most citedMisbehavior Detection Using Collective Perception under Privacy Considerations

1 citations · 1 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CV20241 cited

Logic-Free Building Automation: Learning the Control of Room Facilities with Wall Switches and Ceiling Camera

Hideya Ochiai, Kohki Hashimoto, Takuya Sakamoto +5

Artificial intelligence enables smarter control in building automation by its learning capability of users' preferences on facility control. Reinforcement learning (RL) was one of…

cs.NI2022

zk-PoT: Zero-Knowledge Proof of Traffic for Privacy Enabled Cooperative Perception

Ye Tao, Yuze Jiang, Pengfei Lin +2

Cooperative perception is an essential and widely discussed application of connected automated vehicles. However, the authenticity of perception data is not ensured, because the ve…

cs.LG2022

Resilience of Wireless Ad Hoc Federated Learning against Model Poisoning Attacks

Naoya Tezuka, Hideya Ochiai, Yuwei Sun +1

Wireless ad hoc federated learning (WAFL) is a fully decentralized collaborative machine learning framework organized by opportunistically encountered mobile nodes. Compared to con…

cs.CR20211 cited

Misbehavior Detection Using Collective Perception under Privacy Considerations

Manabu Tsukada, Shimpei Arii, Hideya Ochiai +1

In cooperative ITS, security and privacy protection are essential. Cooperative Awareness Message (CAM) is a basic V2V message standard, and misbehavior detection is critical for pr…

cs.CV2021

Reinforcement Learning Based Optimal Camera Placement for Depth Observation of Indoor Scenes

Yichuan Chen, Manabu Tsukada, Hiroshi Esaki

Exploring the most task-friendly camera setting -- optimal camera placement (OCP) problem -- in tasks that use multiple cameras is of great importance. However, few existing OCP so…

cs.CR2021

Suspicious ARP Activity Detection and Clustering Based on Autoencoder Neural Networks

Yuwei Sun, Hideya Ochiai, Hiroshi Esaki

The rapidly increasing number of smart devices on the Internet necessitates an efficient inspection system for safeguarding our networks from suspicious activities such as Address…