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Enhancing sensor attack detection in supervisory control systems modeled by probabilistic automata

Parastou Fahim, Samuel Oliveira, Rômulo Meira-Góes

TL;DR

A polynomial-time algorithm is developed that verifies $\lambda$-sa detectability by constructing a weighted verifier automaton and solving the shortest path problem, and a method is proposed to determine the maximum detection confidence level achievable by the system, ensuring the highest probability of identifying attack-induced behaviors.

Abstract

Sensor attacks compromise the reliability of cyber-physical systems (CPSs) by altering sensor outputs with the objective of leading the system to unsafe system states. This paper studies a probabilistic intrusion detection framework based on $λ$-sensor-attack detectability ($λ$-sa), a formal measure that evaluates the likelihood of a system being under attack based on observed behaviors. Our framework enhances detection by extending its capabilities to identify multiple sensor attack strategies using probabilistic information, which enables the detection of sensor attacks that were undetected by current detection methodologies. We develop a polynomial-time algorithm that verifies $λ$-sa detectability by constructing a weighted verifier automaton and solving the shortest path problem. Additionally, we propose a method to determine the maximum detection confidence level ($λ$*) achievable by the system, ensuring the highest probability of identifying attack-induced behaviors.

Enhancing sensor attack detection in supervisory control systems modeled by probabilistic automata

TL;DR

A polynomial-time algorithm is developed that verifies -sa detectability by constructing a weighted verifier automaton and solving the shortest path problem, and a method is proposed to determine the maximum detection confidence level achievable by the system, ensuring the highest probability of identifying attack-induced behaviors.

Abstract

Sensor attacks compromise the reliability of cyber-physical systems (CPSs) by altering sensor outputs with the objective of leading the system to unsafe system states. This paper studies a probabilistic intrusion detection framework based on -sensor-attack detectability (-sa), a formal measure that evaluates the likelihood of a system being under attack based on observed behaviors. Our framework enhances detection by extending its capabilities to identify multiple sensor attack strategies using probabilistic information, which enables the detection of sensor attacks that were undetected by current detection methodologies. We develop a polynomial-time algorithm that verifies -sa detectability by constructing a weighted verifier automaton and solving the shortest path problem. Additionally, we propose a method to determine the maximum detection confidence level (*) achievable by the system, ensuring the highest probability of identifying attack-induced behaviors.

Paper Structure

This paper contains 24 sections, 7 theorems, 31 equations, 8 figures.

Table of Contents

  1. Introduction
  2. Motivation Example
  3. Modeling of Controlled Systems
  4. Supervisory Control
  5. Stochastic Supervisory Control
  6. Modeling of Control Systems under Sensor Attacks
  7. Sensor Attacker
  8. Controlled System under Attack
  9. Class of Attack Strategies
  10. Probabilistic Intrusion Detection of Sensor Deception Attacks
  11. Detection Value
  12. Detection Language
  13. Probabilistic Sensor Detectability
  14. Solution Verification of $\lambda$-sa detectability
  15. Construction of nominal system
  16. ...and 9 more sections

Key Result

Proposition 1

Let attack strategy $A$ be complete and consistent. For every $s\in \mathcal{L}(S_A/G)$, then $A(s) \in \mathcal{L}(M_a)$.

Figures (8)

  • Figure 1: Overview of discrete collision avoidance modeling for autonomous vehicles
  • Figure 2: PDES $G$ collision avoidance
  • Figure 3: Supervisor $R$ and controlled system $R/G$
  • Figure 4: Two Attack strategies $A_1$ and $A_2$
  • Figure 5: Controlled system under attack
  • ...and 3 more figures

Theorems & Definitions (29)

  • Example 1
  • Example 2
  • Example 3
  • Definition 1: Attack strategy
  • Example 4
  • Definition 2: Attacked supervisor
  • Example 5
  • Definition 3: Complete, Consistent, and Successful Strategies meira-goes:2021synthesis
  • Definition 4: Detection level
  • Example 6
  • ...and 19 more