Abstract
To date, the issues of privacy and security remain poorly addressed within robotics at large. In this work, we provide a foundation for analyzing the privacy of swarms of heterogeneous robots. Our premise is that information pertaining to individual robot types must be kept private in order to preserve the security and resilience of the swarm system at large. A main contribution is the development of a macroscopic privacy model that can be applied to swarms. Our privacy model draws from the notion of differential privacy that stems from the database literature, and that provides a stringent statistical interpretation of information leakage. We combine the privacy model with a macroscopic abstraction of the swarm system, and show how this enables an analysis of the privacy trends as swarm parameters vary.
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Notes
- 1.
The modeling framework (CRN) can encompass any measurable state that is associated to the swarm (beyond physical robot states). As a consequence, there are no limitations to what the observable state can represent. This choice can be made by the designer as a function of what may be exposed in a given system.
- 2.
In our context of a robotic swarm, an example of side information could be the number of manufacturing parts ordered to build the swarm. If different robot species are made of different parts, such information can be used to construct an initial guess about the number of robots per species. Thus, one would be able to derive the probability of a robot belonging to a given species.
- 3.
We assume a snapshot adversary that gains system-level information at a specific time. This system-level information is a design variable, called the observable state.
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Acknowledgments
We gratefully acknowledge the support of ONR grants N00014-15-1-2115 and N00014-14-1-0510, ARL grant W911NF-08-2-0004, NSF grant IIS-1426840, and TerraSwarm, one of six centers of STARnet, a Semiconductor Research Corporation program sponsored by MARCO and DARPA.
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Prorok, A., Kumar, V. (2016). A Macroscopic Privacy Model for Heterogeneous Robot Swarms. In: Dorigo, M., et al. Swarm Intelligence. ANTS 2016. Lecture Notes in Computer Science(), vol 9882. Springer, Cham. https://doi.org/10.1007/978-3-319-44427-7_2
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DOI: https://doi.org/10.1007/978-3-319-44427-7_2
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