Decision Support Systems (DSS) have traditionally relied on relational data warehouses and ETL pipelines, which provide stable analytics over structured data but struggle with the rapid emergence of heterogeneous data lakes. Rebuilding DSS infrastructures to natively accommodate NoSQL sources is rarely feasible due to the critical role of legacy systems. This paper addresses the challenge of incrementally extending DSS with evolving NoSQL data while preserving analytical consistency, integrity, and compatibility with existing assets. To this end, we propose an MDE-based approach that leverages a unified model to abstract NoSQL structures into entities, attributes, and relationships. A set of transformation rules is introduced to generate evolution operations that update DSS models and keep them consistent. We demonstrate the applicability of our approach through a medical case study based on the MIMIC-III clinical database, extended with NoSQL sources from telemedicine, Internet of Medical Things, and rehabilitation data. The results show that our method enables seamless model evolution, preserving semantics and unlocking new analytical capabilities without disrupting the operational core.

Digital Twins (DTs) are essential in modern Cyber-Physical Systems (CPS) for real-time monitoring, representation, and optimization of complex assets. However, semantic interoperability across heterogeneous subsystems remains challenging due to the complexity of formal modeling languages like SysML. This paper introduces a novel AI-assisted methodology bridging natural language system specifications and formal, machine interpretable models for DTs. Our contributions include: (1) a generative AI framework based on LLaMA3 for automatic SysML diagram generation, (2) a rule based pipeline transforming diagrams into semantically enriched ontologies, and (3) an ontology alignment mechanism enabling interoperability across DT systems. Validation on MAGPIE project use cases: Vessel Traffic Monitoring and Port Equipment Maintenance, demonstrates the approach’s effectiveness in model generation, ontology integration, and reasoning, highlighting the potential of combining MBSE with large language models to advance semantic interoperability in multi domain digital ecosystems.

This demonstration presents TraSSI, a confidential traceability system designed for Self-Sovereign Identity (SSI) based Inter-organizational Business Processes (IOBPs). Unlike traditional Blockchain solutions, which often record transactional data on the ledger and raise privacy concerns, many SSI systems prioritize data control and compliance with privacy regulations by not storing these exchanges on the Blockchain. However, this introduces challenges for legal traceability, especially in audit scenarios. TraSSI addresses these challenges by integrating Zero-Knowledge Proofs (ZKP) and Fully Homomorphic Encryption (FHE) to provide an efficient balance between privacy and transparency. This demo will highlight the system's application to secure traceability without compromising privacy and targets researchers and developers in the fields of privacy and Blockchain technology.

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.

Blockchain is a potential technology for collaborating organizations, notably for executing their Inter-Organizational Business Processes (IOBPs). While Blockchain’s transparency and decentralized characteristics address the lack-of-trust issue in IOBPs, many existing Blockchain solutions share this data on the ledger, often at the expense of serious privacy concerns. Alternatively, Self-Sovereign Identity (SSI) systems are revolutionary Blockchain-based solutions that provide complete data control. Unlike traditional Blockchain solutions, many SSI systems do not record the exchange of transactional data between entities on the ledger in order to comply with privacy regulations. However, this can imply a gap in cases where legal traceability is required for audit purposes. To address traceability issues in SSI-based IOBP, this paper leverages Zero-Knowledge Proof (ZKP) and Fully Homomorphic Encryption (FHE) to provide an efficient privacy-preserving traceability solution. The purpose of this paper is to achieve traceability that strikes a balance between privacy and transparency. This paper also provides a proof-of-concept implementation and a comparative evaluation. The evaluation shows that the proposed ZKP approach provides better financial cost and performance results compared to traditional Blockchain-based traceability solutions.

In the rapidly evolving workplace, ensuring continuous employee development and motivation is a growing challenge for companies. Traditional reward systems often fail to encourage continuous learning and teamwork among employees. To address these limitations, this paper introduces a blockchain-based solution that uses non-fungible tokens (NFTs) to revolutionize employee training and reward systems. Through this approach, employees can earn and exchange tokens for access to quality training programs, promoting continuous professional growth. Additionally, the ability to transfer tokens among employees encourages peer recognition and collaboration. Leveraging blockchain technology, the proposed solution offers enhanced security, transparency, and data immutability, making it an effective solution for modern companies.

Diploma fraud threatens the equity of academic and professional opportunities, undermining the legitimacy of educational institutions. Our paper aims to mitigate this issue using blockchain technology. Our innovative web-based application leverages blockchain to ensure the integrity and credibility of academic credentials. It securely issues, stores, and verifies degrees and certificates, offering real-time verification and immutable diploma storage. The platform also streamlines certification processes for educational institutions and event planners with bulk diploma generation and efficient conference management features. A QR code is integrated into the certification process, enabling quick and easy verification by allowing users to scan and instantly access the corresponding diploma record on the blockchain.

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.

In the blockchain environment, smart contracts are computer programs that run on the blockchain platform. However, the development of smart contracts is a major challenge for developers, since blockchain platforms are still evolving. Owing to the inherited nature of blockchain, developing smart contracts without introducing vulnerabilities is not an easy task, as the deployed code is immutable and can be invoked by anyone with access to the network. Smart contracts have proved to be error-prone in practice due to the complexity of programming. Additionally, non-functional requirements, such as service cost, security, performance, authorization, and authentication, should be well implemented and defined in computer systems. In this paper, we aim to present a systematic literature review to outline in detail different approaches of smart contracts generation. Furthermore, we present a comparison of the existing approaches based on a classification according to automation paradigm and a set of defined criteria. Finally, we discuss the gaps in the literature, as well as identify a set of potential challenges which can significantly strengthen the existing work. The study shows that the examined works focused only on a limited number of specific features, such as authorization, asset control, and security. Additionally, formal verification of smart contracts and data privacy are poorly addressed.

With the speed rise of heterogeneous Blockchain (BC) platforms, interoperability became a critical area of research barrer for a variety of use cases, ranging from supply chain to healthcare. Consequently, a number of BC interoperability solutions were proposed to overcome these issues. One of these is Bifröst, a notary-based BC interoperability Application Programming Interface (API) which enables users or existing applications to interact seamlessly with multiple BCs. An early prototype of Bifröst was built, which proved its feasibility, nonetheless, it failed to allow interactions with Smart Contracts (SCs) across BCs. In this context, we present in this paper an extension of Bifröst architecture enabling secure cross-BC SCs using the Trusted Execution Environment (TEE). The proposed architecture is also fault tolerant by means of a logging module that facilitates the recovery of partially completed transactions in case of a crash.

Deploying a cloud configuration in a real cloud platform is mostly cost- and time- consuming, as large number of cloud resources have to be rented for the time needed to run the configuration. Thereafter, cloud simulation tools are used as a cheap alternative to test cloud configuration. However, most of the existing cloud simulation tools require extensive technical skills and do not support simulation of any kind of cloud resources. In this context, using a model-driven approach can be helpful as it allows developers to efficiently describe their needs at a high level of abstraction. To do, we propose, in this article, a model-driven engineering approach based on the Open Cloud Computing Interface(OCCI) standard metamodel and CloudSim toolkit. We firstly extend OCCI metamodel for the supporting simulation of any kind of cloud resources. Afterward, to illustrate the extensibility of our approach, we enrich the proposed metamodel by new simulation capabilities. As proof of concept, we study the elasticity and pricing strategies of Amazon Web Services (AWS). This article benefits from OCCIware Studio to design an OCCI simulation extension and to provide a simulation designer for designing cloud configurations to be simulated. We detail the approach process from defining an OCCI simulation extension until the generation and the simulation of the OCCI cloud configurations. Finally, we validate the proposed approach by providing a realistic experimentation to study its usability, the resources coverage rate and the cost. The results are compared with the ones computed from AWS.

This paper presents an approach for fragmenting business processes over 2 types of complementary platforms referred to as cloud resources and edge resources. Fragmentation caters to the separate needs and requirements of business processes’ owners. Indeed, some owners prioritize the security of their fragmented processes over availability while others prioritize the reliability of their fragmented processes over performance. Despite its benefits, fragmentation raises many concerns like how to reduce communication delays between disparate fragments and how to maintain acceptable loads over all the distributed resources. To identify the necessary cloud and edge resources that would accommodate fragmented business processes, the approach resorts to Allen’s time algebra allowing to simultaneously reason over both resources’ availability-time intervals and processes’ use-time intervals. This reasoning covers a good range of time relations like overlaps, during, and meets, is aware of resources’ properties like limited-but-extensible, and satisfies business processes’ requirements like data freshness. The fragmentation approach, in this paper, is illustrated with a banking case-study, validated through a system developed on top of Google Colaboratory, and evaluated through a set of real experiments.

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 main objective of the NETTUNIT "TUNisia-Italy Cross-Border Environment Net" project on a 2.5 years period of time (2020-2022) is to propose an emergency response platform in purpose to solve occurring disasters in the border between Tunisian and Italian countries. In this paper, we explain the adopted emergency procedures (mainly; the response phase). To model the emergency response, NETTUNIT combines three modelling languages, notably BPMN, CMMN and DMN. Moreover, in this project we need to model and share data for the emergency process between the different stakeholders, for that, we propose a domain ontology. Indeed, we select and give an overview of three state of the art ontologies. The proposed ontology for NETTUNIT will be built on the basis of these latters and aims to mainly adress their limitations and to further advance the understanding of the emergency response for all involved actors.

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.

Globalization pressure on organizations calls for new approaches to survive, grow, and compete. An approach is to allow inter-organizational business processes (IOBP) collaboration where each partner would expose its public know-how without putting its private know-how at-risk nor impeding this collaboration from happening. Private processes would be the result of running views over public processes. For a successful IOBP collaboration, constraints like temporal need to be satisfied. Organizations could have different time requirements. This paper presents an approach for generating views over collaborative IOBP along with satisfying the combined temporal constraints that would restrict these collaborative IOBP. The paper also details how the consistency of these constraints would be achieved. The approach is illustrated using an online shopping scenario and demonstrated through a system.

Blockchain has emerged as one of the most promising technologies in Industry 4.0. It has the potential to improve interorganizational processes, especially by addressing lack-of-trust issues. Recently, sophisticated Blockchain-based BPM systems have been proposed to enable the execution of business processes in the Blockchain. Despite the importance of the aspect of time in process modeling, these approaches do not provide methods to represent nor to manage temporal constraints for business processes. This insufficiency is due to inherent limitations of Blockchain platforms which do not offer native means of measuring time. We have proposed an approach that enables the transformation of a large set of temporal constraints from a business process model to a smart contract code. In this paper, we aim to validate the feasibility and efficiency of our prior work through a case study of organ transfer by healthcare drone delivery.

Cloud and Fog computing have been widely recognized as attractive solutions in both academic and industrial sectors. Despite their benefits, the adoption of Cloud and Fog computing still have considerable challenges to be handled due to the increase of client requirements. A crucial issue, in this context, is how to verify the correctness of Cloud and Fog systems. The use of formal methods is an efficient mean which provides a real help for the designer to evaluate the behaviour of a system and prevent errors before its implementation. In this paper, we present a systematic literature review (SLR) on the current state of the art in this field. We collect the existing studies on the use of formal methods for proving the correctness of Cloud and Fog systems. The proposed approaches are compared based on some technical properties such as the verification methods, the verification tools, the considered properties, and the application domains. In addition, future directions which need more investigations are presented. We believe that our paper will be useful for industry and academic researchers to understand the existing contributions that deal with the correctness of Cloud and Fog systems. Moreover, it helps them to address several gaps in the literature.