Military Communications Conference (MILCOM), 874-879, 2021
Mandat: US Department of Defense
An Improved Nested Training Approach to Mitigate Clean-label Attacks against Malware Classifiers
A Reddy, S Venkatesan, R Izmailov, A Oprea
MILCOM 2023-2023 IEEE Military Communications Conference (MILCOM), 703-709, 2023
Mandat: US Department of Defense
Poisoning attacks on machine learning models in cyber systems and mitigation strategies
R Izmailov, S Venkatesan, A Reddy, R Chadha, M De Lucia, A Oprea
Disruptive Technologies in Information Sciences VI 12117, 1211702, 2022
Mandat: US Department of Defense
Tersedia di suatu tempat: 35
Extracting training data from large language models
N Carlini, F Tramer, E Wallace, M Jagielski, A Herbert-Voss, K Lee, ...
30th USENIX security symposium (USENIX Security 21), 2633-2650, 2021
Mandat: US National Science Foundation
Manipulating machine learning: Poisoning attacks and countermeasures for regression learning
M Jagielski, A Oprea, B Biggio, C Liu, C Nita-Rotaru, B Li
2018 IEEE symposium on security and privacy (SP), 19-35, 2018
Mandat: US National Science Foundation, US Department of Defense, European Commission
Why do adversarial attacks transfer? explaining transferability of evasion and poisoning attacks
A Demontis, M Melis, M Pintor, M Jagielski, B Biggio, A Oprea, ...
28th USENIX security symposium (USENIX security 19), 321-338, 2019
Mandat: US Department of Defense, European Commission
Explanation-Guided Backdoor Poisoning Attacks Against Malware Classifiers
G Severi, J Meyer, S Coull, A Oprea
30th USENIX Security Symposium (USENIX Security 21), 1487-1504, 2021
Mandat: US Department of Defense
Differentially private fair learning
M Jagielski, M Kearns, J Mao, A Oprea, A Roth, S Sharifi-Malvajerdi, ...
International Conference on Machine Learning, 3000-3008, 2019
Mandat: US National Science Foundation, US Department of Defense
Wild patterns reloaded: A survey of machine learning security against training data poisoning
AE Cinà, K Grosse, A Demontis, S Vascon, W Zellinger, BA Moser, ...
ACM Computing Surveys 55 (13s), 1-39, 2023
Mandat: European Commission, Government of Italy
Subpopulation data poisoning attacks
M Jagielski, G Severi, N Pousette Harger, A Oprea
Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications …, 2021
Mandat: US Department of Defense
Robust linear regression against training data poisoning
C Liu, B Li, Y Vorobeychik, A Oprea
Proceedings of the 10th ACM workshop on artificial intelligence and security …, 2017
Mandat: US National Science Foundation, US Department of Defense, US National …
Fence: Feasible evasion attacks on neural networks in constrained environments
A Chernikova, A Oprea
ACM Transactions on Privacy and Security 25 (4), 1-34, 2022
Mandat: US National Science Foundation, US Department of Defense
Living-off-the-land command detection using active learning
T Ongun, JW Stokes, JB Or, K Tian, F Tajaddodianfar, J Neil, C Seifert, ...
Proceedings of the 24th International Symposium on Research in Attacks …, 2021
Mandat: US National Science Foundation, US Department of Defense
Lens on the endpoint: Hunting for malicious software through endpoint data analysis
AS Buyukkayhan, A Oprea, Z Li, W Robertson
International Symposium on Research in Attacks, Intrusions, and Defenses, 73-97, 2017
Mandat: US National Science Foundation
SNAP: Efficient extraction of private properties with poisoning
H Chaudhari, J Abascal, A Oprea, M Jagielski, F Tramer, J Ullman
2023 IEEE Symposium on Security and Privacy (SP), 400-417, 2023
Mandat: US National Science Foundation
With great dispersion comes greater resilience: Efficient poisoning attacks and defenses for linear regression models
J Wen, BZH Zhao, M Xue, A Oprea, H Qian
IEEE Transactions on Information Forensics and Security 16, 3709-3723, 2021
Mandat: US Department of Defense, Australian Research Council, National Natural …
: An adaptive reinforcement learning strategy for the security game
L Oakley, A Oprea
International Conference on Decision and Game Theory for Security, 364-384, 2019
Mandat: US National Science Foundation, US Department of Defense
Catching predators at watering holes: finding and understanding strategically compromised websites
S Alrwais, K Yuan, E Alowaisheq, X Liao, A Oprea, XF Wang, Z Li
Proceedings of the 32nd Annual Conference on Computer Security Applications …, 2016
Mandat: US National Science Foundation
Network-level adversaries in federated learning
G Severi, M Jagielski, G Yar, Y Wang, A Oprea, C Nita-Rotaru
2022 IEEE Conference on Communications and Network Security (CNS), 19-27, 2022
Mandat: US Department of Defense
Cyber network resilience against self-propagating malware attacks
A Chernikova, N Gozzi, S Boboila, P Angadi, J Loughner, M Wilden, ...
European Symposium on Research in Computer Security, 531-550, 2022
Mandat: US Department of Defense
Informasi terbitan dan pendanaan ditentukan secara otomatis oleh program komputer