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Yuji Yamaoka

Publications and source records attributed to Yuji Yamaoka.

2 recordsLinked to original sources

Synchro: Block-generation Protocol to Synchronously Process Cross-shard Transactions in State Sharding

Traditional blockchains cannot achieve the same transaction throughput as Web2, so their use cases are limited. Therefore, state sharding has been proposed to improve transaction throughput by dividing the blockchain network and managing states and transactions in parallel. However, Nightshade in the NEAR Protocol, a type of state sharding, provides a rollback protocol to cancel the generation of blocks containing inconsistent transaction results because processing cross-shard transactions (CSTXs) in a 2-phase commit may cause state inconsistency. We present a new attack that interferes with the generation of new blocks by repeatedly executing CSTXs that certainly causes state inconsistency, causing continuous rollback. We also propose a block-generation protocol called Synchro to incorporate all the state changes of each CSTX into the same block by coordinating the block prior to approving transactions in each shard. Synchro eliminates the occurrence of the state inconsistency caused by the CSTXs and the necessity of the rollback protocol. We use zero-knowledge proof to make Synchro scalable in the global validation phase. Although the actual overhead of the zero-knowledge proof has not yet been evaluated, we show that Synchro could achieve the same transaction throughput as Nightshade theoretically, depending on the future innovations in zero-knowledge proof techniques.

cs.CR

Designing a Location Trace Anonymization Contest

For a better understanding of anonymization methods for location traces, we have designed and held a location trace anonymization contest that deals with a long trace (400 events per user) and fine-grained locations (1024 regions). In our contest, each team anonymizes her original traces, and then the other teams perform privacy attacks against the anonymized traces. In other words, both defense and attack compete together, which is close to what happens in real life. Prior to our contest, we show that re-identification alone is insufficient as a privacy risk and that trace inference should be added as an additional risk. Specifically, we show an example of anonymization that is perfectly secure against re-identification and is not secure against trace inference. Based on this, our contest evaluates both the re-identification risk and trace inference risk and analyzes their relationship. Through our contest, we show several findings in a situation where both defense and attack compete together. In particular, we show that an anonymization method secure against trace inference is also secure against re-identification under the presence of appropriate pseudonymization. We also report defense and attack algorithms that won first place, and analyze the utility of anonymized traces submitted by teams in various applications such as POI recommendation and geo-data analysis.

cs.CR