Search Results for author: Y. Thomas Hou

Found 5 papers, 1 papers with code

Learning-augmented Online Minimization of Age of Information and Transmission Costs

no code implementations5 Mar 2024 Zhongdong Liu, Keyuan Zhang, Bin Li, Yin Sun, Y. Thomas Hou, Bo Ji

To address this challenge, we develop a robust online algorithm to minimize the sum of transmission and staleness costs, ensuring a worst-case performance guarantee.

Scale-MIA: A Scalable Model Inversion Attack against Secure Federated Learning via Latent Space Reconstruction

no code implementations10 Nov 2023 Shanghao Shi, Ning Wang, Yang Xiao, Chaoyu Zhang, Yi Shi, Y. Thomas Hou, Wenjing Lou

Unlike existing approaches treating models as black boxes, Scale-MIA recognizes the importance of the intricate architecture and inner workings of machine learning models.

Federated Learning

CANShield: Deep Learning-Based Intrusion Detection Framework for Controller Area Networks at the Signal-Level

1 code implementation3 May 2022 Md Hasan Shahriar, Yang Xiao, Pablo Moriano, Wenjing Lou, Y. Thomas Hou

As ordinary injection attacks disrupt the typical timing properties of the CAN data stream, rule-based intrusion detection systems (IDS) can easily detect them.

Intrusion Detection Time Series +1

AoI-minimizing Scheduling in UAV-relayed IoT Networks

no code implementations12 Jul 2021 Biplav Choudhury, Vijay K. Shah, Aidin Ferdowsi, Jeffrey H. Reed, Y. Thomas Hou

Our simulation results show that DQN-based scheduler outperforms MAF-MAD scheduler and three other baseline schedulers, i. e., Maximal AoI First (MAF), Round Robin (RR) and Random, employed at both hops under general conditions when the network is small (with 10's of IoT devices).

Scheduling

Enjoy the Untrusted Cloud: A Secure, Scalable and Efficient SQL-like Query Framework for Outsourcing Data

no code implementations18 Dec 2019 Yaxing Chen, Qinghua Zheng, Dan Liu, Zheng Yan, Wenhai Sun, Ning Zhang, Wenjing Lou, Y. Thomas Hou

On one hand, such work lacks of supporting scalable access control over multiple data users.

Cryptography and Security Databases Distributed, Parallel, and Cluster Computing

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