Foundations of Cryptography: Volume 2, Basic Applications
Foundations of Cryptography: Volume 2, Basic Applications
Computation in networks of passively mobile finite-state sensors
Distributed Computing - Special issue: PODC 04
Self-stabilizing leader election in networks of finite-state anonymous agents
OPODIS'06 Proceedings of the 10th international conference on Principles of Distributed Systems
When birds die: making population protocols fault-tolerant
DCOSS'06 Proceedings of the Second IEEE international conference on Distributed Computing in Sensor Systems
Stably computable properties of network graphs
DCOSS'05 Proceedings of the First IEEE international conference on Distributed Computing in Sensor Systems
Fast computation by population protocols with a leader
DISC'06 Proceedings of the 20th international conference on Distributed Computing
Self-stabilizing population protocols
OPODIS'05 Proceedings of the 9th international conference on Principles of Distributed Systems
Decentralized Polling with Respectable Participants
OPODIS '09 Proceedings of the 13th International Conference on Principles of Distributed Systems
SSS'10 Proceedings of the 12th international conference on Stabilization, safety, and security of distributed systems
Self-stabilizing tiny interaction protocols
Proceedings of the Third International Workshop on Reliability, Availability, and Security
Decentralized polling with respectable participants
Journal of Parallel and Distributed Computing
Information and Computation
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We study private computations in a system of tiny mobile agents. We consider the mobile population protocol model of Angluin et al. [2] and ask what can be computed without ever revealing any input to a curious adversary. We show that any computable predicate of the original population model can be made private through an obfuscation procedure that exploits the inherent nondeterminism of the mobility pattern. In short, the idea is for every mobile agent to generate, besides its actual input value, a set of wrong input values to confuse the curious adversary. To converge to the correct result, the procedure has the agents eventually eliminate the wrong values; however, the moment when this happens is hidden from the adversary. This is achieved without jeopardizing the tiny nature of the agents: they still have very small storage size that is independent of the cardinality of the system. We present three variants of this obfuscation procedure that help compute respectively, remainder, threshold, and or predicates which, when composed, cover all those that can be computed in the population protocol model.