Alina Oprea

The House That Knows You: User Authentication Based on IoT Data

2019 · arXiv (Cornell University)

Home-based Internet of Things (IoT) devices have gained in popularity and many households have become 'smart' by using devices such as smart sensors, locks, and voice-based assistants. Traditional authentication methods such as passwords, biometrics or …

Network-Level Adversaries in Federated Learning

2022 · arXiv (Cornell University)

Federated learning is a popular strategy for training models on distributed, sensitive data, while preserving data privacy. Prior work identified a range of security threats on federated learning protocols that poison the data or the …

Dropout Attacks

2023 · arXiv (Cornell University)

Dropout is a common operator in deep learning, aiming to prevent overfitting by randomly dropping neurons during training. This paper introduces a new family of poisoning attacks against neural networks named DROPOUTATTACK. DROPOUTATTACK attacks the …

User Inference Attacks on Large Language Models

2023 · arXiv (Cornell University)

Fine-tuning is a common and effective method for tailoring large language models (LLMs) to specialized tasks and applications. In this paper, we study the privacy implications of fine-tuning LLMs on user data. To this end, …