ProACT: Probabilistic Analysis and Countermeasures Tool for Blockchain Supply Chains With Smart Contracts Composition

IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Rangu Manjula, Naveen Chauhan
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引用次数: 0

Abstract

This study introduces the ProACT (Probabilistic Analysis and Countermeasures Tool) framework, which uses Bayesian Networks, Colored Petri Nets, and NuSMV (new symbolic model validator) to check and improve smart contracts in blockchain-based supply chains. The main aim is to make smart contracts safer and more reliable in the Agrochem and Fertilizers Supply Chain. The research focuses on the need for better security in blockchain applications. There is a gap in current methods that handle the unpredictable nature of smart contracts. This study seeks to fill this gap with a new approach. The ProACT framework combines different models. Bayesian Networks help understand dependencies and uncertainties. Colored Petri Nets show how contracts change over time. NuSMV checks the contracts formally to find issues. The study includes a detailed case study and tests. Results show that ProACT is better at finding problems and checking contracts quickly. It also reduces the impact of attacks on the system. The findings are important because they offer a new way to make smart contracts safer. This helps improve the overall security of blockchain-based supply chains.

ProACT:基于智能合约组合的区块链供应链概率分析与对策工具
本研究介绍了ProACT(概率分析和对策工具)框架,该框架使用贝叶斯网络、彩色Petri网和NuSMV(新的符号模型验证器)来检查和改进基于区块链的供应链中的智能合约。其主要目的是使智能合约在农化和化肥供应链中更安全、更可靠。研究的重点是区块链应用程序对更好的安全性的需求。目前处理智能合约不可预测性的方法存在差距。这项研究试图用一种新的方法来填补这一空白。ProACT框架结合了不同的模型。贝叶斯网络有助于理解依赖性和不确定性。彩色Petri网显示了合同如何随时间变化。NuSMV正式检查合同以发现问题。该研究包括详细的案例研究和测试。结果表明,ProACT在快速发现问题和检查合同方面做得更好。它还减少了攻击对系统的影响。这些发现很重要,因为它们提供了一种使智能合约更安全的新方法。这有助于提高基于区块链的供应链的整体安全性。
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来源期刊
Concurrency and Computation-Practice & Experience
Concurrency and Computation-Practice & Experience 工程技术-计算机:理论方法
CiteScore
5.00
自引率
10.00%
发文量
664
审稿时长
9.6 months
期刊介绍: Concurrency and Computation: Practice and Experience (CCPE) publishes high-quality, original research papers, and authoritative research review papers, in the overlapping fields of: Parallel and distributed computing; High-performance computing; Computational and data science; Artificial intelligence and machine learning; Big data applications, algorithms, and systems; Network science; Ontologies and semantics; Security and privacy; Cloud/edge/fog computing; Green computing; and Quantum computing.
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