International Association for Cryptologic Research

International Association
for Cryptologic Research

IACR News item: 08 December 2025

Panagiotis Chatzigiannis, Suvradip Chakraborty, Shimaa Ahmed
ePrint Report ePrint Report
In the Web2 world, users control their accounts using credentials such as usernames and passwords, which can be reset or recovered by centralized servers if the user loses them. In the decentralized Web3 world however, users control their accounts through cryptographic private-public key pairs which are much more complex to manage securely. In addition, the decentralized nature of Web3 makes account recovery impossible in the absence of predetermined recovery mechanisms. With the proliferation of blockchains and cryptocurrencies over the last years, it is crucial to provide users secure, usable and reliable ways to recover their accounts and assets. However, up to this day, no Web3 recovery method has adequately achieved all three of the above required properties. For instance, conventional ``mnemonic" backups which can deterministically reconstruct a private key require verbatim recall of a fixed word list, creating an unpleasant usability/security trade-off.

In this work, we present a fully-offline protocol called LifeXP$^{+}$, that allows a user to reconstruct a cryptographically-secure private key from a natural-language story, which a user always remembers, such an memorable life event. To ensure usability of our protocol, key reconstruction can work even when the story is later retold with different wording or grammar, only requiring to preserve the semantics. The protocol combines pre-trained sentence embeddings to capture semantics, locality-sensitive hashing to quantize embeddings into stable bit strings, a cryptographic fuzzy extractor that corrects bit errors caused by paraphrasing, and a biometric factor that is fused with the linguistic factor to boost entropy and enhance security. In our paper we describe the design, show that the protocol achieves the required properties, and provide an evaluation based on publicly-available datasets which runs completely offline on commodity hardware, showcasing its feasibility.
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