Antonio Villafranca
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Antonio Villafranca has a total of 11 co-authors. Here are the top co-authors by number of shared publications:
- Maria-Dolores Cano
Department of Information and Communications Technologies, Universidad Politécnica de Cartagena, 30202 Cartagena, Spain
4 shared publications - Igor Tasic
Faculty of Economics and Business, UCAM Universidad Católica San Antonio de Murcia, 30107 Murcia, Spain
2 shared publications Jesus Ochoa Rego
Department of Agricultural Engineering Universidad Politécnica de Cartagena Cartagena Spain
2 shared publicationsAlmudena Gimenez
Department of Agricultural Engineering Universidad Politécnica de Cartagena Cartagena Spain
1 shared publication- Almudena Giménez
Department of Agronomical Engineering, Universidad Politécnica de Cartagena, 30203 Cartagena, Spain
1 shared publication Igor Tasic
Faculty of Economics and Business UCAM Universidad Católica San Antonio de Murcia Murcia Spain
1 shared publication
Latest Publications
- Open Access
- 26 April 2026
- Published by Wiley in International Journal of Network Management
- Vol. 36 (3)
A Blockchain‐Less Traceability System for Agriculture Using DAG, IPFS, and Serverless Deployments
Ensuring transparency and integrity in agricultural data management is a critical challenge as the sector increasingly relies on advanced technologies. The primary problem is maintaining data traceability and security throughout the supply chain. In this paper, we explore the use of directed acyclic graph (DAG) technology to address these challenges in agricultural environments. We have implemented the corresponding software to test the following three DAG‐based data storage and traceability scenarios: serverless, utilizing the interplanetary file system (IPFS), and a centralized server for data storage and transaction validation. Our results demonstrate that DAG and PoA ensure fast and secure transaction validation, crucial to maintaining trust and efficiency in the agricultural supply chain. We find that each scenario presents unique strengths and limitations, suggesting that a hybrid approach may offer the most robust solution for agricultural data management.
- 26 April 2026
- Published by Wiley in International Journal of Network Management
- Vol. 36 (3)
Open AccessA Blockchain‐Less Traceability System for Agriculture Using DAG, IPFS, and Serverless Deployments
Ensuring transparency and integrity in agricultural data management is a critical challenge as the sector increasingly relies on advanced technologies. The primary problem is maintaining data traceability and security throughout the supply chain. In this paper, we explore the use of directed acyclic graph (DAG) technology to address these challenges in agricultural environments. We have implemented the corresponding software to test the following three DAG‐based data storage and traceability scenarios: serverless, utilizing the interplanetary file system (IPFS), and a centralized server for data storage and transaction validation. Our results demonstrate that DAG and PoA ensure fast and secure transaction validation, crucial to maintaining trust and efficiency in the agricultural supply chain. We find that each scenario presents unique strengths and limitations, suggesting that a hybrid approach may offer the most robust solution for agricultural data management.
- Open Access
- 31 October 2025
- Published by Elsevier in Internet of Things
- Vol. 34
A lightweight edge-DL intrusion detection system for IoT sustainable smart-agriculture
- 31 October 2025
- Published by Elsevier in Internet of Things
- Vol. 34
Open AccessA lightweight edge-DL intrusion detection system for IoT sustainable smart-agriculture
- Open Access
- 6 October 2025
- Published by MDPI AG in Machine Learning and Knowledge Extraction
- Vol. 7 (4) , 115
AI-Enabled IoT Intrusion Detection: Unified Conceptual Framework and Research Roadmap
The Internet of Things (IoT) revolutionizes connectivity, enabling innovative applications across healthcare, industry, and smart cities but also introducing significant cybersecurity challenges due to its expanded attack surface. Intrusion Detection Systems (IDSs) play a pivotal role in addressing these challenges, offering tailored solutions to detect and mitigate threats in dynamic and resource-constrained IoT environments. Through a rigorous analysis, this study classifies IDS research based on methodologies, performance metrics, and application domains, providing a comprehensive synthesis of the field. Key findings reveal a paradigm shift towards integrating artificial intelligence (AI) and hybrid approaches, surpassing the limitations of traditional, static methods. These advancements highlight the potential for IDSs to enhance scalability, adaptability, and detection accuracy. However, unresolved challenges, such as resource efficiency and real-world applicability, underline the need for further research. By contextualizing these findings within the broader landscape of IoT security, this work emphasizes the critical importance of developing IDS solutions that ensure the reliability, privacy, and security of interconnected systems, contributing to the sustainable evolution of IoT ecosystems.
- 6 October 2025
- Published by MDPI AG in Machine Learning and Knowledge Extraction
- Vol. 7 (4) , 115
Open AccessAI-Enabled IoT Intrusion Detection: Unified Conceptual Framework and Research Roadmap
The Internet of Things (IoT) revolutionizes connectivity, enabling innovative applications across healthcare, industry, and smart cities but also introducing significant cybersecurity challenges due to its expanded attack surface. Intrusion Detection Systems (IDSs) play a pivotal role in addressing these challenges, offering tailored solutions to detect and mitigate threats in dynamic and resource-constrained IoT environments. Through a rigorous analysis, this study classifies IDS research based on methodologies, performance metrics, and application domains, providing a comprehensive synthesis of the field. Key findings reveal a paradigm shift towards integrating artificial intelligence (AI) and hybrid approaches, surpassing the limitations of traditional, static methods. These advancements highlight the potential for IDSs to enhance scalability, adaptability, and detection accuracy. However, unresolved challenges, such as resource efficiency and real-world applicability, underline the need for further research. By contextualizing these findings within the broader landscape of IoT security, this work emphasizes the critical importance of developing IDS solutions that ensure the reliability, privacy, and security of interconnected systems, contributing to the sustainable evolution of IoT ecosystems.
- Open Access
- 5 May 2025
- Published by Elsevier in Simulation Modelling Practice and Theory
- Vol. 142
Comparing blockchain and DAG technologies for smart agriculture traceability in terms of efficiency and latency
- 5 May 2025
- Published by Elsevier in Simulation Modelling Practice and Theory
- Vol. 142
Open AccessComparing blockchain and DAG technologies for smart agriculture traceability in terms of efficiency and latency
- Open Access
- 1 January 2019
- Published by Egea Spa in ECONOMIA & MANAGEMENT
- Vol. 1 (1) , 21-24
Brexit: il danno è già stato fatto
- 1 January 2019
- Published by Egea Spa in ECONOMIA & MANAGEMENT
- Vol. 1 (1) , 21-24
Open AccessBrexit: il danno è già stato fatto