SecSens: Secure State Estimation with Application to Localization and Time Synchronization

TL;DR

SecSens introduces two algorithms, SecEKF and SecOPT, for secure nonlinear state estimation in CPS, enhancing localization and synchronization robustness against sensor attacks without specialized hardware.

Contribution

The paper presents SecSens, a novel security-aware state estimation framework using EKF and MLE that is faster and more effective against attacks than existing solutions.

Findings

SecSens achieves several orders of magnitude faster runtime.

It effectively localizes and synchronizes devices under attack.

The approach does not require specialized hardware or cryptography.

Abstract

Research evidence in Cyber-Physical Systems (CPS) shows that the introduced tight coupling of information technology with physical sensing and actuation leads to more vulnerability and security weaknesses. But, the traditional security protection mechanisms of CPS focus on data encryption while neglecting the sensors which are vulnerable to attacks in the physical domain. Accordingly, researchers attach utmost importance to the problem of state estimation in the presence of sensor attacks. In this work, we present SecSens, a novel approach for secure nonlinear state estimation in the presence of modeling and measurement noise. SecSens consists of two independent algorithms, namely, SecEKF and SecOPT, which are based on Extended Kalman Filter and Maximum Likelihood Estimation, respectively. We adopt a holistic approach to introduce security awareness among state estimation algorithms without requiring specialized hardware, or cryptographic techniques. We apply SecSens to securely localize and time synchronize networked mobile devices. SecSens provides good performance at run-time several order of magnitude faster than the state of art solutions under the presence of powerful attacks. Our algorithms are evaluated on a testbed with static nodes and a mobile quadrotor all equipped with commercial ultra-wide band wireless devices.