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ORCIDAlina Oprea
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- affiliation: Northeastern University, Boston, MA, USA
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2020 – today
- 2024
[j12]John Abascal, Stanley Wu, Alina Oprea, Jonathan R. Ullman:
TMI! Finetuned Models Leak Private Information from their Pretraining Data. Proc. Priv. Enhancing Technol. 2024(3): 202-223 (2024)- [c65]Lisa Oakley, Steven Holtzen, Alina Oprea:
Synthesizing Tight Privacy and Accuracy Bounds via Weighted Model Counting. CSF 2024: 449-463 - [c64]Galen Andrew, Peter Kairouz, Sewoong Oh, Alina Oprea, Hugh Brendan McMahan, Vinith Menon Suriyakumar:
One-shot Empirical Privacy Estimation for Federated Learning. ICLR 2024 - [c63]Harsh Chaudhari, Giorgio Severi, Alina Oprea, Jonathan R. Ullman:
Chameleon: Increasing Label-Only Membership Leakage with Adaptive Poisoning. ICLR 2024 - [c62]Andrew Yuan, Alina Oprea, Cheng Tan:
Dropout Attacks. SP 2024: 1255-1269 - [i52]Lisa Oakley, Steven Holtzen, Alina Oprea:
Synthesizing Tight Privacy and Accuracy Bounds via Weighted Model Counting. CoRR abs/2402.16982 (2024) - [i51]Harsh Chaudhari, Giorgio Severi, John Abascal, Matthew Jagielski, Christopher A. Choquette-Choo, Milad Nasr, Cristina Nita-Rotaru, Alina Oprea:
Phantom: General Trigger Attacks on Retrieval Augmented Language Generation. CoRR abs/2405.20485 (2024) - [i50]Ethan Rathbun, Christopher Amato, Alina Oprea:
SleeperNets: Universal Backdoor Poisoning Attacks Against Reinforcement Learning Agents. CoRR abs/2405.20539 (2024) - [i49]Giorgio Severi, Simona Boboila, John T. Holodnak, Kendra Kratkiewicz, Rauf Izmailov, Alina Oprea:
Model-agnostic clean-label backdoor mitigation in cybersecurity environments. CoRR abs/2407.08159 (2024) - 2023
- [j11]Alesia Chernikova, Nicolò Gozzi, Nicola Perra, Simona Boboila, Tina Eliassi-Rad, Alina Oprea:
Modeling self-propagating malware with epidemiological models. Appl. Netw. Sci. 8(1): 52 (2023) - [j10]Antonio Emanuele Cinà
, Kathrin Grosse, Ambra Demontis, Sebastiano Vascon, Werner Zellinger, Bernhard Alois Moser, Alina Oprea, Battista Biggio, Marcello Pelillo, Fabio Roli:
Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning. ACM Comput. Surv. 55(13s): 294:1-294:39 (2023) - [j9]Matthew Jagielski, Stanley Wu, Alina Oprea, Jonathan R. Ullman, Roxana Geambasu:
How to Combine Membership-Inference Attacks on Multiple Updated Machine Learning Models. Proc. Priv. Enhancing Technol. 2023(3): 211-232 (2023) - [j8]Han Wang, David Eklund, Alina Oprea, Shahid Raza:
FL4IoT: IoT Device Fingerprinting and Identification Using Federated Learning. ACM Trans. Internet Things 4(3): 17:1-17:24 (2023) - [c61]Giorgio Severi, Simona Boboila, Alina Oprea, John T. Holodnak, Kendra Kratkiewicz, Jason Matterer:
Poisoning Network Flow Classifiers. ACSAC 2023: 337-351 - [c60]Achyut Reddy, Sridhar Venkatesan, Rauf Izmailov, Alina Oprea:
An Improved Nested Training Approach to Mitigate Clean-label Attacks against Malware Classifiers. MILCOM 2023: 703-709 - [c59]Krishna Pillutla, Galen Andrew, Peter Kairouz, H. Brendan McMahan, Alina Oprea, Sewoong Oh:
Unleashing the Power of Randomization in Auditing Differentially Private ML. NeurIPS 2023 - [c58]Joshua Bundt, Michael Davinroy, Ioannis Agadakos, Alina Oprea, William K. Robertson:
Black-box Attacks Against Neural Binary Function Detection. RAID 2023: 1-16 - [c57]Harsh Chaudhari, Matthew Jagielski, Alina Oprea:
SafeNet: The Unreasonable Effectiveness of Ensembles in Private Collaborative Learning. SaTML 2023: 176-196 - [c56]Harsh Chaudhari, John Abascal, Alina Oprea, Matthew Jagielski, Florian Tramèr, Jonathan R. Ullman:
SNAP: Efficient Extraction of Private Properties with Poisoning. SP 2023: 400-417 - [i48]Gökberk Yar, Cristina Nita-Rotaru, Alina Oprea:
Backdoor Attacks in Peer-to-Peer Federated Learning. CoRR abs/2301.09732 (2023) - [i47]Galen Andrew, Peter Kairouz, Sewoong Oh, Alina Oprea, H. Brendan McMahan, Vinith M. Suriyakumar:
One-shot Empirical Privacy Estimation for Federated Learning. CoRR abs/2302.03098 (2023) - [i46]Krishna Pillutla, Galen Andrew, Peter Kairouz, H. Brendan McMahan, Alina Oprea, Sewoong Oh:
Unleashing the Power of Randomization in Auditing Differentially Private ML. CoRR abs/2305.18447 (2023) - [i45]John Abascal, Stanley Wu, Alina Oprea, Jonathan R. Ullman:
TMI! Finetuned Models Leak Private Information from their Pretraining Data. CoRR abs/2306.01181 (2023) - [i44]Giorgio Severi, Simona Boboila, Alina Oprea, John T. Holodnak, Kendra Kratkiewicz, Jason Matterer:
Poisoning Network Flow Classifiers. CoRR abs/2306.01655 (2023) - [i43]Andrew Yuan, Alina Oprea, Cheng Tan:
Dropout Attacks. CoRR abs/2309.01614 (2023) - [i42]Harsh Chaudhari, Giorgio Severi, Alina Oprea, Jonathan R. Ullman:
Chameleon: Increasing Label-Only Membership Leakage with Adaptive Poisoning. CoRR abs/2310.03838 (2023) - [i41]Nikhil Kandpal, Krishna Pillutla, Alina Oprea, Peter Kairouz, Christopher A. Choquette-Choo, Zheng Xu:
User Inference Attacks on Large Language Models. CoRR abs/2310.09266 (2023) - 2022
- [j7]Alina Oprea, Anoop Singhal, Apostol Vassilev:
Poisoning Attacks Against Machine Learning: Can Machine Learning Be Trustworthy? Computer 55(11): 94-99 (2022) - [j6]Nathalie Baracaldo, Alina Oprea:
Machine Learning Security and Privacy. IEEE Secur. Priv. 20(5): 11-13 (2022) - [j5]Alesia Chernikova, Alina Oprea:
FENCE: Feasible Evasion Attacks on Neural Networks in Constrained Environments. ACM Trans. Priv. Secur. 25(4): 34:1-34:34 (2022) - [c55]Afsah Anwar, Yi Hui Chen, Roy Hodgman, Tom Sellers, Engin Kirda, Alina Oprea:
A Recent Year On the Internet: Measuring and Understanding the Threats to Everyday Internet Devices. ACSAC 2022: 251-266 - [c54]Giorgio Severi, Matthew Jagielski, Gökberk Yar, Yuxuan Wang, Alina Oprea, Cristina Nita-Rotaru:
Network-Level Adversaries in Federated Learning. CNS 2022: 19-27 - [c53]Lisa Oakley, Alina Oprea, Stavros Tripakis:
Adversarial Robustness Verification and Attack Synthesis in Stochastic Systems. CSF 2022: 380-395 - [c52]Alesia Chernikova, Nicolò Gozzi, Simona Boboila, Priyanka Angadi, John Loughner, Matthew Wilden, Nicola Perra, Tina Eliassi-Rad, Alina Oprea:
Cyber Network Resilience Against Self-Propagating Malware Attacks. ESORICS (1) 2022: 531-550 - [c51]Giorgio Severi, Will Pearce, Alina Oprea:
Bad Citrus: Reducing Adversarial Costs with Model Distances. ICMLA 2022: 307-312 - [c50]Samson Ho, Achyut Reddy, Sridhar Venkatesan, Rauf Izmailov, Ritu Chadha, Alina Oprea:
Data Sanitization Approach to Mitigate Clean-Label Attacks Against Malware Detection Systems. MILCOM 2022: 993-998 - [i40]Antonio Emanuele Cinà, Kathrin Grosse, Ambra Demontis, Sebastiano Vascon, Werner Zellinger, Bernhard Alois Moser, Alina Oprea, Battista Biggio, Marcello Pelillo, Fabio Roli:
Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning. CoRR abs/2205.01992 (2022) - [i39]Matthew Jagielski, Stanley Wu, Alina Oprea, Jonathan R. Ullman, Roxana Geambasu:
How to Combine Membership-Inference Attacks on Multiple Updated Models. CoRR abs/2205.06369 (2022) - [i38]Harsh Chaudhari, Matthew Jagielski, Alina Oprea:
SafeNet: Mitigating Data Poisoning Attacks on Private Machine Learning. CoRR abs/2205.09986 (2022) - [i37]Talha Ongun, Simona Boboila, Alina Oprea, Tina Eliassi-Rad, Jason Hiser, Jack W. Davidson:
CELEST: Federated Learning for Globally Coordinated Threat Detection. CoRR abs/2205.11459 (2022) - [i36]Alesia Chernikova, Nicolò Gozzi, Simona Boboila, Priyanka Angadi, John Loughner, Matthew Wilden, Nicola Perra, Tina Eliassi-Rad, Alina Oprea:
Cyber Network Resilience against Self-Propagating Malware Attacks. CoRR abs/2206.13594 (2022) - [i35]Alesia Chernikova, Nicolò Gozzi, Simona Boboila, Nicola Perra, Tina Eliassi-Rad, Alina Oprea:
Modeling Self-Propagating Malware with Epidemiological Models. CoRR abs/2208.03276 (2022) - [i34]Joshua Bundt, Michael Davinroy, Ioannis Agadakos, Alina Oprea, William Robertson:
Attacking Neural Binary Function Detection. CoRR abs/2208.11667 (2022) - [i33]Harsh Chaudhari, John Abascal, Alina Oprea, Matthew Jagielski, Florian Tramèr, Jonathan R. Ullman:
SNAP: Efficient Extraction of Private Properties with Poisoning. CoRR abs/2208.12348 (2022) - [i32]Giorgio Severi, Matthew Jagielski, Gökberk Yar, Yuxuan Wang, Alina Oprea, Cristina Nita-Rotaru:
Network-Level Adversaries in Federated Learning. CoRR abs/2208.12911 (2022) - [i31]Giorgio Severi, Will Pearce, Alina Oprea:
Bad Citrus: Reducing Adversarial Costs with Model Distances. CoRR abs/2210.03239 (2022) - [i30]Harsh Chaudhari, Matthew Jagielski, Alina Oprea:
SafeNet: Mitigating Data Poisoning Attacks on Private Machine Learning. IACR Cryptol. ePrint Arch. 2022: 663 (2022) - 2021
- [j4]Jialin Wen, Benjamin Zi Hao Zhao, Minhui Xue, Alina Oprea, Haifeng Qian:
With Great Dispersion Comes Greater Resilience: Efficient Poisoning Attacks and Defenses for Linear Regression Models. IEEE Trans. Inf. Forensics Secur. 16: 3709-3723 (2021) - [c49]Matthew Jagielski, Giorgio Severi, Niklas Pousette Harger, Alina Oprea:
Subpopulation Data Poisoning Attacks. CCS 2021: 3104-3122 - [c48]Xianrui Meng, Dimitrios Papadopoulos, Alina Oprea, Nikos Triandopoulos:
Private Hierarchical Clustering and Efficient Approximation. CCSW 2021: 3-20 - [c47]Talha Ongun, Oliver Spohngellert, Benjamin A. Miller, Simona Boboila, Alina Oprea, Tina Eliassi-Rad, Jason Hiser, Alastair Nottingham, Jack W. Davidson, Malathi Veeraraghavan:
PORTFILER: Port-Level Network Profiling for Self-Propagating Malware Detection. CNS 2021: 182-190 - [c46]Sridhar Venkatesan, Harshvardhan Sikka, Rauf Izmailov, Ritu Chadha, Alina Oprea, Michael J. De Lucia:
Poisoning Attacks and Data Sanitization Mitigations for Machine Learning Models in Network Intrusion Detection Systems. MILCOM 2021: 874-879 - [c45]Talha Ongun, Jack W. Stokes, Jonathan Bar Or, Ke Tian, Farid Tajaddodianfar, Joshua Neil, Christian Seifert, Alina Oprea, John C. Platt:
Living-Off-The-Land Command Detection Using Active Learning. RAID 2021: 442-455 - [c44]Alina Oprea:
Machine Learning Integrity and Privacy in Adversarial Environments. SACMAT 2021: 1-2 - [c43]Giorgio Severi, Jim Meyer, Scott E. Coull, Alina Oprea:
Explanation-Guided Backdoor Poisoning Attacks Against Malware Classifiers. USENIX Security Symposium 2021: 1487-1504 - [c42]Nicholas Carlini, Florian Tramèr, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom B. Brown, Dawn Song, Úlfar Erlingsson, Alina Oprea, Colin Raffel:
Extracting Training Data from Large Language Models. USENIX Security Symposium 2021: 2633-2650 - [i29]Molly Buchanan, Jeffrey W. Collyer, Jack W. Davidson, Saikat Dey, Mark Gardner, Jason D. Hiser, Jeffry Lang, Alastair Nottingham, Alina Oprea:
On Generating and Labeling Network Traffic with Realistic, Self-Propagating Malware. CoRR abs/2104.10034 (2021) - [i28]Talha Ongun, Simona Boboila, Alina Oprea, Tina Eliassi-Rad, Alastair Nottingham, Jason Hiser, Jack W. Davidson:
Collaborative Information Sharing for ML-Based Threat Detection. CoRR abs/2104.11636 (2021) - [i27]Lisa Oakley, Alina Oprea, Stavros Tripakis:
Adversarial Robustness Verification and Attack Synthesis in Stochastic Systems. CoRR abs/2110.02125 (2021) - [i26]Talha Ongun, Jack W. Stokes, Jonathan Bar Or, Ke Tian, Farid Tajaddodianfar, Joshua Neil, Christian Seifert, Alina Oprea, John C. Platt:
Living-Off-The-Land Command Detection Using Active Learning. CoRR abs/2111.15039 (2021) - [i25]Talha Ongun, Oliver Spohngellert, Benjamin A. Miller, Simona Boboila, Alina Oprea, Tina Eliassi-Rad, Jason Hiser, Alastair Nottingham, Jack W. Davidson, Malathi Veeraraghavan:
PORTFILER: Port-Level Network Profiling for Self-Propagating Malware Detection. CoRR abs/2112.13798 (2021) - 2020
- [c41]Matthew Jagielski, Jonathan R. Ullman, Alina Oprea:
Auditing Differentially Private Machine Learning: How Private is Private SGD? NeurIPS 2020 - [c40]Ahmet Salih Buyukkayhan, Can Gemicioglu, Tobias Lauinger, Alina Oprea, William Robertson, Engin Kirda:
What's in an Exploit? An Empirical Analysis of Reflected Server XSS Exploitation Techniques. RAID 2020: 107-120 - [i24]Giorgio Severi, Jim Meyer, Scott E. Coull, Alina Oprea:
Exploring Backdoor Poisoning Attacks Against Malware Classifiers. CoRR abs/2003.01031 (2020) - [i23]Matthew Jagielski, Jonathan R. Ullman, Alina Oprea:
Auditing Differentially Private Machine Learning: How Private is Private SGD? CoRR abs/2006.07709 (2020) - [i22]Matthew Jagielski, Giorgio Severi, Niklas Pousette Harger, Alina Oprea:
Subpopulation Data Poisoning Attacks. CoRR abs/2006.14026 (2020) - [i21]Nicholas Carlini, Florian Tramèr, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom B. Brown, Dawn Song, Úlfar Erlingsson, Alina Oprea, Colin Raffel:
Extracting Training Data from Large Language Models. CoRR abs/2012.07805 (2020)
2010 – 2019
- 2019
- [c39]Indranil Jana, Alina Oprea:
AppMine: Behavioral Analytics for Web Application Vulnerability Detection. CCSW 2019: 69-80 - [c38]Lisa Oakley, Alina Oprea:
\mathsf QFlip : An Adaptive Reinforcement Learning Strategy for the \mathsf FlipIt Security Game. GameSec 2019: 364-384 - [c37]Matthew Jagielski, Michael J. Kearns, Jieming Mao, Alina Oprea, Aaron Roth, Saeed Sharifi-Malvajerdi, Jonathan R. Ullman:
Differentially Private Fair Learning. ICML 2019: 3000-3008 - [c36]Alesia Chernikova, Alina Oprea, Cristina Nita-Rotaru, BaekGyu Kim:
Are Self-Driving Cars Secure? Evasion Attacks Against Deep Neural Networks for Steering Angle Prediction. IEEE Symposium on Security and Privacy Workshops 2019: 132-137 - [c35]Ambra Demontis, Marco Melis, Maura Pintor, Matthew Jagielski, Battista Biggio, Alina Oprea, Cristina Nita-Rotaru, Fabio Roli:
Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks. USENIX Security Symposium 2019: 321-338 - [i20]Xianrui Meng, Dimitrios Papadopoulos, Alina Oprea, Nikos Triandopoulos:
Privacy-Preserving Hierarchical Clustering: Formal Security and Efficient Approximation. CoRR abs/1904.04475 (2019) - [i19]Alesia Chernikova, Alina Oprea, Cristina Nita-Rotaru, BaekGyu Kim:
Are Self-Driving Cars Secure? Evasion Attacks against Deep Neural Networks for Steering Angle Prediction. CoRR abs/1904.07370 (2019) - [i18]Lisa Oakley, Alina Oprea:
Playing Adaptively Against Stealthy Opponents: A Reinforcement Learning Strategy for the FlipIt Security Game. CoRR abs/1906.11938 (2019) - [i17]Talha Ongun, Timothy Sakharaov, Simona Boboila, Alina Oprea, Tina Eliassi-Rad:
On Designing Machine Learning Models for Malicious Network Traffic Classification. CoRR abs/1907.04846 (2019) - [i16]Talha Ongun, Oliver Spohngellert, Alina Oprea, Cristina Nita-Rotaru, Mihai Christodorescu, Negin Salajegheh:
The House That Knows You: User Authentication Based on IoT Data. CoRR abs/1908.00592 (2019) - [i15]Indranil Jana, Alina Oprea:
AppMine: Behavioral Analytics for Web Application Vulnerability Detection. CoRR abs/1908.01928 (2019) - [i14]Alesia Chernikova, Alina Oprea:
Adversarial Examples for Deep Learning Cyber Security Analytics. CoRR abs/1909.10480 (2019) - 2018
- [c34]Alina Oprea, Zhou Li, Robin Norris, Kevin D. Bowers:
MADE: Security Analytics for Enterprise Threat Detection. ACSAC 2018: 124-136 - [c33]Jiayi Duan, Ziheng Zeng, Alina Oprea, Shobha Vasudevan:
Automated Generation and Selection of Interpretable Features for Enterprise Security. IEEE BigData 2018: 1258-1265 - [c32]Talha Ongun, Alina Oprea, Cristina Nita-Rotaru, Mihai Christodorescu, Negin Salajegheh:
The House That Knows You: User Authentication Based on IoT Data. CCS 2018: 2255-2257 - [c31]Matthew Jagielski, Alina Oprea, Battista Biggio, Chang Liu, Cristina Nita-Rotaru, Bo Li:
Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning. IEEE Symposium on Security and Privacy 2018: 19-35 - [i13]Matthew Jagielski, Alina Oprea, Battista Biggio, Chang Liu, Cristina Nita-Rotaru, Bo Li:
Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning. CoRR abs/1804.00308 (2018) - [i12]Ambra Demontis, Marco Melis, Maura Pintor, Matthew Jagielski, Battista Biggio, Alina Oprea, Cristina Nita-Rotaru, Fabio Roli:
On the Intriguing Connections of Regularization, Input Gradients and Transferability of Evasion and Poisoning Attacks. CoRR abs/1809.02861 (2018) - [i11]Matthew Jagielski, Michael J. Kearns, Jieming Mao, Alina Oprea, Aaron Roth, Saeed Sharifi-Malvajerdi, Jonathan R. Ullman:
Differentially Private Fair Learning. CoRR abs/1812.02696 (2018) - 2017
- [c30]Trishita Tiwari, Ata Turk, Alina Oprea, Katzalin Olcoz, Ayse K. Coskun:
User-profile-based analytics for detecting cloud security breaches. IEEE BigData 2017: 4529-4535 - [c29]Chang Liu, Bo Li, Yevgeniy Vorobeychik, Alina Oprea:
Robust Linear Regression Against Training Data Poisoning. AISec@CCS 2017: 91-102 - [c28]Ahmet Salih Buyukkayhan, Alina Oprea, Zhou Li, William K. Robertson:
Lens on the Endpoint: Hunting for Malicious Software Through Endpoint Data Analysis. RAID 2017: 73-97 - 2016
- [c27]Sumayah A. Alrwais, Kan Yuan, Eihal Alowaisheq, Xiaojing Liao, Alina Oprea, XiaoFeng Wang, Zhou Li:
Catching predators at watering holes: finding and understanding strategically compromised websites. ACSAC 2016: 153-166 - [c26]Zhou Li, Alina Oprea:
Operational Security Log Analytics for Enterprise Breach Detection. SecDev 2016: 15-22 - [c25]Alina Oprea, Ata Turk, Cristina Nita-Rotaru, Orran Krieger:
MOSAIC: A Platform for Monitoring and Security Analytics in Public Clouds. SecDev 2016: 69-70 - [i10]Chang Liu, Bo Li, Yevgeniy Vorobeychik, Alina Oprea:
Robust High-Dimensional Linear Regression. CoRR abs/1608.02257 (2016) - 2015
- [c24]Alina Oprea, Zhou Li, Ting-Fang Yen, Sang H. Chin, Sumayah A. Alrwais:
Detection of Early-Stage Enterprise Infection by Mining Large-Scale Log Data. DSN 2015: 45-56 - 2014
- [c23]Ting-Fang Yen, Victor Heorhiadi, Alina Oprea, Michael K. Reiter, Ari Juels:
An Epidemiological Study of Malware Encounters in a Large Enterprise. CCS 2014: 1117-1130 - [c22]Alina Oprea, Reihaneh Safavi-Naini:
CCSW 2014: Sixth ACM Cloud Computing Security Workshop. CCS 2014: 1560-1561 - [e1]Gail-Joon Ahn, Alina Oprea, Reihaneh Safavi-Naini:
Proceedings of the 6th edition of the ACM Workshop on Cloud Computing Security, CCSW '14, Scottsdale, Arizona, USA, November 7, 2014. ACM 2014, ISBN 978-1-4503-3239-2 [contents] - [i9]Alina Oprea, Zhou Li, Ting-Fang Yen, Sang H. Chin, Sumayah A. Alrwais:
Detection of Early-Stage Enterprise Infection by Mining Large-Scale Log Data. CoRR abs/1411.5005 (2014) - 2013
- [j3]Ari Juels, Alina Oprea:
New approaches to security and availability for cloud data. Commun. ACM 56(2): 64-73 (2013) - [j2]Marten van Dijk, Ari Juels, Alina Oprea, Ronald L. Rivest:
FlipIt: The Game of "Stealthy Takeover". J. Cryptol. 26(4): 655-713 (2013) - [c21]Ting-Fang Yen, Alina Oprea, Kaan Onarlioglu, Todd Leetham, William K. Robertson, Ari Juels, Engin Kirda:
Beehive: large-scale log analysis for detecting suspicious activity in enterprise networks. ACSAC 2013: 199-208 - 2012
- [j1]Jianqiang Luo, Kevin D. Bowers, Alina Oprea, Lihao Xu:
Efficient software implementations of large finite fields GF(2n) for secure storage applications. ACM Trans. Storage 8(1): 2:1-2:27 (2012) - [c20]Emil Stefanov, Marten van Dijk, Ari Juels, Alina Oprea:
Iris: a scalable cloud file system with efficient integrity checks. ACSAC 2012: 229-238 - [c19]Marten van Dijk, Ari Juels, Alina Oprea, Ronald L. Rivest, Emil Stefanov, Nikos Triandopoulos:
Hourglass schemes: how to prove that cloud files are encrypted. CCS 2012: 265-280 - [c18]George Amvrosiadis, Alina Oprea, Bianca Schroeder:
Practical scrubbing: Getting to the bad sector at the right time. DSN 2012: 1-12 - [c17]Kevin D. Bowers, Marten van Dijk, Robert Griffin, Ari Juels, Alina Oprea, Ronald L. Rivest, Nikos Triandopoulos:
Defending against the Unknown Enemy: Applying FlipIt to System Security. GameSec 2012: 248-263 - [i8]Marten van Dijk, Ari Juels, Alina Oprea, Ronald L. Rivest:
FlipIt: The Game of "Stealthy Takeover". IACR Cryptol. ePrint Arch. 2012: 103 (2012) - [i7]Kevin D. Bowers, Marten van Dijk, Robert Griffin, Ari Juels, Alina Oprea, Ronald L. Rivest, Nikos Triandopoulos:
Defending Against the Unknown Enemy: Applying FlipIt to System Security. IACR Cryptol. ePrint Arch. 2012: 579 (2012) - 2011
- [c16]Kevin D. Bowers, Marten van Dijk, Ari Juels, Alina Oprea, Ronald L. Rivest:
How to tell if your cloud files are vulnerable to drive crashes. CCS 2011: 501-514 - [c15]Yinqian Zhang, Ari Juels, Alina Oprea, Michael K. Reiter:
HomeAlone: Co-residency Detection in the Cloud via Side-Channel Analysis. IEEE Symposium on Security and Privacy 2011: 313-328 - [i6]Emil Stefanov, Marten van Dijk, Alina Oprea, Ari Juels:
Iris: A Scalable Cloud File System with Efficient Integrity Checks. IACR Cryptol. ePrint Arch. 2011: 585 (2011) - 2010
- [c14]Alina Oprea, Ari Juels:
A Clean-Slate Look at Disk Scrubbing. FAST 2010: 57-70 - [i5]Kevin D. Bowers, Marten van Dijk, Ari Juels, Alina Oprea, Ronald L. Rivest:
How to Tell if Your Cloud Files Are Vulnerable to Drive Crashes. IACR Cryptol. ePrint Arch. 2010: 214 (2010)
2000 – 2009
- 2009
- [c13]Kevin D. Bowers, Ari Juels, Alina Oprea:
Proofs of retrievability: theory and implementation. CCSW 2009: 43-54 - [c12]Kevin D. Bowers, Ari Juels, Alina Oprea:
HAIL: a high-availability and integrity layer for cloud storage. CCS 2009: 187-198 - [c11]Alina Oprea, Kevin D. Bowers:
Authentic Time-Stamps for Archival Storage. ESORICS 2009: 136-151 - [i4]Alina Oprea, Kevin D. Bowers:
Authentic Time-Stamps for Archival Storage. IACR Cryptol. ePrint Arch. 2009: 306 (2009) - 2008
- [c10]Constantin Vertan, Alina Oprea, Corneliu Florea, Laura Florea:
A Pseudo-logarithmic Image Processing Framework for Edge Detection. ACIVS 2008: 637-644 - [i3]Kevin D. Bowers, Ari Juels, Alina Oprea:
Proofs of Retrievability: Theory and Implementation. IACR Cryptol. ePrint Arch. 2008: 175 (2008) - [i2]Kevin D. Bowers, Ari Juels, Alina Oprea:
HAIL: A High-Availability and Integrity Layer for Cloud Storage. IACR Cryptol. ePrint Arch. 2008: 489 (2008) - 2007
- [c9]