Offline and online energy-efficient monitoring of scattered uncertain logs using a bounding model

TL;DR

This paper presents a novel method for energy-efficient, offline and online monitoring of uncertain logs in cyber-physical systems using an over-approximated non-linear dynamical model, ensuring safety with minimal false alarms.

Contribution

It introduces a new approach for monitoring uncertain logs in cyber-physical systems both offline and online, reducing false alarms and energy consumption.

Findings

Effective offline safety monitoring with limited false alarms.

Online monitoring reduces sample triggers for energy efficiency.

Validated on anesthesia, cruise control, and aircraft systems.

Abstract

Monitoring the correctness of distributed cyber-physical systems is essential. Detecting possible safety violations can be hard when some samples are uncertain or missing. We monitor here black-box cyber-physical system, with logs being uncertain both in the state and timestamp dimensions: that is, not only the logged value is known with some uncertainty, but the time at which the log was made is uncertain too. In addition, we make use of an over-approximated yet expressive model, given by a non-linear extension of dynamical systems. Given an offline log, our approach is able to monitor the log against safety specifications with a limited number of false alarms. As a second contribution, we show that our approach can be used online to minimize the number of sample triggers, with the aim at energetic efficiency. We apply our approach to three benchmarks, an anesthesia model, an adaptive cruise controller and an aircraft orbiting system.