RECAST: Random Entanglement for Censorship-Resistant Archival STorage

Users entrust an increasing amount of data to online cloud systems for archival purposes. Existing storage systems designed to preserve user data unaltered for decades do not, however, provide strong security guarantees - at least at a reasonable cost. This paper introduces RECAST, an anti-censorship data archival system based on random data entanglement. Documents are mixed together using an entanglement scheme that exploits erasure codes for secure and tamper-proof long-term archival. Data is intertwined in such a way that it becomes virtually impossible to delete a specific document that has been stored long enough in the system, without also erasing a substantial fraction of the whole archive, which requires a very powerful adversary and openly exposes the attack. We validate RECAST entanglement approach via simulations and we present and evaluate a full-fledged prototype deployed in a local cluster. In one of our settings, we show that RECAST, configured with the same storage overhead as triple replication, can withstand 10% of storage node failures without any data loss. Furthermore, we estimate that the effort required from a powerful censor to delete a specific target document is two orders of magnitude larger than for triple replication.