activity
20122026
most citedConAML: Constrained Adversarial Machine Learning for Cyber-Physical Systems

18 citations · 46 across the 11 of their papers we have counts for

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Showing cs.CRShow all

9 papers · 1 filter

cs.CR2024★ 5 cited

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…

cs.CR2023

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…

cs.CR2023★ 1 cited

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…

cs.CR2021★ 8 cited

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)…

cs.CR2020★ 9 cited

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…

cs.CR2020

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…

cs.CR2020★ 2 cited

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…

cs.CR2020★ 18 cited

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…

cs.CR2018

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…