19 citations · 20 across the 11 of their papers we have counts for
12 papers
CPInj: Uncovering Prompt Injection Risks in Textual Collaborative Prompt Optimization
Xinting Liao, Behnoosh Zamanlooy, Masoumeh Shafieinejad +4
Textual Collaborative Prompt Optimization (TCPO) extends TextGrad (Yuksekgonul et al., 2025) to a decentralized setting by allowing multiple clients to jointly improve prompts for…
FERMI: Exploiting Relations for Membership Inference Against Tabular Diffusion Models
Abtin Mahyar, Masoumeh Shafieinejad, Yuhan Liu +1
Diffusion models are the leading approach for tabular data synthesis and are increasingly used to share sensitive records. Whether they actually protect privacy has become a pressi…
On Privacy in Data-Space Tabular Diffusion Models: Influential Factors, Attacker Knowledge, and Metrics
Masoumeh Shafieinejad, D. B. Emerson, Behnoosh Zamanlooy +5
Tabular data plays an important role in many fields and industries, including those with elevated privacy considerations and risks. As such, there is a rising interest in generatin…
MIDST Challenge at SaTML 2025: Membership Inference over Diffusion-models-based Synthetic Tabular data
Masoumeh Shafieinejad, Xi He, Mahshid Alinoori +6
Synthetic data is often perceived as a silver-bullet solution to data anonymization and privacy-preserving data publishing. Drawn from generative models like diffusion models, synt…
CAPID: Context-Aware PII Detection for Question-Answering Systems
Mariia Ponomarenko, Sepideh Abedini, Masoumeh Shafieinejad +3
Detecting personally identifiable information (PII) in user queries is critical for ensuring privacy in question-answering systems. Current approaches mainly redact all PII, disreg…
MaskSQL: Safeguarding Privacy for LLM-Based Text-to-SQL via Abstraction
Sepideh Abedini, Shubhankar Mohapatra, D. B. Emerson +3
Large language models (LLMs) have shown promising performance on tasks that require reasoning, such as text-to-SQL, code generation, and debugging. However, regulatory frameworks w…
Adopt a PET! An Exploration of PETs, Policy, and Practicalities for Industry in Canada
Masoumeh Shafieinejad, Xi He, Bailey Kacsmar
Privacy is an instance of a social norm formed through legal, technical, and cultural dimensions. Institutions such as regulators, industry, and researchers act as societal agents…
ClavaDDPM: Multi-relational Data Synthesis with Cluster-guided Diffusion Models
Wei Pang, Masoumeh Shafieinejad, Lucy Liu +2
Recent research in tabular data synthesis has focused on single tables, whereas real-world applications often involve complex data with tens or hundreds of interconnected tables. P…
On Privacy and Confidentiality of Communications in Organizational Graphs
Masoumeh Shafieinejad, Huseyin Inan, Marcello Hasegawa +1
Machine learned models trained on organizational communication data, such as emails in an enterprise, carry unique risks of breaching confidentiality, even if the model is intended…
Equi-Joins Over Encrypted Data for Series of Queries
Masoumeh Shafieinejad, Suraj Gupta, Jin Yang Liu +2
Encryption provides a method to protect data outsourced to a DBMS provider, e.g., in the cloud. However, performing database operations over encrypted data requires specialized enc…
PCOR: Private Contextual Outlier Release via Differentially Private Search
Masoumeh Shafieinejad, Florian Kerschbaum, Ihab F. Ilyas
Outlier detection plays a significant role in various real world applications such as intrusion, malfunction, and fraud detection. Traditionally, outlier detection techniques are a…
On the Robustness of the Backdoor-based Watermarking in Deep Neural Networks
Masoumeh Shafieinejad, Jiaqi Wang, Nils Lukas +2
Obtaining the state of the art performance of deep learning models imposes a high cost to model generators, due to the tedious data preparation and the substantial processing requi…