@inproceedings{6c9f636367774c4ebb739c1c57b83c1d,
title = "Three-Valued Model Checking Smart Contract Systems with Trust Under Uncertainty",
abstract = "Blockchain systems based on smart contracts are critical systems that have to be verified in order to ensure their reliability and efficiency. Verifying these systems is a major challenge that is still an active topic of research in different domains. In this paper, we focus on verifying these systems that we model using trust protocols under uncertainty. Specifically, we address the problem using an effective verification approach called three-valued model checking. We introduce a new logic by extending the recently proposed Computation Tree Logic of Trust (TCTL) to the three-valued case (3 v- TCTL ) to reason about trust with uncertainty over smart contract-based systems. We also propose a new transformation approach to reduce the 3 v- TCTL model checking problem to the classical case. We apply our approach to a smart contract-based drug traceability system in the healthcare supply chain. The approach is implemented using a Java toolkit that automatically interacts with the NuSMV model checker. We verify this system against a set of specifications and report the results of our experiments.",
keywords = "Blockchain, Smart contract, TCTL, Three-valued model checking, Trust, Uncertainty",
author = "Ghalya Alwhishi and Jamal Bentahar and Ahmed Elwhishi",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 3rd International Conference on Deep Learning, Big Data and Blockchain, DBB 2022 ; Conference date: 22-08-2022 Through 24-08-2022",
year = "2023",
doi = "10.1007/978-3-031-16035-6_10",
language = "British English",
isbn = "9783031160349",
series = "Lecture Notes in Networks and Systems",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "119--133",
editor = "Irfan Awan and Muhammad Younas and Jamal Bentahar and Salima Benbernou",
booktitle = "The International Conference on Deep Learning, Big Data and Blockchain, DBB 2022",
address = "Germany",
}