Sandboxing Controllers for Stochastic Cyber-Physical Systems

Bingzhuo Zhong, Majid Zamani, Marco Caccamo

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Current cyber-physical systems (CPS) are expected to accomplish complex tasks. To achieve this goal, high performance, but unverified controllers (e.g. deep neural network, black-box controllers from third parties) are applied, which makes it very challenging to keep the overall CPS safe. By sandboxing these controllers, we are not only able to use them but also to enforce safety properties over the controlled physical systems at the same time. However, current available solutions for sandboxing controllers are just applicable to deterministic (a.k.a. non-stochastic) systems, possibly affected by bounded disturbances. In this paper, for the first time we propose a novel solution for sandboxing unverified complex controllers for CPS operating in noisy environments (a.k.a. stochastic CPS). Moreover, we also provide probabilistic guarantees on their safety. Here, the unverified control input is observed at each time instant and checked whether it violates the maximal tolerable probability of reaching the unsafe set. If this probability exceeds a given threshold, the unverified control input will be rejected, and the advisory input provided by the optimal safety controller will be used to maintain the probabilistic safety guarantee. The proposed approach is illustrated empirically and the results indicate that the expected safety probability is guaranteed.

Original languageEnglish (US)
Title of host publicationFormal Modeling and Analysis of Timed Systems - 17th International Conference, FORMATS 2019, Proceedings
EditorsÉtienne André, Mariëlle Stoelinga, Mariëlle Stoelinga
Number of pages18
ISBN (Print)9783030296612
StatePublished - 2019
Externally publishedYes
Event17th International Conference on Formal Modeling and Analysis of Timed Systems, FORMATS 2019 - Amsterdam, Netherlands
Duration: Aug 27 2019Aug 29 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11750 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference17th International Conference on Formal Modeling and Analysis of Timed Systems, FORMATS 2019


  • Fault-tolerance
  • Sandboxing controllers
  • Stochastic cyber-physical systems

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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