A Decentralized Storage System for Storing Big Data in Consortium Blockchains

核心概念

A decentralized storage system for Hyperledger Fabric that uses erasure coding, a two-layer hash-slots mechanism, and a mirror strategy to enable efficient and secure storage of large files within the blockchain network.

摘要

The paper proposes a decentralized storage system called "DBNode" for Hyperledger Fabric, a consortium blockchain. The key highlights are:

1. Erasure coding is used to partition files into chunks, which are then organized into a hierarchical structure for efficient and reliable data storage.
2. A two-layer hash-slots mechanism and a mirror strategy are designed to enable high data availability, even in the face of node failures.
3. An access control mechanism based on a smart contract is implemented to regulate file access and enforce predefined rules.
4. The system eliminates the need for external storage solutions like IPFS, simplifying the management of large files for clients and encapsulating the complexities within the blockchain.
5. Experiments show that the proposed system outperforms IPFS in terms of file retrieval latency and adapts well to changes in network bandwidth.

統計資料

The maximum number of links stored in a single DBNode is about 100 when storing 1,000 chunks.
The total number of links stored in the entire system is about 300 when storing 1,000 chunks.
The storage overhead for links is negligible, accounting for only 0.02‰ of the file size for a single DBNode and 0.06‰ for the entire system.
The writing latency of the DBNode system is higher than IPFS due to the additional communication with the blockchain and the need to ensure data availability.
The reading latency of the DBNode system is significantly lower than IPFS, especially for large files, due to the use of erasure coding and the hash slot table.
The DBNode system effectively adapts to changes in network bandwidth, maintaining consistent reading latency, while IPFS experiences a significant increase in reading latency under the stepped bandwidth setting.

引述

"The availability of files in DBNodes is fixed based on the setting of erasure coding. Moreover, the file tree, which records the hash value of each chunk, is uploaded to the smart contract to guarantee that every chunk is searchable."
"The DBNode system allocates more hash slots to nodes with high bandwidth, resulting in more stored chunks in these nodes and reduced impact from nodes with lower bandwidth."
"A (n, k) erasure code allows the client to recover the file based on the first k obtained chunks. In that case, the client will not wait for other chunks that might not have been transferred by the nodes with low bandwidth."

從以下內容提煉的關鍵洞見

DBNode: A Decentralized Storage System for Big Data Storage in Consortium Blockchains

by Narges Dadkh... 於 arxiv.org 10-01-2024

https://arxiv.org/pdf/2409.20123.pdf

深入探究

How can the proposed system be extended to support dynamic changes in the consortium blockchain, such as the addition or removal of organizations?

The proposed decentralized storage system, DBNode, can be extended to accommodate dynamic changes in the consortium blockchain by implementing a flexible architecture that allows for the seamless addition or removal of organizations. This can be achieved through the following strategies:

Dynamic Membership Management: The system can incorporate a membership service provider (MSP) that manages the identities and roles of organizations within the consortium. When an organization is added or removed, the MSP can update the access control lists and permissions associated with the smart contracts governing file access. This ensures that the access rules remain consistent and secure.

Reconfiguration of Erasure Coding: The erasure coding parameters can be dynamically adjusted based on the current number of organizations and nodes. For instance, if a new organization joins, the system can redistribute the data chunks according to the new organizational structure while maintaining the redundancy and fault tolerance levels. This may involve recalculating the (n, k) parameters of the Reed-Solomon code to ensure that the system can still tolerate node and organization failures.

Adaptive Hash Slot Allocation: The two-layer hash-slot mechanism can be designed to adapt to changes in the number of organizations. When an organization is added, the hash slots can be reallocated based on the new bandwidth and storage capacities of the participating nodes. This dynamic allocation can help maintain optimal performance and data distribution across the network.

Smart Contract Upgrades: The smart contracts that govern file access and storage can be designed to support upgradeable patterns. This allows for modifications to the access control rules and the addition of new functionalities without disrupting the existing operations. By utilizing proxy contracts or similar patterns, the system can ensure that the latest access rules are enforced even as organizations change.

Monitoring and Notification System: Implementing a monitoring system that tracks the status of organizations and nodes can facilitate timely updates to the storage architecture. Notifications can be sent to the relevant parties when changes occur, prompting necessary adjustments in the storage strategy or access controls.

By incorporating these strategies, the DBNode system can effectively manage dynamic changes in the consortium blockchain, ensuring continued performance, security, and data integrity.

What are the potential security implications of storing file access rules in a smart contract, and how can the system be further hardened against malicious attacks?

Storing file access rules in a smart contract introduces several potential security implications, including:

Immutable Access Control: Once deployed, smart contracts are immutable, meaning that any vulnerabilities or errors in the access control logic cannot be easily corrected. If a flaw exists, it could be exploited by malicious actors to gain unauthorized access to sensitive files.

Exposure of Access Rules: The access rules defined in the smart contract are visible to all participants in the blockchain. This transparency can be a double-edged sword; while it promotes trust, it also means that attackers can analyze the rules to identify potential weaknesses or loopholes.

Denial of Service (DoS) Attacks: Malicious actors could attempt to overload the smart contract with excessive requests or transactions, leading to increased latency or even service outages. This could hinder legitimate users from accessing their files.

Sybil Attacks: In a consortium blockchain, if an attacker can create multiple identities, they may manipulate the access control mechanisms to gain unauthorized access to files by exploiting the trust model of the consortium.

To further harden the system against these potential attacks, the following measures can be implemented:

Access Control Audits: Regular audits of the smart contract code should be conducted to identify and rectify vulnerabilities. Employing formal verification methods can help ensure that the access control logic behaves as intended.

Role-Based Access Control (RBAC): Implementing RBAC within the smart contract can help limit access based on user roles, reducing the risk of unauthorized access. This can be combined with multi-signature requirements for critical operations to enhance security.

Encryption of Access Rules: While the smart contract must remain transparent, sensitive access rules can be encrypted. Only authorized parties would have the decryption keys, ensuring that even if the contract is visible, the actual rules remain confidential.

Rate Limiting and Throttling: Implementing rate limiting on the number of requests to the smart contract can mitigate the risk of DoS attacks. This can be achieved through mechanisms that restrict the number of transactions a single identity can initiate within a given timeframe.

Monitoring and Anomaly Detection: Establishing a monitoring system that tracks access patterns and detects anomalies can help identify potential attacks in real-time. Alerts can be generated for unusual access attempts, allowing for prompt responses.

By addressing these security implications and implementing robust protective measures, the DBNode system can enhance its resilience against malicious attacks while maintaining the integrity of file access rules.

Could the two-layer hash-slots mechanism and mirror strategy be applied to other distributed storage systems beyond consortium blockchains to improve their performance and resilience?

Yes, the two-layer hash-slots mechanism and mirror strategy can be effectively applied to other distributed storage systems beyond consortium blockchains to enhance their performance and resilience. Here’s how these strategies can be beneficial in various contexts:

Two-Layer Hash-Slots Mechanism:

Load Balancing: In any distributed storage system, the two-layer hash-slots mechanism can facilitate load balancing by distributing data chunks across nodes based on their storage capacity and network bandwidth. This ensures that no single node becomes a bottleneck, improving overall system performance.
Dynamic Data Distribution: The mechanism can adapt to changes in node availability or performance, allowing for dynamic reallocation of data chunks. This adaptability is crucial in cloud storage environments where nodes may frequently join or leave the network.
Efficient Data Retrieval: By using hash slots to determine the storage location of data chunks, retrieval times can be minimized. This is particularly beneficial in systems that require quick access to large datasets, such as content delivery networks (CDNs) or real-time data processing systems.

Mirror Strategy:

Data Redundancy: The mirror strategy enhances data redundancy by ensuring that multiple copies of data chunks are stored across different nodes. This is particularly useful in systems where data availability is critical, such as in healthcare or financial applications where data loss can have severe consequences.
Privacy Preservation: By allowing clients to specify storage locations and implementing links instead of direct data storage, the mirror strategy can help maintain data privacy. This is applicable in any distributed system where sensitive information needs to be protected from unauthorized access.
Conflict Resolution: The mirror strategy can effectively resolve conflicts that arise from data distribution algorithms, ensuring that redundancy requirements are met without compromising the efficiency of data storage. This is valuable in peer-to-peer storage systems where nodes may have varying capabilities.

Broader Applications:

Cloud Storage Solutions: The two-layer hash-slots mechanism can be integrated into cloud storage services to optimize data distribution and retrieval, enhancing user experience and reducing latency.
Decentralized File Systems: In decentralized file systems like IPFS, these strategies can improve data availability and resilience against node failures, addressing some of the inherent limitations of current implementations.
Big Data Analytics: In big data environments, where large volumes of data are processed and analyzed, applying these strategies can enhance data management efficiency and ensure that data remains accessible even in the face of node failures.

In conclusion, the two-layer hash-slots mechanism and mirror strategy are versatile approaches that can significantly improve the performance and resilience of various distributed storage systems, making them suitable for a wide range of applications beyond consortium blockchains.