TolerStore: Tolerating Malicious Nodes in Decentralized Storage Network

A decentralized storage network (DSN) collects idle storage resources from Internet nodes for low-cost rental to users, and its scale has grown exponentially. In a DSN, most users rely on a centralized third-party service provider (SP) to process userside data and interact with decentralized storage nodes (SNs), making users suffer from a single point of failure. Additionally, since both SP and SNs may offer malicious services, enabling fault tolerance, data confidentiality, and availability guarantee with public verifiability is crucial in the presence of such threats. In this paper, we propose TolerStore, a completely decentralized service framework for DSNs with decentralized SPs and SNs, which can tolerate Byzantine SPs and malicious SNs. To the best of our knowledge, TolerStore is the first to develop a blockchain with multiple SPs for privacy-aware data processing in DSNs, which is formally proven to ensure Byzantine fault tolerance, data confidentiality, public verification, and data availability. Furthermore, we propose an optimized Byzantine Fault-Tolerant consensus with an adaptive leader rotation, incorporating homomorphic fingerprints to verify privacy-aware data processing with enhanced performance. We implement a TolerStore prototype over Hyperledger Fabric, and extensive experiments show that it tolerates [<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\frac{N-1}{3}$</tex-math></inline-formula>] Byzantine SPs and 50% malicious SNs with up to 99.99% data availability.

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Publication Details

Journal
IEEE Transactions on Computers
Published
2025-12-17
DOI
https://doi.org/10.1109/tc.2025.3644302
Primary Topic
Cloud Data Security Solutions
Type
article
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article

TolerStore: Tolerating Malicious Nodes in Decentralized Storage Network

IEEE Transactions on Computers
Cloud Data Security Solutions
article

TolerStore: Tolerating Malicious Nodes in Decentralized Storage Network

article en

Abstract

A decentralized storage network (DSN) collects idle storage resources from Internet nodes for low-cost rental to users, and its scale has grown exponentially. In a DSN, most users rely on a centralized third-party service provider (SP) to process userside data and interact with decentralized storage nodes (SNs), making users suffer from a single point of failure. Additionally, since both SP and SNs may offer malicious services, enabling fault tolerance, data confidentiality, and availability guarantee with public verifiability is crucial in the presence of such threats. In this paper, we propose TolerStore, a completely decentralized service framework for DSNs with decentralized SPs and SNs, which can tolerate Byzantine SPs and malicious SNs. To the best of our knowledge, TolerStore is the first to develop a blockchain with multiple SPs for privacy-aware data processing in DSNs, which is formally proven to ensure Byzantine fault tolerance, data confidentiality, public verification, and data availability. Furthermore, we propose an optimized Byzantine Fault-Tolerant consensus with an adaptive leader rotation, incorporating homomorphic fingerprints to verify privacy-aware data processing with enhanced performance. We implement a TolerStore prototype over Hyperledger Fabric, and extensive experiments show that it tolerates [<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\frac{N-1}{3}$</tex-math></inline-formula>] Byzantine SPs and 50% malicious SNs with up to 99.99% data availability.

IEEE Transactions on ComputersVol. 75(3)
University of Copenhagen (DK), Shanghai Key Laboratory of Trustworthy Computing (CN), East China Normal University (CN), Southeast University (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 26%
Cloud Data Security Solutions
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TolerStore: Tolerating Malicious Nodes in Decentralized Storage Network · IEEE Transactions on Computers (2025) | TGRS Research Map | TGRS