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A dependable and secure consensus algorithm for blockchain assisted microservice architecture

Published: 01 August 2023 Publication History

Abstract

One of the integral components in the architectural design and development of Internet of Things (IoT) is Microservice. Microservices are basically an architectural and organizational approach in the process of software development where the software is composed of small but independent services that would communicate over well-defined APIs (Application Programming Interfaces). It is quite challenging to ensure data integrity and data availability in the architecture design of microservices. As Blockchain technology has emerged as a panacea to many of the other domains, the distributed microservice architecture can also utilize it. We know that the consensus algorithms are used in the Blockchain technology to validate the transactions alongside providing extra level of security. Taking the advantage of consensus algorithms in blockchain-based architecture models, in this paper, we propose TCA (Trustworthy Consensus Algorithm), which is designed to solve the data integrity and availability challenges in microservice architectures. We have evaluated the proposed algorithm against the known alternatives and it shows good level of efficiency.

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Highlights

One of the integral components of Internet of Things (IoT) is Microservice.
It is a challenge to ensure data integrity and data availability.
The consensus algorithms in blockchain provide extra level of security.
Trustworthy Consensus Algorithm enhances the security of microservice.

References

[1]
Lu D, Huang D, Walenstein A, Medhi D. A Secure Microservice Framework for IoT. In: 2017 IEEE symposium on service-oriented system engineering. 2017, p. 9–18.
[2]
Khan P.W., Byun Y.-C., Park N., A data verification system for CCTV surveillance cameras using blockchain technology in smart cities, Electronics 9 (3) (2020).
[3]
Khan P.W., Byun Y., A blockchain-based secure image encryption scheme for the industrial internet of things, Entropy 22 (2) (2020).
[4]
Zhang J., Lu C., Cheng G., Guo T., Kang J., Zhang X., et al., A blockchain-based trusted edge platform in edge computing environment, Sensors (Basel, Switzerland) 21 (6) (2021) 2126.
[5]
Sousa PSd, Nogueira NP, Santos RCd, Maia PHM, Souza JTd. Building a prototype based on Microservices and Blockchain technologies for notary’s office: An academic experience report. In: 2020 IEEE international conference on software architecture companion. 2020, p. 122–9.
[6]
Goodin D., A patient dies after a ransomware attack hits a hospital, 2020, https://www.wired.com/story/a-patient-dies-after-a-ransomware-attack-hits-a-hospital/. [Accessed: 22 February 2021].
[7]
Eismann S., Bezemer C.-P., Shang W., Okanović D., van Hoorn A., Microservices: A performance tester’s dream or nightmare?, in: Proceedings of the ACM/SPEC international conference on performance engineering, Association for Computing Machinery, New York, NY, USA, 2020, pp. 138–149.
[8]
Ahmed M., Akhter A., Rashid A., Fahmideh M., Pathan A., Anwar A., Blockchain meets secured microservice architecture: A trustworthy consensus algorithm, in: Proceedings of the 19th international conference on wireless networks and mobile systems, SciTePress, INSTICC, 2022, pp. 53–60.
[9]
Jamil F., Ahmad S., Iqbal N., Kim D.-H., Towards a remote monitoring of patient vital signs based on IoT-based blockchain integrity management platforms in smart hospitals, Sensors 20 (8) (2020).
[10]
Ahmed M., Pathan A.-S.K., Blockchain: Can it be trusted?, Computer 53 (4) (2020) 31–35.
[11]
Fluree: The Web3 data platform, 2022, https://flur.ee/. [Accessed 22 February 2023].
[12]
Ahmed M., Pathan A.-S.K., False data injection attack (FDIA): An overview and new metrics for fair evaluation of its countermeasure, Complex Adapt Syst Model 8 (2020) 1–14.
[13]
Zhang S., Lee J.-H., Double-spending with a sybil attack in the bitcoin decentralized network, IEEE Trans Ind Inf 15 (10) (2019) 5715–5722.
[14]
Buterin V., The P + epsilon attack, 2015, https://blog.ethereum.org/2015/01/28/p-epsilon-attack/. [Accessed 22 February 2023].
[15]
Nakamoto S., Bitcoin: A peer-to-peer electronic cash system, Manubot, 2019.
[16]
Sun H., Ruan N., Su C., How to model the bribery attack: A practical quantification method in blockchain, in: European symposium on research in computer security, Springer, 2020, pp. 569–589.
[17]
Nicolas K., Wang Y., Giakos G.C., Comprehensive overview of selfish mining and double spending attack countermeasures, in: 2019 IEEE 40th Sarnoff symposium, IEEE, 2019, pp. 1–6.
[18]
Judmayer A., Stifter N., Krombholz K., Weippl E., Blocks and chains: Introduction to bitcoin, cryptocurrencies, and their consensus mechanisms, Synthesis Lect Inf Secur, Priv Trust 9 (1) (2017) 1–123.
[19]
Binance Academy A., Sybil attack, 2021, https://academy.binance.com/en/articles/sybil-attacks-explained. [Accessed 22 February 2023].
[20]
Sayeed S., Marco-Gisbert H., Assessing blockchain consensus and security mechanisms against the 51% attack, Appl Sci 9 (9) (2019).
[21]
Akhter A.F.M.S., Ahmed M., Anwar A., Shah A.S., Pathan A.-S.K., Zengin A., Blockchain in vehicular ad hoc networks: Applications, challenges and solutions, Int J Sensor Networks 40 (2) (2022) 94–130.
[22]
Wang K., Cryptoeconomics: Paving the future of blockchain technology, 2017, https://hackernoon.com/cryptoeconomics-paving-the-future-of-blockchain-technology-13b04dab971. [Accessed 22 February 2023].
[23]
Sharma A., Understanding proof of stake through it’s flaws. Part 3— ‘long range attacks, 2018, https://medium.com/@abhisharm/understanding-proof-of-stake-through-its-flaws-part-3-long-range-attacks-672a3d413501. [Accessed 22 February 2023].
[24]
Ferdous M.S., Chowdhury M.J.M., Hoque M.A., A survey of consensus algorithms in public blockchain systems for crypto-currencies, J Netw Comput Appl 182 (2021).
[25]
Garoffolo A., Stabilini P., Viglione R., Stav U., A penalty system for delayed block submission, 2018, https://www.horizen.global/assets/files/A-Penalty-System-for-Delayed-Block-Submission-by-Horizen.pdf. [Accessed 22 February 2023].
[26]
Minchev R., PirlGuard — Innovative solution against 51% attacks, 2018, https://medium.com/pirl/pirlguard-innovative-solution-against-51-attacks-87dd45aa1109. [Accessed 28 February 2023].
[27]
Block A., Mitigating 51% attacks with LLMQ-based ChainLocks, 2018, https://blog.dash.org/mitigating-51-attacks-with-llmq-based-chainlocks-7266aa648ec9. [Accessed 28 February 2023].
[28]
ChainZilla A., Blockchain security and how to mitigate, 2019, https://medium.com/chainzilla/solutions-to-51-attacks-and-double-spending-71526be4bb86. [Accessed 28 February 2023].

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Information & Contributors

Information

Published In

cover image Computers and Electrical Engineering
Computers and Electrical Engineering  Volume 109, Issue PB
Aug 2023
339 pages

Publisher

Pergamon Press, Inc.

United States

Publication History

Published: 01 August 2023

Author Tags

  1. Blockchain
  2. Microservices
  3. Consensus algorithm
  4. False data injection attacks
  5. Internet of everything

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