32 citations · 91 across the 60 of their papers we have counts for
38 papers · 1 filter
SoK: Privacy Attacks on Machine Learning via Explainable AI
Abdullah Caglar Oksuz, Anisa Halimi, Erman Ayday
Machine learning explanations reveal model behavior beyond predictions, creating attack surfaces for model confidentiality and data privacy. We systematize 25 studies that exploit…
The End of Trust: How Agentic AI Breaks Security Assumptions
Osama Zafar, Alexander Nemecek, Erman Ayday
For decades, the security of digital interaction has rested on an unacknowledged economic constraint. Attackers faced a tradeoff between the fidelity of a deception and the scale a…
Authenticated Contradictions from Desynchronized Provenance and Watermarking
Alexander Nemecek, Hengzhi He, Guang Cheng +1
Cryptographic provenance standards such as C2PA and invisible watermarking are positioned as complementary defenses for content authentication, yet the two verification layers are…
Neighborhood Blending: A Lightweight Inference-Time Defense Against Membership Inference Attacks
Osama Zafar, Shaojie Zhan, Tianxi Ji +1
In recent years, the widespread adoption of Machine Learning as a Service (MLaaS), particularly in sensitive environments, has raised considerable privacy concerns. Of particular i…
Privacy-Preserving AI-Enabled Decentralized Learning and Employment Records System
Yuqiao Xu, Mina Namazi, Sahith Reddy Jalapally +3
Learning and Employment Record (LER) systems are emerging as critical infrastructure for securely compiling and sharing educational and work achievements. Existing blockchain-based…
Digital Agriculture Sandbox for Collaborative Research
Osama Zafar, Rosemarie Santa González, Alfonso Morales +1
Digital agriculture is transforming the way we grow food by utilizing technology to make farming more efficient, sustainable, and productive. This modern approach to agriculture ge…
Exploring Membership Inference Vulnerabilities in Clinical Large Language Models
Alexander Nemecek, Zebin Yun, Zahra Rahmani +4
As large language models (LLMs) become progressively more embedded in clinical decision-support, documentation, and patient-information systems, ensuring their privacy and trustwor…
Empowering Digital Agriculture: A Privacy-Preserving Framework for Data Sharing and Collaborative Research
Osama Zafar, Rosemarie Santa González, Mina Namazi +2
Data-driven agriculture, which integrates technology and data into agricultural practices, has the potential to improve crop yield, disease resilience, and long-term soil health. H…
A User-Centric, Privacy-Preserving, and Verifiable Ecosystem for Personal Data Management and Utilization
Osama Zafar, Mina Namazi, Yuqiao Xu +2
In the current paradigm of digital personalized services, the centralized management of personal data raises significant privacy concerns, security vulnerabilities, and diminished…
ZKPROV: A Zero-Knowledge Approach to Dataset Provenance for Large Language Models
Mina Namazi, Alexander Nemecek, Erman Ayday
As large language models (LLMs) are used in sensitive fields, accurately verifying their computational provenance without disclosing their training datasets poses a significant cha…
Watermarking Without Standards Is Not AI Governance
Alexander Nemecek, Yuzhou Jiang, Erman Ayday
Watermarking has emerged as a leading technical proposal for attributing generative AI content and is increasingly cited in global governance frameworks. This position paper argues…
The Feasibility of Topic-Based Watermarking on Academic Peer Reviews
Alexander Nemecek, Yuzhou Jiang, Erman Ayday
Large language models (LLMs) are increasingly integrated into academic workflows, with many conferences and journals permitting their use for tasks such as language refinement and…
Privacy-Preserving Collaborative Genomic Research: A Real-Life Deployment and Vision
Zahra Rahmani, Nahal Shahini, Nadav Gat +7
The data revolution holds significant promise for the health sector. Vast amounts of data collected from individuals will be transformed into knowledge, AI models, predictive syste…
Topic-Based Watermarks for Large Language Models
Alexander Nemecek, Yuzhou Jiang, Erman Ayday
The indistinguishability of large language model (LLM) output from human-authored content poses significant challenges, raising concerns about potential misuse of AI-generated text…
zkFaith: Soonami's Zero-Knowledge Identity Protocol
Mina Namazi, Duncan Ross, Xiaojie Zhu +1
Individuals are encouraged to prove their eligibility to access specific services regularly. However, providing various organizations with personal data spreads sensitive informati…
Privacy-Preserving Link Prediction
Didem Demirag, Mina Namazi, Erman Ayday +1
Consider two data holders, ABC and XYZ, with graph data (e.g., social networks, e-commerce, telecommunication, and bio-informatics). ABC can see that node A is linked to node B, an…
PROVGEN: A Privacy-Preserving Approach for Outcome Validation in Genomic Research
Yuzhou Jiang, Tianxi Ji, Erman Ayday
As genomic research has grown increasingly popular in recent years, dataset sharing has remained limited due to privacy concerns. This limitation hinders the reproducibility and va…
Robust Fingerprinting of Genomic Databases
Tianxi Ji, Erman Ayday, Emre Yilmaz +1
Database fingerprinting has been widely used to discourage unauthorized redistribution of data by providing means to identify the source of data leakages. However, there is no fing…
Robust Fingerprint of Location Trajectories Under Differential Privacy
Yuzhou Jiang, Emre Yilmaz, Erman Ayday
Directly releasing those data raises privacy and liability (e.g., due to unauthorized distribution of such datasets) concerns since location data contain users' sensitive informati…
Facilitating Federated Genomic Data Analysis by Identifying Record Correlations while Ensuring Privacy
Leonard Dervishi, Xinyue Wang, Wentao Li +4
With the reduction of sequencing costs and the pervasiveness of computing devices, genomic data collection is continually growing. However, data collection is highly fragmented and…
Privacy-Preserving Database Fingerprinting
Tianxi Ji, Erman Ayday, Emre Yilmaz +1
When sharing sensitive relational databases with other parties, a database owner aims to (i) have privacy guarantees for the database entries, (ii) have liability guarantees (via f…
Privacy-Preserving Identification of Target Patients from Outsourced Patient Data
Xiaojie Zhu, Erman Ayday, Roman Vitenberg
With the increasing affordability and availability of patient data, hospitals tend to outsource their data to cloud service providers (CSPs) for the purpose of storage and analytic…
Near-Optimal Privacy-Utility Tradeoff in Genomic Studies Using Selective SNP Hiding
Nour Almadhoun Alserr, Gulce Kale, Onur Mutlu +2
Motivation: Researchers need a rich trove of genomic datasets that they can leverage to gain a better understanding of the genetic basis of the human genome and identify associatio…
The Curse of Correlations for Robust Fingerprinting of Relational Databases
Tianxi Ji, Emre Yilmaz, Erman Ayday +1
Database fingerprinting have been widely adopted to prevent unauthorized sharing of data and identify the source of data leakages. Although existing schemes are robust against comm…