Improving Efficiency and Security of Sharded Blockchain

Zhang, Zixu

Improving Efficiency and Security of Sharded Blockchain

Zhang, Zixu

Permalink

Publication Type:: Thesis
Issue Date:: 2025

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download thesisAdobe PDF (8.45 MB)

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Zhang, Zixu
dc.date.accessioned	2025-06-02T21:29:00Z
dc.date.available	2025-06-02T21:29:00Z
dc.date.issued	2025
dc.identifier.uri	http://hdl.handle.net/10453/187588
dc.description	University of Technology Sydney. Faculty of Engineering and Information Technology.	en_US.UTF-8
dc.description.abstract	Blockchain technology has significantly evolved, notably through the adoption of sharding techniques to enhance scalability and manage growing transaction demands efficiently. Sharding divides the blockchain network into smaller, more manageable segments, or shards, which operate parallel transactions, thereby boosting throughput. However, conventional sharding solutions often encounter challenges related to node distribution and transaction efficiency, particularly when managing cross-shard transactions which can significantly degrade network performance and increase transaction costs. In this thesis, Blockchain Sharding bottlenecks are addressed by introducing novel methods to optimize sharding schemes for enhanced efficiency and security. Firstly, a community detection based sharding scheme are validated using over one million public Ethereum transactions. This scheme dramatically decreases the ratio of cross-shard transactions from 80% to 20%, significantly lower than that of baseline random sharding methods. By clustering transactional communities, community detection-based sharding approach promotes intra-shard transactions, which substantially reduces transaction fees by 50%, thereby enhancing blockchain scalability and making the ecosystem more budget friendly. Furthermore, a novel Trust-based and Deep Reinforcement Learning-driven (TbDd) framework are introduced to mitigate collusion risks and dynamically adjust node allocation, thus enhancing throughput while maintaining network security. The TbDd framework features a comprehensive trust evaluation system that identifies node behaviors and performs targeted resharding to address potential threats. Designed to increase tolerance for dishonest nodes, optimize node movement frequency, and ensure equitable distribution across shards, this framework effectively balances sharding risks. Extensive testing shows that TbDd surpasses traditional random, community, and trust-based methods in maintaining shard risk equilibrium and reducing cross-shard transactions. Lastly, an advanced Overlapping Sharding with xPBFT Consensus Mechanism are proposed, which simplifies cross-shard transactions by treating them as intra-shard processes. This approach reduces latency by up to 40% and strengthens security, offering a scalable solution for decentralized applications. These contributions advance the efficiency, security, and scalability of sharded blockchain systems, providing a robust foundation for future developments in blockchain technology.	en_US.UTF-8
dc.format	Thesis (PhD)
dc.language.iso	en_US	en_US.UTF-8
dc.relation	https://opus.lib.uts.edu.au/bitstream/10453/187588/1/thesis.pdf
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	The author owns the copyright in this thesis including all reproduction and reuse rights for the work. The work may not be altered without the permission of the copyright owner. Attribution is essential when quoting or paraphrasing from this thesis.
dc.rights	© 2025 Zixu Zhang
dc.rights	au.edu.uts.lib/cph
dc.title	Improving Efficiency and Security of Sharded Blockchain	en_US.UTF-8
dc.type	Thesis
utslib.copyright.status	open_access	*

Abstract:

Blockchain technology has significantly evolved, notably through the adoption of sharding techniques to enhance scalability and manage growing transaction demands efficiently. Sharding divides the blockchain network into smaller, more manageable segments, or shards, which operate parallel transactions, thereby boosting throughput. However, conventional sharding solutions often encounter challenges related to node distribution and transaction efficiency, particularly when managing cross-shard transactions which can significantly degrade network performance and increase transaction costs. In this thesis, Blockchain Sharding bottlenecks are addressed by introducing novel methods to optimize sharding schemes for enhanced efficiency and security. Firstly, a community detection based sharding scheme are validated using over one million public Ethereum transactions. This scheme dramatically decreases the ratio of cross-shard transactions from 80% to 20%, significantly lower than that of baseline random sharding methods. By clustering transactional communities, community detection-based sharding approach promotes intra-shard transactions, which substantially reduces transaction fees by 50%, thereby enhancing blockchain scalability and making the ecosystem more budget friendly. Furthermore, a novel Trust-based and Deep Reinforcement Learning-driven (TbDd) framework are introduced to mitigate collusion risks and dynamically adjust node allocation, thus enhancing throughput while maintaining network security. The TbDd framework features a comprehensive trust evaluation system that identifies node behaviors and performs targeted resharding to address potential threats. Designed to increase tolerance for dishonest nodes, optimize node movement frequency, and ensure equitable distribution across shards, this framework effectively balances sharding risks. Extensive testing shows that TbDd surpasses traditional random, community, and trust-based methods in maintaining shard risk equilibrium and reducing cross-shard transactions. Lastly, an advanced Overlapping Sharding with xPBFT Consensus Mechanism are proposed, which simplifies cross-shard transactions by treating them as intra-shard processes. This approach reduces latency by up to 40% and strengthens security, offering a scalable solution for decentralized applications. These contributions advance the efficiency, security, and scalability of sharded blockchain systems, providing a robust foundation for future developments in blockchain technology.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/187588