BlockASP: A Framework for AOP-Based Model Checking Blockchain System

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Abstract

Blockchain systems are lauded for their security, and reliability. Security is a cornerstone, as they employ cryptographic techniques to ensure the immutability of data, making it extremely resistant to tampering. With decentralized networks, they also reduce the risk of a single point of failure, enhancing reliability. Model checking plays a vital role in ensuring the security, and reliability of blockchain systems. However, traditional model-checking approaches face challenges in handling the inherent dynamism exhibited in blockchain systems. To overcome this challenge, Aspect-Oriented programming (AOP) offers capabilities to enhance blockchain model checking through the modularization of cross-cutting concerns, enabling traceability and monitoring, facilitating dynamic instrumentation, and supporting fine-grained property specifications. The aim of this research is to enable more effective and efficient verification of dynamic behaviors in blockchain systems compared to conventional model-checking techniques using AOP. As a result, this research introduces BlockASP, a novel blockchain model verification method that leverages AOP to analyze and monitor dynamic behavior of the blockchain system. BlockASP integrates the benefits of aspect-orientation and model checking into the blockchain architecture to strengthen security, and reliability. This research has examined prior art that are related to blockchain modeling using Object-oriented (OO) and those are using AOP. Our research has proposed and discussed the BlockASP technique, the research provided a case study to demonstrate the validity and superiority in facilitating the monitoring of dynamic blockchain behavior using AOP compared to traditional approaches such as Model-Driven Architecture (MDA).

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APA

Alsobeh, A. M. R., & Magableh, A. A. (2023). BlockASP: A Framework for AOP-Based Model Checking Blockchain System. IEEE Access, 11, 115062–115075. https://doi.org/10.1109/ACCESS.2023.3325060

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