78 citations · 112 across the 10 of their papers we have counts for
10 papers
Benchmarking the Benchmarks: Evaluating Benchmarks for Conversational Agents
Noam Koren, Roy Bar-Haim, Abigail Goldsteen
Task-oriented conversational agents are evaluated using curated or automatically generated benchmarks, yet benchmark quality is rarely assessed. Poor benchmarks may contain inconsi…
Membership Inference Attacks Against Time-Series Models
Noam Koren, Abigail Goldsteen, Guy Amit +1
Analyzing time-series data that contains personal information, particularly in the medical field, presents serious privacy concerns. Sensitive health data from patients is often us…
Is My Data in Your Retrieval Database? Membership Inference Attacks Against Retrieval Augmented Generation
Maya Anderson, Guy Amit, Abigail Goldsteen
Retrieval Augmented Generation (RAG) systems have shown great promise in natural language processing. However, their reliance on data stored in a retrieval database, which may cont…
SoK: Reducing the Vulnerability of Fine-tuned Language Models to Membership Inference Attacks
Guy Amit, Abigail Goldsteen, Ariel Farkash
Natural language processing models have experienced a significant upsurge in recent years, with numerous applications being built upon them. Many of these applications require fine…
Improved Membership Inference Attacks Against Language Classification Models
Shlomit Shachor, Natalia Razinkov, Abigail Goldsteen
Artificial intelligence systems are prevalent in everyday life, with use cases in retail, manufacturing, health, and many other fields. With the rise in AI adoption, associated ris…
Data Minimization for GDPR Compliance in Machine Learning Models
Abigail Goldsteen, Gilad Ezov, Ron Shmelkin +2
The EU General Data Protection Regulation (GDPR) mandates the principle of data minimization, which requires that only data necessary to fulfill a certain purpose be collected. How…
Anonymizing Machine Learning Models
Abigail Goldsteen, Gilad Ezov, Ron Shmelkin +2
There is a known tension between the need to analyze personal data to drive business and privacy concerns. Many data protection regulations, including the EU General Data Protectio…
Reducing Risk of Model Inversion Using Privacy-Guided Training
Abigail Goldsteen, Gilad Ezov, Ariel Farkash
Machine learning models often pose a threat to the privacy of individuals whose data is part of the training set. Several recent attacks have been able to infer sensitive informati…
Forgotten @ Scale: A Practical Solution for Implementing the Right To Be Forgotten in Large-Scale Systems
Abigail Goldsteen, Tomer Douek, Yaniv Cohen +5
The European General Data Protection Regulation asserts data subjects' right to be forgotten, i.e., their right to request that all their personal data be deleted from an organizat…
Proceedings of the Ninth Workshop on Web 2.0 Security and Privacy (W2SP) 2015
Abigail Goldsteen, Tyrone Grandison, Mike Just +3
This is the Proceedings of the Ninth Workshop on Web 2.0 Security and Privacy (W2SP) 2015, held in San Jose, CA, USA, on May 21, 2015. The workshop was held as part of the IEEE Com…