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Ghost Train for Anonymous Communication

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Security, Privacy, and Anonymity in Computation, Communication, and Storage (SpaCCS 2016)

Abstract

We study the problem of hiding communication: while it is easy to encrypt a message sent from Alice to Bob, it is hard to hide that such a communication takes place. Communiaction hiding is one of the fundamental privacy challenges, especially in case of an adversary having a complete view of the traffic and controlling a large number of nodes.

Following the Beimel-Dolev’s buses concept and Young-Yung drunk motorcyclist protocol we propose a theoretical concept called Ghost Train. The ghost trains are travelling at random through the network just as drunk motorcyclists and one version of Beimel-Dolev buses. However, there are no assigned seats or motorcyclists holding a ciphertext. The trains are not generated by the senders, once created they travel forever, and hold messages in the way that the older messages gradually decay and are replaced by new messages inserted into the train. Each train route is random and stochastically independent from the existing sender-destination pairs, thus the protocol is fully oblivious. Additionally, it works for dynamic networks where the nodes can join and leave the network (unlike the Beimel-Dolev solution) and yet it is not possible to indicate the origin of any given package (unlike in the drunken motorcyclist protocol).

Our protocol is based on basic tools (Bloom filters, PRNGs) and a novel concept of inserting many ciphertexts on the same place and their decay.

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References

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Acknowledgments

The research was supported by the Polish National Science Centre, Decision DEC-2013/08/M/ST6/00928.

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Correspondence to Jakub Lemiesz .

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Błaśkiewicz, P., Kutyłowski, M., Lemiesz, J., Sulkowska, M. (2016). Ghost Train for Anonymous Communication. In: Wang, G., Ray, I., Alcaraz Calero, J., Thampi, S. (eds) Security, Privacy, and Anonymity in Computation, Communication, and Storage. SpaCCS 2016. Lecture Notes in Computer Science(), vol 10066. Springer, Cham. https://doi.org/10.1007/978-3-319-49148-6_20

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  • DOI: https://doi.org/10.1007/978-3-319-49148-6_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49147-9

  • Online ISBN: 978-3-319-49148-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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