Performance Impact of Strengthening the Accountability and Explainability System in Autonomous Robots

EasyChair Preprint 15324

Abstract

Enhancing data management and security in robotics is crucial for ensuring reliable and efficient robotic operations. Effective data management facilitates data auditing, which further improves system reliability and traceability. This paper explores the integration of SealFS, a secure file system, into autonomous robotic systems. The primary problem addressed is the potential impact of SealFS on system performance, particularly write latency, compared to traditional Ext4 file systems. The methodology involves conducting latency tests in audio, video, and navigation contexts, along with analyzing CPU usage, file size consistency, and power efficiency.

Keyphrases: Cibersecurity, Explainability, ROS 2, ROS integration, Secure file systems, Tamper-Evident Logging, Traceability in robotics, system reliability

@booklet{EasyChair:15324,
  author    = {Alejandro González Cantón and Miguel Angel Gonzalez Santamarta and Enrique Soriano Salvador and Gorka Guardiola Muzquiz and Francisco J Rodríguez Lera},
  title     = {Performance Impact of Strengthening the Accountability and Explainability System in Autonomous Robots},
  howpublished = {EasyChair Preprint 15324},
  year      = {EasyChair, 2024}}