I am a Professor at Northeastern University in the Khoury College of Computer Sciences. I have a BS in Mathematics and Computer Science from University of Bucharest, Romania, and MS and PhD in Computer Science from Carnegie Mellon University. I joined Northeastern University in Fall 2016. Before that, I was a Research Scientist at RSA Laboratories for 9 years. I am the recipient of the Technology Review TR35 award for research in cloud security in 2011 and the Google Security and Privacy Award in 2019. I was on sabbatical at Google Research during the 2022-2023 academic year.

Publications

New Papers, Reports, and Manuscripts

1. Hierarchical Multi-agent Reinforcement Learning for Cyber Network Defense
   Aditya Vikram Singh, Ethan Rathbun, Emma Graham, Lisa Oakley, Simona Boboila, Alina Oprea, and Peter Chin.
   [arXiv version]
2. Adversarial Inception for Bounded Backdoor Poisoning in Deep Reinforcement Learning
   Ethan Rathbun, Christopher Amato, and Alina Oprea.
   [arXiv version]
3. UTrace: Poisoning Forensics for Private Collaborative Learning
   Evan Rose, Hidde Lycklama, Harsh Chaudhari, Anwar Hithnawi, and Alina Oprea.
   [arXiv version]
4. Model-agnostic clean-label backdoor mitigation in cybersecurity environments
   Giorgio Severi, Simona Boboila, John Holodnak, Kendra Kratkiewicz, Rauf Izmailov, and Alina Oprea.
   [arXiv version]
5. Phantom: General Trigger Attacks on Retrieval Augmented Language Generation
   Harsh Chaudhari, Giorgio Severi, John Abascal, Matthew Jagielski, Christopher A. Choquette-Choo, Milad Nasr, Cristina Nita-Rotaru, and Alina Oprea.
   [arXiv version]
6. Adversarial Machine Learning: A Taxonomy and Terminology of Attacks and Mitigations.
   Apostol Vassilev, Alina Oprea, Alie Fordyce, and Hyrum Anderson.
   Report NIST AI 100-2 E2023.
   [URL]
7. CELEST: Federated Learning for Globally Coordinated Threat Detection.
   Talha Ongun, Simona Boboila, Alina Oprea, Tina Eliassi-Rad, Jason Hiser, and Jack W. Davidson.
   [arXiv version]

Complete List of Papers

8. [NeurIPS 2024] SleeperNets: Universal Backdoor Poisoning Attacks Against Reinforcement Learning Agents
   Ethan Rathbun, Christopher Amato, and Alina Oprea. In Proceedings of the 38th Conference on Neural Information Processing Systems (NeurIPS), 2024.
   [arXiv version]
9. [EMNLP 2024] User Inference Attacks on Large Language Models
   Nikhil Kandpal, Krishna Pillutla, Alina Oprea, Peter Kairouz, Christopher A. Choquette-Choo, and Zheng Xu. In Conference on Empirical Methods in Natural Language Processing (EMNLP), Oral, 2024
   [arXiv version]
10. [IEEE CSF 2024] Synthesizing Tight Privacy and Accuracy Bounds via Weighted Model Counting.
    Lisa Oakley, Steven Holzen, and Alina Oprea. In Proceedings of the 37th IEEE Computer Security Foundations Symposium (CSF), 2024.
    [arXiv version] [Conference paper] [Code]
11. [ACM TOPS 2024] Backdoor Attacks in Peer-to-Peer Federated Learning.
    Georgios Syros, Gokberk Yar, Simona Boboila, Cristina Nita-Rotaru, and Alina Oprea. In ACM Transactions on Privacy and Security (TOPS), 2024. To Appear.
    [arXiv version] [Code]
12. [PETS 2024] TMI! Finetuned Models Leak Private Information from their Pretraining Data.
    John Abascal, Stanley Wu, Alina Oprea, and Jonathan Ullman. In Privacy Enhancing Technologies Symposium (PETS), 2024.
    [arXiv version] [Conference paper] [Code]
13. [ICLR 2024] One-shot Empirical Privacy Estimation for Federated Learning.
    Galen Andrew, Peter Kairouz, Sewoong Oh, Alina Oprea, H. Brendan McMahan, and Vinith Suriyakumar. In International Conference on Learning Representations (ICLR), Oral, 2024.
    [arXiv version] [Conference paper]
14. [ICLR 2024] Chameleon: Increasing Label-Only Membership Leakage with Adaptive Poisoning.
    Harsh Chaudhari, Giorgio Severi, Alina Oprea, and Jonathan Ullman. In International Conference on Learning Representations (ICLR), 2024.
    [arXiv version] [Conference paper] [Code]
15. [IEEE S&P 2024] Dropout Attacks.
    Andrew Yuan, Alina Oprea, and Cheng Tan. In Proceedings of the IEEE Symposium on Security and Privacy, 2024.
    [arXiv version][Conference paper] [Code]
16. [NeurIPS 2023] Unleashing the Power of Randomization in Auditing Differentially Private ML.
    Krishna Pillutla, Galen Andrew, Peter Kairouz, H. Brendan McMahan, Alina Oprea, and Sewoong Oh. In Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS), 2023.
    [arXiv version] [Conference paper] [Code]
17. [ACSAC 2023] Poisoning Network Flow Classifiers.
    Giorgio Severi, Simona Boboila, Alina Oprea, John Holodnak, Kendra Kratkiewicz, and Jason Matterer. In Proceedings of Annual Computer Security Applications Conference (ACSAC), 2023.
    [arXiv version] [Conference paper]
18. [ANS 2023] Modeling Self-Propagating Malware with Epidemiological Models
    Alesia Chernikova, Nicolo Gozzi, Nicola Perra, Simona Boboila, Tina Eliassi-Rad, and Alina Oprea. In Applied Network Science, 2023.
    [arXiv version] [Journal paper]
19. [RAID 2023] Attacking Neural Binary Function Detection.
    Joshua Bundt, Michael Davinroy, Ioannis Agadakos, Alina Oprea, and William Robertson. In Proceedings of the 26th International Symposium on Research in Attacks, Intrusions and Defenses (RAID), 2023. [arXiv version] [Conference paper]
20. [ACM TOIT 2023] FL4IoT: IoT Device Fingerprinting and Identification Using Federated Learning.
    Han Wang, David Eklund, Alina Oprea, and Shahid Raza. In ACM Transactions on Internet of Things, Volume 4, Issue 3, 2023. [Journal paper]
21. [PETS 2023] How to Combine Membership-Inference Attacks on Multiple Updated Models.
    Matthew Jagielski, Stanley Wu, Alina Oprea, Jonathan Ullman, and Roxana Geambasu. In Proceedings of the 23rd Privacy Enhancing Technologies Symposium (PETS), 2023.
    [arXiv version] [Conference paper]
22. [IEEE S&P 2023] SNAP: Efficient Extraction of Private Properties with Poisoning.
    Harsh Chaudhari, John Abascal, Alina Oprea, Matthew Jagielski, Florian Tramèr, and Jonathan Ullman. In Proceedings of the IEEE Symposium on Security and Privacy, 2023.
    [arXiv version] [Conference paper]
23. [ACM Computing Surveys 2023] Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning.
    Antonio Emanuele Cinà, Kathrin Grosse, Ambra Demontis, Sebastiano Vascon, Werner Zellinger, Bernhard A Moser, Alina Oprea, Battista Biggio, Marcello Pelillo, and Fabio Roli. In ACM Computing Surveys, 2023.
    [arXiv version] [Journal paper]
24. [SaTML 2023] SafeNet: Mitigating Data Poisoning Attacks on Private Machine Learning.
    Harsh Chaudhari, Matthew Jagielski, and Alina Oprea. In Proceedings of the IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), 2023.
    [arXiv version]
25. [ACSAC 2022] A Recent Year On the Internet: Measuring and Understanding the Threats to Everyday Internet Devices.
    Afsah Anwar, Yi Hui Chen, Roy Hodgman, Tom Sellers, Engin Kirda, and Alina Oprea.
    In Proceedings of Annual Computer Security Applications Conference (ACSAC), 2022 [Conference paper]
26. [IEEE Computer 2022] Poisoning Attacks Against Machine Learning: Can Machine Learning Be Trustworthy?
    Alina Oprea, Anoop Singhal, and Apostol Vassilev.
    In IEEE Computer, 2022 [PDF]
27. [IEEE CNS 2022] Network-Level Adversaries in Federated Learning
    Giorgio Severi, Matthew Jagielski, Gokberk Yar, Yuxuan Wang, Alina Oprea, Cristina Nita-Rotaru. In Proceedings of the IEEE Conference on Communications and Network Security (CNS), 2022. [arXiv version] [Conference paper] [Code]
28. [ESORICS 2022] Cyber Network Resilience against Self-Propagating Malware Attacks.
    Alesia Chernikova, Nicolò Gozzi, Simona Boboila, Priyanka Angadi, John Loughner, Matthew Wilden, Nicola Perra, Tina Eliassi-Rad, and Alina Oprea. In Proceedings of the 27th European Symposium on Research in Computer Security (ESORICS), 2022.
    [arXiv version][Conference paper] [Code]
29. [ACM TOPS 2022] FENCE: Feasible Evasion Attacks on Neural Networks in Constrained Environments.
    Alesia Chernikova and Alina Oprea. In ACM Transactions of Privacy and Security (TOPS), 2022.
    [arXiv version] [Journal paper]
30. [IEEE CSF 2022] Adversarial Robustness Verification and Attack Synthesis in Stochastic Systems.
    Lisa Oakley, Alina Oprea, and Stavros Tripakis. In Proceedings of the 35th IEEE Computer Security Foundations Symposium (CSF), 2022.
    [arXiv version]
31. [ACM CCS 2021] Subpopulation Data Poisoning Attacks.
    Matthew Jagielski, Giorgio Severi, Niklas Pousette-Harger, and Alina Oprea. In Proceedings of the ACM Conference on Computer and Communications Security (CCS), 2021.
    [arXiv version]
32. [ACM CCSW 2021] Private Hierarchical Clustering and Efficient Approximation.
    Xianrui Meng, Dimitrios Papadopoulos, Alina Oprea, and Nikos Triandopoulos. In Proceedings of the The ACM Cloud Computing Security Workshop (CCSW), 2021
    [arXiv version]
33. [MILCOM 2021] Poisoning Attacks and Data Sanitization Mitigations for Machine Learning Models in Network Intrusion Detection Systems.
    Sridhar Venkatesan, Harshvardhan Sikka, Rauf Izmailov, Ritu Chadha, Alina Oprea, and Michael J. De Lucia. In Proceedings of the Military Communications Conference (MILCOM), 2021.
34. [IEEE CNS 2021] PORTFILER: Port-Level Network Profiling for Self-Propagating Malware Detection
    Talha Ongun, Oliver Spohngellert, Benjamin Miller, Simona Boboila, Alina Oprea, Tina Eliassi-Rad, Jason Hiser, Alastair Nottingham, Jack Davidson, and Malathi Veeraraghavan. In Proceedings of the IEEE Conference on Communications and Network Security (CNS), 2021. [PDF]
35. [RAID 2021] Living-Off-The-Land Command Detection Using Active Learning.
    Talha Ongun, Jay Stokes, Jonathan Bar Or, Ke Tian, Farid Tajaddodianfar, Joshua Neil, Christian Seifert, Alina Oprea, John Platt. In Proceedings of the 24th International Symposium on Research in Attacks, Intrusions and Defenses (RAID), 2021 [PDF]
36. [USENIX Security 2021 (a)] Extracting Training Data from Large Language Models.
    Nicholas Carlini, Florian Tramèr, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom Brown, Dawn Song, Úlfar Erlingsson, Alina Oprea, and Colin Raffel. In Proceedings of the USENIX Security Symposium, 2021.
    [arXiv version] [Conference paper]
37. [USENIX Security 2021 (b)] Explanation-Guided Backdoor Poisoning Attacks Against Malware Classifiers.
    Giorgio Severi, Jim Meyer, Scott Coull, and Alina Oprea. In Proceedings of the USENIX Security Symposium, 2021.
    [arXiv version] [Code] [Conference paper]
38. [ACM TIFS 2021] With Great Dispersion Comes Greater Resilience: Efficient Poisoning Attacks and Defenses for Linear Regression Models.
    Jialin Wen, Benjamin Zi Hao Zhao, Minhui Xue, Alina Oprea, and Haifeng Qian. In ACM Transactions on Information Forensics and Security (TIFS) Journal, 2021.
    [arXiv version]
39. [DPML 2021] Does Differential Privacy Defeat Data Poisoning?
    Matthew Jagielski and Alina Oprea. In the Distributed and Private Machine Learning (DPML) Workshop at International Conference on Learning Representations (ICLR), 2021.
40. [AI4CS 2021 (a)] Collaborative Information Sharing for ML-Based Threat Detection.
    Talha Ongun, Simona Boboila, Alina Oprea, Tina Eliassi-Rad, Alastair Nottingham, Jason Hiser, and Jack Davidson. In AI/ML for Cybersecurity Workshop at SIAM International Conference on Data Mining (SDM), 2021.
    [arXiv version]
41. [AI4CS 2021 (b)] On Generating and Labeling Network Traffic with Realistic, Self-Propagating Malware.
    Molly Buchanan, Jeffrey W. Collyer, Jack W. Davidson, Saikat Dey, Mark Gardner, Jason D. Hiser, Jeffry Lang, Alastair Nottingham, and Alina Oprea. In AI/ML for Cybersecurity Workshop at SIAM International Conference on Data Mining (SDM), 2021.
    [arXiv version]
42. [NeurIPS 2020] Auditing Differentially Private Machine Learning: How Private is Private SGD?
    Matthew Jagielski, Jonathan Ullman, and Alina Oprea. In Proceedings of the 34th Conference on Neural Information Processing Systems (NeurIPS), 2020
    [arXiv version]
43. [FCS 2020] Adversarial Robustness of AI Agents Acting in Probabilistic Environments.
    Lisa Oakley, Alina Oprea, and Stavros Tripakis. In Workshop on Foundations of Computer Security (FCS), 2019. [PDF]
44. [RAID 2020] What’s in an Exploit? An Empirical Analysis of Reflected Server XSS Exploitation Techniques.
    Ahmet Salih Buyukkayhan, Can Gemicioglu, Tobias Lauinger, Alina Oprea, William Robertson, and Engin Kirda. In The 23rd International Symposium on Research in Attacks, Intrusions and Defenses (RAID), 2020. [PDF]
45. [RobustAI 2019] Subpopulation Data Poisoning Attacks.
    Matthew Jagielski, Paul Hand, and Alina Oprea. In NeurIPS 2019 Workshop on Robust AI in Financial Services, 2019. [PDF]
46. The House That Knows You: User Authentication Based on IoT Data.
    Talha Ongun, Oliver Spohngellert, Alina Oprea, Cristina Nita-Rotaru, Mihai Christodorescu, and Negin Salajegheh
    [arXiv version]
47. On Designing Machine Learning Models for Malicious Network Traffic Classification.
    Talha Ongun, Timothy Sakharaov, Simona Boboila, Alina Oprea, and Tina Eliassi-Rad
    [arXiv version]
48. [CCSW 2019] AppMine: Behavioral Analytics for Web Application Vulnerability Detection.
    Indranil Jana and Alina Oprea. In Proceedings of the The ACM Cloud Computing Security Workshop (CCSW), 2019.[arXiv version]
49. [GameSec 2019] QFlip: An Adaptive Reinforcement Learning Strategy for the FlipIt Security Game.
    Lisa Oakley and Alina Oprea. In Proceedings of the Conference on Decision and Game Theory for Security (GameSec), 2019. [arXiv version]. Received Outstanding Student Paper Award.
50. [USENIX Security 2019] Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks.
    Ambra Demontis, Marco Melis, Maura Pintor, Matthew Jagielski, Battista Biggio, Alina Oprea, Cristina Nita-Rotaru, and Fabio Roli.
    In Proceedings of the USENIX Security Symposium, 2019 [arXiv version]
51. [ICML 2019] Differentially Private Fair Learning.
    Matthew Jagielski, Michael Kearns, Jieming Mao, Alina Oprea, Aaron Roth, Saeed Sharifi-Malvajerdi, and Jonathan Ullman
    In Proceedings of the International Conference on Machine Learning (ICML), 2019 [arXiv version]
52. [SafeThings 2019] Are Self-Driving Cars Secure? Evasion Attacks against Deep Neural Networks for Self-Driving Cars.
    Alesia Chernikova, Alina Oprea, Cristina Nita-Rotaru, and BaekGyu Kim
    In Proceedings of the IEEE Workshop on the Internet of Safe Things, 2019 [arXiv version]
53. [BigData 2018] Automated Generation and Selection of Interpretable Features for Enterprise Security.
    Jiayi Duan, Ziheng Zeng, Alina Oprea, and Shobha Vasudevan
    In Proceedings of the IEEE International Conference on Big Data (IEEE BigData), 2018 [PDF]
54. [ACSAC 2018] MADE: Security Analytics for Enterprise Threat Detection.
    Alina Oprea, Zhou Li, Robin Norris, and Kevin Bowers
    In Proceedings of Annual Computer Security Applications Conference (ACSAC), 2018 [PDF]
55. [ACM CCS 2018, Poster] The House That Knows You: User Authentication Based on IoT Data.
    Talha Ongun, Alina Oprea, Cristina Nita-Rotaru, Mihai Christodorescu, and Negin Salajegheh.
    Poster at the ACM Conference on Computer and Communications Security (CCS), 2018 [PDF]
56. [IEEE S&P 2018] Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning.
    Matthew Jagielski, Alina Oprea, Battista Biggio, Chang Liu, Cristina Nita-Rotaru, and Bo Li
    In Proceedings of the IEEE Symposium on Security and Privacy, 2018. [PDF]
57. [PSBD 2017] User-Profile-Based Analytics for Detecting Cloud Security Breaches.
    Trishita Tiwari, Ata Turk, Alina Oprea, Katzalin Olcoz, and Ayse K. Coskun
    In Proceedings of the 4th International Workshop on Privacy and Security of Big Data (PSBD), 2017 [PDF]
58. [AISEC 2017] Robust Linear Regression Against Training Data Poisoning.
    Chang Liu, Bo Li, Yevgeniy Vorobeychik, and Alina Oprea.
    In Proceedings of 10th ACM Workshop on Artificial Intelligence and Security (AISEC), 2017 Best paper award. [PDF]
59. [RAID 2017] Lens on the endpoint: Hunting for malicious software through endpoint data analysis.
    Ahmet Buyukkayhan, Alina Oprea, Zhou Li, and William Robertson.
    In Proceedings of Recent Advances in Intrusion Detection (RAID), 2017 [PDF]
60. [ACSAC 2016] Catching Predators at Watering Holes: Finding and Understanding Strategically Compromised Websites.
    Sumayah Alrwais, Kan Yuan, Eihal Alowaisheq, Xiaojing Liao, Alina Oprea, Xiaofeng Wang and Zhou Li
    In Proceedings of Annual Computer Security Applications Conference (ACSAC), 2016 [PDF]
61. [SecDev 2016] Operational security log analytics for enterprise breach detection.
    Zhou Li and Alina Oprea
    In Proceedings of the First IEEE Cybersecurity Development Conference (SecDev), 2016 [PDF]
62. [SecDev 2016] MOSAIC: A Platform for Monitoring and Anomaly Detection in Cloud Computing.
    Alina Oprea, Ata Turk, Cristina Nita-Rotaru and Orran Krieger
    In First IEEE Cybersecurity Development Conference (SecDev), 2016. Short paper. [PDF]
63. [DSN 2015] Detection of Early-Stage Enterprise Infection by Mining Large-Scale Log Data.
    Alina Oprea, Zhou Li, Ting-Fang Yen, Sang H. Chin, and Sumyah Alrwais
    In Proceedings of IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), 2015 [PDF]
64. [CCS 2014] An Epidemiological Study of Malware Encounters in a Large Enterprise.
    Ting-Fang Yen, Victor Heorhiadi, Alina Oprea, Michael K. Reiter, and Ari Juels
    In Proceedings of ACM Conference on Computer and Communications Security (CCS), 2014 [PDF]
65. [ACSAC 2013] Beehive: Large-Scale Log Analysis for Detecting Suspicious Activity in Enterprise Networks.
    Ting-Fang Yen, Alina Oprea, Kaan Onarlioglu, Todd Leetham, William Robertson, Ari Juels, and Engin Kirda
    In Proceedings of Annual Computer Security Applications Conference (ACSAC), 2013 [PDF]
66. [Journal of Cryptology 2013] FlipIt: The Game of Stealthy Takeover.
    Marten van Dijk, Ari Juels, Alina Oprea, and Ronald L. Rivest
    In Journal of Cryptology, volume 26, issue 4, pages 655-713, 2013 [PDF]
67. [CACM 2013] New Approaches to Security and Availability for Cloud Data.
    Ari Juels and Alina Oprea
    In Communications of the ACM (CACM) volume 56, issue 2, pages 64-73, 2013 [PDF]
68. [ACSAC 2012] Iris: A Scalable Cloud File System with Efficient Integrity Checks.
    Emil Stefanov, Marten van Dijk, Alina Oprea, and Ari Juels
    In Proceedings of Annual Computer Security Applications Conference (ACSAC) , 2013 [PDF]
69. [CCS 2012] Hourglass Schemes: How to Prove that Cloud Files Are Encrypted.
    Marten van Dijk, Ari Juels, Alina Oprea, Ronald L. Rivest, Emil Stefanov, and Nikos Triandopoulos
    In Proceedings of ACM Conference on Computer and Communications Security (CCS), 2012 [PDF]
70. [GameSec 2012] Defending Against the Unknown Enemy: Applying FlipIt to System Security.
    Kevin D. Bowers, Marten van Dijk, Robert Griffin, Ari Juels, Alina Oprea, Ronald L. Rivest, and Nikos Triandopoulos
    In Proceedings of Conference on Decision and Game Theory for Security (GameSec), 2012 [PDF]
71. [DSN 2012] Practical Scrubbing: Getting to the Bad Sector at the Right Time.
    George Amvrosiadis, Bianca Schroeder, and Alina Oprea
    In Proceedings of IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), 2012 [PDF]
72. [ACM ToS 2012] Efficient Implementation of Large Finite Fields GF(2^n) for Secure Storage Applications.
    Jianqiang Luo, Kevin D. Bowers, Alina Oprea, and Lihao Xu
    In ACM Transactions on Storage, volume 8, issue 1, pages 1-27, 2012 [PDF]
73. [CCS 2011] How to Tell if Your Cloud Files Are Vulnerable to Drive Crashes.
    Kevin D. Bowers, Marten van Dijk, Ari Juels, Alina Oprea, and Ronald L. Rivest
    In Proceedings of ACM Conference on Computer and Communications Security (CCS), 2011 [PDF]
74. [IEEE S&P 2011] HomeAlone: Co-Residency Detection in the Cloud via Side-Channel Analysis.
    Yinqian Zhang, Ari Juels, Alina Oprea, and Michael K. Reiter
    In Proceedings of IEEE Symposium on Security and Privacy (S&P), 2011 [PDF]
75. [FAST 2010] A Clean-Slate Look at Disk Scrubbing.
    Alina Oprea and Ari Juels
    In Proceedings of USENIX Conference on File and Storage Technologies (FAST), 2010 [PDF]
76. [CCS 2009] HAIL: A High-Availability and Integrity Layer for Cloud Storage.
    Kevin D. Bowers, Ari Juels, and Alina Oprea
    In Proceedings of ACM Conference on Computer and Communications Security (CCS), 2009 [PDF]
77. [CCSW 2009] Proofs of Retrievability: Theory and Implementation.
    Kevin D. Bowers, Ari Juels, and Alina Oprea
    In Proceedings of ACM Cloud Computing Security Workshop (CCSW), [PDF]
78. [ESORICS 2009] Authentic Time-Stamps for Archival Storage.
    Alina Oprea and Kevin D. Bowers
    In Proceedings of European Symposium on Research in Computer Security (ESORICS), 2009 [PDF]
79. [USENIX Security 2007] Integrity Checking in Cryptographic File Systems with Constant Trusted Storage.
    Alina Oprea and Michael K. Reiter
    In Proceedings of USENIX Security Symposium (SECURITY), 2007 [PDF]
80. [DISC 2006] On Consistency of Encrypted Files.
    Alina Oprea and Michael K. Reiter
    In Proceedings of Symposium on Distributed Computing (DISC), 2006 [PDF]
81. [ESORICS 2006] Secure Key-Updating for Lazy Revocation.
    Michael Backes, Christian Cachin, and Alina Oprea
    In Proceedings of European Symposium on Research in Computer Security (ESORICS), 2009 [PDF]
82. [SISW 2005] Lazy Revocation in Cryptographic File Systems.
    Michael Backes, Christian Cachin, and Alina Oprea
    In Proceedings of IEEE Security in Storage Workshop (SISW), 2005 [PDF]
83. [NDSS 2005] Space-Efficient Block Storage Integrity.
    Alina Oprea, Michael K. Reiter, and Ke Yang
    In Proceedings of Network and Distributed System Security Symposium (NDSS), 2005. Best paper award. [PDF]
84. [ACSAC 2004] Securing a Remote Terminal Application with a Mobile Trusted Device.
    Alina Oprea, Dirk Balfanz, Glenn Durfee, and Diana K. Smetters
    In Proceedings of Annual Computer Security Applications Conference (ACSAC), 2004 [PDF]
85. [ACNS 2004] Private Keyword-Based Push and Pull with Applications to Anonymous Communication.
    Lea Kissner, Alina Oprea, Michael K. Reiter, Dawn Song, and Ke Yang
    In Proceedings of Applied Cryptography and Network Security Conference (ACNS), 2004 [PDF]
86. [CCS 2003] Automatic Generation of Two-Party Computations.
    Philip MacKenzie, Alina Oprea, and Michael K. Reiter
    In Proceedings of ACM Conference on Computer and Communications Security (CCS), 2003 [PDF]

Theses

87. [Ph.D. Thesis 2007] Efficient Cryptographic Techniques for Securing Storage Systems.
    Alina Oprea
    Carnegie Mellon University, Technical Report CMU-CS-07-119, May 2007 [PDF]

Other

88. [NetSci 2019] Detecting Self-Propagating Attacks in Cyber Networks.
    Timothy A Sakharov and Benjamin Miller and Talha Ongun and Alina Oprea and Tina Eliassi-Rad.
    In The International Conference on Network Science (NetSci’19), oral presentation, 2019
89. [Security Brief 2011] Mobilizing Intelligent Security Operations for Advanced Persistent Threats.
    Sam Curry, Bret Hartman, David P. Hunter, David Martin, Dennis R. Moreau, Alina Oprea, Uri Rivner, and Dana E. Wolf
    RSA Security Brief, February 2011