8 citations · 13 across the 5 of their papers we have counts for
11 papers
Exploring Adversarial Examples for Efficient Active Learning in Machine Learning Classifiers
Honggang Yu, Shihfeng Zeng, Teng Zhang +2
Machine learning researchers have long noticed the phenomenon that the model training process will be more effective and efficient when the training samples are densely sampled aro…
CHIMERA: A Hybrid Estimation Approach to Limit the Effects of False Data Injection Attacks
Xiaorui Liu, Yaodan Hu, Charalambos Konstantinou +1
The reliable operation of power grid is supported by energy management systems (EMS) that provide monitoring and control functionalities. Contingency analysis is a critical applica…
A Survey of Machine Learning Methods for Detecting False Data Injection Attacks in Power Systems
Ali Sayghe, Yaodan Hu, Ioannis Zografopoulos +4
Over the last decade, the number of cyberattacks targeting power systems and causing physical and economic damages has increased rapidly. Among them, False Data Injection Attacks (…
On the (In)security of Bluetooth Low Energy One-Way Secure Connections Only Mode
Yue Zhang, Jian Weng, Rajib Dey +3
To defeat security threats such as man-in-the-middle (MITM) attacks, Bluetooth Low Energy (BLE) 4.2 and 5.x introduce the Secure Connections Only mode, under which a BLE device acc…
RTL-PSC: Automated Power Side-Channel Leakage Assessment at Register-Transfer Level
Miao, He, Jungmin Park +4
Power side-channel attacks (SCAs) have become a major concern to the security community due to their non-invasive feature, low-cost, and effectiveness in extracting secret informat…
IoT Security: An End-to-End View and Case Study
Zhen Ling, Kaizheng Liu, Yiling Xu +5
In this paper, we present an end-to-end view of IoT security and privacy and a case study. Our contribution is three-fold. First, we present our end-to-end view of an IoT system an…