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Assessing security and performance of blockchain systems and consensus protocols: taxonomies, methodologies and benchmarking procedures

Assessing security and performance of blockchain systems and consensus protocols: taxonomies, methodologies and benchmarking procedures
Assessing security and performance of blockchain systems and consensus protocols: taxonomies, methodologies and benchmarking procedures
Blockchain promises to improve systems security and trust by decentralising computer infrastructures. However, decentralisation also requires higher complexity that may lead to performance issues. With the rapid growth of blockchain adoption, such properties are paramount, and it becomes crucial to assess them in different application scenarios. In this PhD thesis, we study performance and security of modern blockchain systems. We first refine the standard concepts of security and dependability, defining a set of properties for blockchain systems. We provide a taxonomy of platforms, consensus protocols, and smart contacts vulnerabilities, and we assess their security according to the proposed properties. We show that consensus strictly impacts system’s security. We also argue that it introduces trade-offs with performance that must be understood for building secure and efficient systems. So we design METHUS, a systematic methodology to assess blockchain consensus protocols applying qualitative and quantitative methods. Hence we evaluate two families of consensus protocols used in permissioned blockchains, and we show that a traditional Byzantine Fault Tolerant approach is preferable in this context. Extending the study to permissionless blockchains, we propose PETHARD, a framework to measure performance of consensus employed in two famous blockchains, namely Ethereum and Algorand. Despite promising results, PETHARD only simulates testing setups and cannot be used to evaluate realistic deployments. To this extent, we design PERSECUS which defines the standards for blockchain benchmarking. PERSECUS fosters efficient and precise measurements simulating various setups and real-world scenarios. We benchmark two blockchains, namely Parity and GoQuorum, evaluating their security, performance, and scalability properties. We illustrate that, besides consensus, other blockchain components, such as configuration of nodes parameters and transactions serialisation, strictly affect performance and security. To conclude this thesis, we discuss the possibility of using elasticity, broadly adopted in Cloud Computing to automatise the provisioning of a system, to enhance performance and security in blockchain systems.
Blockchain, Consensus Algorithms, Performance Measurement, Security, Benchmark, Taxonomy, methodologies
University of Southampton
De Angelis, Stefano
3a260021-da00-4b26-b9f0-b91dcf70cb19
De Angelis, Stefano
3a260021-da00-4b26-b9f0-b91dcf70cb19
Sassone, Vladimiro
df7d3c83-2aa0-4571-be94-9473b07b03e7
Aniello, Leonardo
9846e2e4-1303-4b8b-9092-5d8e9bb514c3

De Angelis, Stefano (2022) Assessing security and performance of blockchain systems and consensus protocols: taxonomies, methodologies and benchmarking procedures. University of Southampton, Doctoral Thesis, 173pp.

Record type: Thesis (Doctoral)

Abstract

Blockchain promises to improve systems security and trust by decentralising computer infrastructures. However, decentralisation also requires higher complexity that may lead to performance issues. With the rapid growth of blockchain adoption, such properties are paramount, and it becomes crucial to assess them in different application scenarios. In this PhD thesis, we study performance and security of modern blockchain systems. We first refine the standard concepts of security and dependability, defining a set of properties for blockchain systems. We provide a taxonomy of platforms, consensus protocols, and smart contacts vulnerabilities, and we assess their security according to the proposed properties. We show that consensus strictly impacts system’s security. We also argue that it introduces trade-offs with performance that must be understood for building secure and efficient systems. So we design METHUS, a systematic methodology to assess blockchain consensus protocols applying qualitative and quantitative methods. Hence we evaluate two families of consensus protocols used in permissioned blockchains, and we show that a traditional Byzantine Fault Tolerant approach is preferable in this context. Extending the study to permissionless blockchains, we propose PETHARD, a framework to measure performance of consensus employed in two famous blockchains, namely Ethereum and Algorand. Despite promising results, PETHARD only simulates testing setups and cannot be used to evaluate realistic deployments. To this extent, we design PERSECUS which defines the standards for blockchain benchmarking. PERSECUS fosters efficient and precise measurements simulating various setups and real-world scenarios. We benchmark two blockchains, namely Parity and GoQuorum, evaluating their security, performance, and scalability properties. We illustrate that, besides consensus, other blockchain components, such as configuration of nodes parameters and transactions serialisation, strictly affect performance and security. To conclude this thesis, we discuss the possibility of using elasticity, broadly adopted in Cloud Computing to automatise the provisioning of a system, to enhance performance and security in blockchain systems.

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More information

Submitted date: April 2022
Keywords: Blockchain, Consensus Algorithms, Performance Measurement, Security, Benchmark, Taxonomy, methodologies

Identifiers

Local EPrints ID: 457412
URI: http://eprints.soton.ac.uk/id/eprint/457412
PURE UUID: 6fbc99c0-c855-4a66-bf87-6669d8cb8ac1
ORCID for Stefano De Angelis: ORCID iD orcid.org/0000-0002-1168-9064
ORCID for Leonardo Aniello: ORCID iD orcid.org/0000-0003-2886-8445

Catalogue record

Date deposited: 07 Jun 2022 16:46
Last modified: 08 Jun 2022 01:51

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Contributors

Author: Stefano De Angelis ORCID iD
Thesis advisor: Vladimiro Sassone
Thesis advisor: Leonardo Aniello ORCID iD

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