A Macroscopic Privacy Model for Heterogeneous Robot Swarms

  • Amanda ProrokEmail author
  • Vijay KumarEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9882)


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.


Chemical Reaction Network Side Information Population Vector Propensity Rate Stochastic Simulation Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



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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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.University of PennsylvaniaPhiladelphiaUSA

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