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An increasing amount of information today is generated, exchanged, and storeddigitally. This also includes long-lived and highly sensitive information(e.g., electronic health records, governmental documents) whose integrity andconfidentiality must be protected over decades or even centuries. While thereis a vast amount of cryptography-based data protection schemes, only few aredesigned for long-term protection. Recently, Braun et al. (AsiaCCS'17) proposedthe first long-term protection scheme that provides renewable integrityprotection and information-theoretic confidentiality protection. However,computation and storage costs of their scheme increase significantly with thenumber of stored data items. As a result, their scheme appears suitable onlyfor protecting databases with a small number of relatively large data items,but unsuitable for databases that hold a large number of relatively small dataitems (e.g., medical record databases). In this work, we present a solution forefficient long-term integrity and confidentiality protection of large datasetsconsisting of relatively small data items. First, we construct a renewablevector commitment scheme that is information-theoretically hiding underselective decommitment. We then combine this scheme with renewable timestampsand information-theoretically secure secret sharing. The resulting solutionrequires only a single timestamp for protecting a dataset while the state ofthe art requires a number of timestamps linear in the number of data items. Weimplemented our solution and measured its performance in a scenario where 12000 data items are aggregated, stored, protected, and verified over a time spanof 100 years. Our measurements show that our new solution completes thisevaluation scenario an order of magnitude faster than the state of the art.

ELSA: Efficient Long-Term Secure Storage of Large Datasets