International audience

The proliferation of fraudulent certificates not only erodes trust but also deceives employers and academic organizations, making it harder to verify the qualifications of applicants and employees. Our blockchain-based web application, enhanced with self-sovereign identity (SSI), addresses these challenges by ensuring the authenticity and integrity of academic credentials. Graduates gain full control over their credentials through SSI, allowing them to securely manage, share, and verify their qualifications independently. Educational institutions, in turn, benefit from streamlined processes such as bulk certificate generation and QR code-enabled verification, all within a decentralized and tamper-proof framework enabled by SSI. Additionally, we provide an off-chain cache to further enhance system efficiency by alleviating the blockchain’s load and achieving optimal response times for frequently accessed credentials.

Abstract Security faces huge challenges in Internet of Things (IoT) environments. In particular, conventional access control standards and models tend to be less tailored for IoT due to the constrained nature of smart objects. Usually, a powerful third party is used to handle the access control logic. However, this third party is lacking in transparency and could harm user privacy. Therefore, providing a distributed access control solution, while considering transparency and privacy-preserving awareness in IoT smart systems, is of paramount importance. The described issue can be addressed using the emergent Blockchain technology that provides a promising choice to build a new generation of decentralized and transparent access control solutions. This paper proposes a smart contract-based access control framework for IoT smart healthcare systems, which is based on smart contracts to provide a distributed and trustworthy access control, combined with the GTRBAC model to express fine-grained access control policies while considering temporal authorization constraints. To prove the feasibility and validity of the proposed framework, this paper also provides a detailed technical description and an initial implementation and execution. An experimental evaluation shows that security properties’ analyses on smart contracts achieved the best possible evaluation with no vulnerabilities found, and the cost of access control operations increases linearly as the number of policy constraints increases. Besides, a comparative analysis reveals that the proposed approach can achieve good results with low gas costs and latency.

Blockchain presents a promising and revolutionary technology for organizations' collaboration, particularly for Inter-Organizational Business Processes (IOBP).It addresses the lack-of-trust problem thanks to its transparency and decentralized features.However, while the adoption of Blockchain technology can alleviate some of IOBP's challenges, it does so at the expense of significant privacy issues.In fact, some process execution data, such as customers' data or business secrets, cannot be shared across the collaborating organizations owing to regulatory restrictions such as the General Data Protection Regulation (GDPR).To address trust and privacy issues in IOBP, this paper presents a Blockchain-based Self-Sovereign Identity (SSI) approach.The SSI concept is combined with a registry proof smart contract to provide an efficient privacy-preserving solution.The proposed approach is applied to the pharmaceutical supply chain case study and implemented on the Ethereum Blockchain.

The COVID-19 pandemic has emerged as a highly transmissible disease which has caused a disastrous impact worldwide by adversely affecting the global economy, health, and human lives. This sudden explosion and uncontrolled worldwide spread of COVID-19 has revealed the limitations of existing healthcare systems regarding handling public health emergencies. As governments seek to effectively re-establish their economies, open workplaces, ensure safe travels and progressively return to normal life, there is an urgent need for technologies that may alleviate the severity of the losses. This article explores a promising solution for secure Digital Health Certificate, called NovidChain, a Blockchain-based privacy-preserving platform for COVID-19 test/vaccine certificates issuing and verifying. More precisely, NovidChain incorporates several emergent concepts: (i) Blockchain technology to ensure data integrity and immutability, (ii) self-sovereign identity to allow users to have complete control over their data, (iii) encryption of Personally Identifiable Information to enhance privacy, (iv) W3C verifiable credentials standard to facilitate instant verification of COVID-19 proof, and (v) selective disclosure concept to permit user to share selected pieces of information with trusted parties. Therefore, NovidChain is designed to meet a high level of protection of personal data, in compliant with the GDPR and KYC requirements, and guarantees the user's self-sovereignty, while ensuring both the safety of populations and the user's right to privacy. To prove the security and efficiency of the proposed NovidChain platform, this article also provides a detailed technical description, a proof-of-concept implementation, different experiments, and a comparative evaluation. The evaluation shows that NovidChain provides better financial cost and scalability results compared to other solutions. More precisely, we note a high difference in time between operations (i.e., between 46% and 56%). Furthermore, the evaluation confirms that NovidChain ensures security properties, particularly data integrity, forge, binding, uniqueness, peer-indistinguishability, and revocation.

Ethereum is a blockchain-based platform that pro-vides a global computational infrastructure to run smart contracts. In order to assign a cost to smart contract and transaction execution, the Ethereum Blockchain adopts a gas-based metering approach which is designed to motivate miners to operate the network and protect it against attacks. More precisely, miners receive fees from all transactions included in the mined block in addition to the mining reward. Hence, the higher the gas price in the transactions, the higher the fee paid to the miner will be, resulting in faster selection and execution of higher priced gas transactions. Therefore, an Ethereum transaction sender is exposed to the non-trivial task of having to choose an optimal gas price, as underpaying likely results in a transaction not being picked by miners, whereas overpaying leads to superfluous costs. This paper provides recommendation approach that proposes an appropriate gas price to users. More precisely, it investigates different approaches of forecasting algorithms applied for gas price predictions for the next block in Ethereum Blockchain. The gas price is predicted using the Prophet model and the deep learning models, Long-Short Term Memory (LSTM) and Gated Recurrent Unit (GRU). It also aims to compare these approaches with the most used gas price oracles. An evaluation of the obtained results show that the LSTM and GRU proposed models outperform Prophet model as well as the gas price oracle Geth. In this case, LSTM and GRU provide a low mean squared error (MSE) of 0,008 whereas Geth gives an MSE of 0.016 and Prophet gives an MSE of 0.014.

The COVID-19 pandemic is sweeping across the world and causing widespread death and disruption. To this effect, nations have struggled to use technologies to detect and to monitor COVID-19 cases and related information. Unfortunately, both inconsistent and inaccurate information from "trustless" sources, and "mistrust" in effectively monitoring and reporting patients symptoms and condition have highlighted the failure of existing infrastructures to preserve human healthcare while maintaining patient's privacy and to slow down the widespread of the pandemic. This paper provides an insight of the perceived benefits of Blockchain to expectations of the COVID-19 pandemic in terms of providing "trust" in addressing information sharing in health systems while maintaining privacy. This paper exhibits a Blockchain-based COVID-19 Smart Healthcare approach that embraces Blockchain's benefits in healthcare systems.

Summary Modeling Cyber‐physical systems (CPS) is a challenging step that requires a lot of background from both the cyber and physical fields. However, there is a lack of studies in the existing literature that discuss the state of the art in modeling CPS or explore the research gaps in this area. In this paper, we survey existing approaches to modeling CPS. We focus on studying the considered CPS properties. Based on this study, we classify these properties and discuss their importance in different application domains. Moreover, research directions are presented to address key challenges in the specification of CPS models.

Cyber‐physical systems (CPSs) are characterized by a multitude of physical and software. Particularly time‐related properties are of paramount importance and they can impact the behaviour of these systems. Designing and verifying CPS while tackling time‐related and physical properties are very important steps in the CPS life cycle development. Indeed, it is necessary to capture and characterize the different features and their dependencies with time through expressive models. Then, these models must be verified to prove their correctness. Existing process modelling languages such as business process modelling notation (BPMN) has been widely used to model business processes. However, BPMN lacks several features for modelling rich CPS processes such as those related to time and physical properties. In this study, the authors propose a verification framework for collaborative time‐aware CPS processes. In this context, they propose to extend BPMN to support the various CPS concepts and properties. Based on this extension, they propose a consistency verification approach, which aims to verify that the time‐related and physical properties associated with each process do not give rise to conflicts. Finally, they propose a compatibility verification approach, which aims to verify that the set of involved CPS processes form consistent inter‐CPS processes.

Temporal constraints are one cornerstone of process specification and verification in the whole process lifecycle. Nevertheless, in the existing research approaches, little consideration has been given to the subject of verification of advanced temporal constraints such as absolute temporal constraints associated with relative temporal constraints. In this paper, we handle the problem of verification while considering advanced relative and absolute temporal constraints. Firstly, a set of rules are proposed to prevent the designer to specify some faulty temporal combinations of absolute temporal constraints, early on, before the execution step. Second, to capture relative temporal constraints, we propose a mapping step whose aim is to map timed business processes into timed automata. Using the defined formal model, we finally investigate a model checking based verification approach that aims at validating business processes against their temporal constraints.

Business-to-business (B2B) e-commerce market is expected to expand rapidly in coming years. In this context, organizations tend to rely more on business process management (BPM) to streamline their operations. The business process field is influenced by a wide range of temporal constraints which rise from legal, regulatory, and managerial rules. One of the most promising standards for business process modeling, namely the Business process Model and notation BPMN poorly addresses the time dimension so far. In this paper, we elaborate an extension to BPMN 2.0 to handle the time dimension. The aim of this BPMN extensions is to support business analysts and modellers in easily including the needed temporal constraints in their processes. We motivate and justify our proposed extensions by means of illustrative case studies. Furthermore, based on the proposed extensions, a verification approach based on the model checking technique is used to diagnose potential temporal violations of the process model. The work presented in this paper sets foundation for later automation of these constraints through process execution engines.