# Secure State Estimation For Cyber Physical Systems Under Sensor Attacks: A Satisfiability Modulo Theory Approach

arXiv: https://arxiv.org/abs/1412.4324 · HTML: https://mlsanity.com/paper/1412.4324/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Dec 2014.

## Built on by (most cited first, 2 of 2)

- [Model Extraction Attacks Against Reinforcement Learning Based Controllers](https://mlsanity.com/paper/2304.13090/) (2023)
- [Adversarial observations in probabilistic State-Space Models for robust Reinforcement Learning](https://mlsanity.com/paper/2606.20880/) (2026)

## Abstract (arXiv)

We address the problem of detecting and mitigating the effect of malicious attacks to the sensors of a linear dynamical system. We develop a novel, efficient algorithm that uses a Satisfiability-Modulo-Theory approach to isolate the compromised sensors and estimate the system state despite the presence of the attack, thus harnessing the intrinsic combinatorial complexity of the problem. By leveraging results from formal methods over real numbers, we provide guarantees on the soundness and completeness of our algorithm. We then report simulation results to compare its runtime performance with alternative techniques. Finally, we demonstrate its application to the problem of controlling an unmanned ground vehicle.