Xiaofei Xie · PaperMetrix

FESR: A Framework for Eliciting Security Requirements Based on Integration of Common Criteria and Weakness Detection Formal Model

2017

It is critical and foremost to come up with the corresponding security requirements first which the following implementations are based on. However, previous security requirement elicitation work based on Common Criteria (CC) rarely addresses the …

Stealing Deep Reinforcement Learning Models for Fun and Profit

2020 · arXiv (Cornell University)

This paper presents the first model extraction attack against Deep Reinforcement Learning (DRL), which enables an external adversary to precisely recover a black-box DRL model only from its interaction with the environment. Model extraction attacks …

Have Your Cake and Eat It Too: Toward Efficient and Accurate Split Federated Learning

2023 · arXiv (Cornell University)

Due to its advantages in resource constraint scenarios, Split Federated Learning (SFL) is promising in AIoT systems. However, due to data heterogeneity and stragglers, SFL suffers from the challenges of low inference accuracy and low …

Adversarial Learning for Coordinate Regression Through k-Layer Penetrating Representation

2024 · IEEE Transactions on Dependable and Secure Computing

Adversarial attack is a crucial step when evaluating the reliability and robustness of deep neural networks (DNNs) models. Most existing attack approaches apply an end-to-end gradient update strategy to generate adversarial examples for a classification …

NebulaFL: Effective Asynchronous Federated Learning for JointCloud Computing

2024 · arXiv (Cornell University)

With advancements in AI infrastructure and Trusted Execution Environment (TEE) technology, Federated Learning as a Service (FLaaS) through JointCloud Computing (JCC) is promising to break through the resource constraints caused by heterogeneous edge devices in …

SpecGen: Automated Generation of Formal Program Specifications via Large Language Models

2025