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We explore practical tradeoffs in blockchain-based biometric templatestorage. We first discuss opportunities and challenges in the integration ofblockchain and biometrics, with emphasis in biometric template storage andprotection, a key problem in biometrics still largely unsolved. Blockchaintechnologies provide excellent architectures and practical tools for securingand managing the sensitive and private data stored in biometric templates, butat a cost. We explore experimentally the key tradeoffs involved in thatintegration, namely: latency, processing time, economic cost, and biometricperformance. We experimentally study those factors by implementing a smartcontract on Ethereum for biometric template storage, whose cost-performance isevaluated by varying the complexity of state-of-the-art schemes for face andhandwritten signature biometrics. We report our experiments using popularbenchmarks in biometrics research, including deep learning approaches anddatabases captured in the wild. As a result, we experimentally show thatstraightforward schemes for data storage in blockchain (i.e., direct andhash-based) may be prohibitive for biometric template storage usingstate-of-the-art biometric methods. A good cost-performance tradeoff is shownby using a blockchain approach based on Merkle trees.

Biometric Template Storage with Blockchain: A First Look into Cost and Performance Tradeoffs