Name
Abstract | ||
|---|---|---|
In networked environments, adversaries may exploit location information to perform carefully crafted attacks on cyber-physical systems (CPS). To prevent such security breaches, this letter develops a network localization and navigation (NLN) paradigm that accounts for network secrecy in the control of mobile agents. We consider a scenario in which a mobile agent is tasked with maneuvering through an adversarial network, based on a nominal control policy, and we aim to reduce the ability of the adversarial network to infer the mobile agent's position. Specifically, the Fisher information of the agent's position obtained by the adversarial network is adopted as a secrecy metric. We propose a new control policy that results from an optimization problem and achieves a compromise between maximizing location secrecy and minimizing the deviation from the nominal control policy. Results show that the proposed optimization-based control policy significantly improves the secrecy of the mobile agent. |
Year | DOI | Venue |
|---|---|---|
2023 | 10.1109/LCSYS.2022.3189960 | IEEE CONTROL SYSTEMS LETTERS |
Keywords | DocType | Volume |
Sensors, Robot sensing systems, Mobile agents, Robots, Location awareness, Measurement, Trajectory, Localization, Fisher information, sensor network, secrecy, control | Journal | 7 |
ISSN | Citations | PageRank |
2475-1456 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mohammad Javad Khojasteh | 1 | 0 | 0.34 |
| Augustin A. Saucan | 2 | 0 | 0.34 |
| Zhenyu Liu | 3 | 23 | 4.52 |
| Andrea Conti | 4 | 1594 | 106.05 |
| Moe Z. Win | 5 | 2225 | 196.12 |