18 citations · 55 across the 20 of their papers we have counts for
21 papers
IntraShuffler: A Privacy Preserving Framework for Heterogeneous DP Federated Learning
Farhin Farhad Riya, Olivera Kotevska, Jinyuan Stella Sun
Heterogeneous Differential Privacy (HDP) in Federated Learning (FL) allows clients to select individual privacy budgets () according to institutional policies and da…
Pseudo-Feature Padding: A Lightweight Defense Against False Data Injection in Power Grids
Farhin Farhad Riya, Shahinul Hoque, Yingyuan Yang +2
Deep Neural Networks DNNs have achieved remarkable accuracy in various tasks including their application in CyberPhysical Systems CPS for detecting False Data Injection Attacks FDI…
Token Inflation: How Dishonest Providers Can Overcharge for Large Language Model Usage
Shahinul Hoque, Jinghuai Zhang, Jinyuan Sun +1
Per-token billing is now the standard pricing model for commercial large language models (LLMs), so the honesty of reported token counts directly affects what users pay. We show th…
Accuracy is Not Enough: Poisoning Interpretability in Federated Learning via Color Skew
Farhin Farhad Riya, Shahinul Hoque, Jinyuan Stella Sun +1
As machine learning models are increasingly deployed in safety-critical domains, visual explanation techniques have become essential tools for supporting transparency. In this work…
Risks of Practicing Large Language Models in Smart Grid: Threat Modeling and Validation
Jiangnan Li, Yingyuan Yang, Jinyuan Sun
Large language models (LLMs) represent significant breakthroughs in artificial intelligence and hold potential for applications within smart grids. However, as demonstrated in prev…
Smart Driver Monitoring Robotic System to Enhance Road Safety : A Comprehensive Review
Farhin Farhad Riya, Shahinul Hoque, Xiaopeng Zhao +1
The future of transportation is being shaped by technology, and one revolutionary step in improving road safety is the incorporation of robotic systems into driver monitoring infra…
HRI Challenges Influencing Low Usage of Robotic Systems in Disaster Response and Rescue Operations
Shahinul Hoque, Farhin Farhad Riya, Jinyuan Sun
The breakthrough in AI and Machine Learning has brought a new revolution in robotics, resulting in the construction of more sophisticated robotic systems. Not only can these roboti…
Graph Neural Network Framework for Security Assessment Informed by Topological Measures
Mojtaba Dezvarei, Kevin Tomsovic, Jinyuan Stella Sun +1
In the power system, security assessment (SA) plays a pivotal role in determining the safe operation in a normal situation and some contingencies scenarios. Electrical variables as…
Mitigating Adversarial Effects of False Data Injection Attacks in Power Grid
Farhin Farhad Riya, Shahinul Hoque, Yingyuan Yang +3
Deep Neural Networks have proven to be highly accurate at a variety of tasks in recent years. The benefits of Deep Neural Networks have also been embraced in power grids to detect…
Deep Learning model integrity checking mechanism using watermarking technique
Shahinul Hoque, Farhin Farhad Riya, Yingyuan Yang +1
In response to the growing popularity of Machine Learning (ML) techniques to solve problems in various industries, various malicious groups have started to target such techniques i…
Exploring Physical-Based Constraints in Short-Term Load Forecasting: A Defense Mechanism Against Cyberattack
Mojtaba Dezvarei, Kevin Tomsovic, Jinyuan Stella Sun +1
Short-term load forecasting is an essential task that supports utilities to schedule generating sufficient power for balancing supply and demand, and can become an attractive targe…
Towards Adversarial-Resilient Deep Neural Networks for False Data Injection Attack Detection in Power Grids
Jiangnan Li, Yingyuan Yang, Jinyuan Stella Sun +2
False data injection attacks (FDIAs) pose a significant security threat to power system state estimation. To detect such attacks, recent studies have proposed machine learning (ML)…
Latent Group Structured Multi-task Learning
Xiangyu Niu, Yifan Sun, Jinyuan Sun
In multi-task learning (MTL), we improve the performance of key machine learning algorithms by training various tasks jointly. When the number of tasks is large, modeling task stru…
Exploiting Vulnerabilities of Deep Learning-based Energy Theft Detection in AMI through Adversarial Attacks
Jiangnan Li, Yingyuan Yang, Jinyuan Stella Sun
Effective detection of energy theft can prevent revenue losses of utility companies and is also important for smart grid security. In recent years, enabled by the massive fine-grai…
BubbleMap: Privilege Mapping for Behavior-based Implicit Authentication Systems
Yingyuan Yang, Xueli Huang, Jiangnan Li +1
Leveraging users' behavioral data sampled by various sensors during the identification process, implicit authentication (IA) relieves users from explicit actions such as rememberin…
EchoIA: Implicit Authentication System Based on User Feedback
Yingyuan Yang, Xueli Huang, Jiangnan Li +1
Implicit authentication (IA) transparently authenticates users by utilizing their behavioral data sampled from various sensors. Identifying the illegitimate user through constantly…
SearchFromFree: Adversarial Measurements for Machine Learning-based Energy Theft Detection
Jiangnan Li, Yingyuan Yang, Jinyuan Stella Sun
Energy theft causes large economic losses to utility companies around the world. In recent years, energy theft detection approaches based on machine learning (ML) techniques, espec…
ConAML: Constrained Adversarial Machine Learning for Cyber-Physical Systems
Jiangnan Li, Yingyuan Yang, Jinyuan Stella Sun +2
Recent research demonstrated that the superficially well-trained machine learning (ML) models are highly vulnerable to adversarial examples. As ML techniques are becoming a popular…
Dynamic Detection of False Data Injection Attack in Smart Grid using Deep Learning
Xiangyu Niu Jiangnan Li, Jinyuan Sun
Modern advances in sensor, computing, and communication technologies enable various smart grid applications. The heavy dependence on communication technology has highlighted the vu…
A Practical Searchable Symmetric Encryption Scheme for Smart Grid Data
Jiangnan Li, Xiangyu Niu, Jinyuan Stella Sun
Outsourcing data storage to the remote cloud can be an economical solution to enhance data management in the smart grid ecosystem. To protect the privacy of data, the utility compa…
Dynamic Multi-level Privilege Control in Behavior-based Implicit Authentication Systems Leveraging Mobile Devices
Yingyuan Yang, Xueli Huang, Yanhui Guo +1
Implicit authentication (IA) is gaining popularity over recent years due to its use of user behavior as the main input, relieving users from explicit actions such as remembering an…