Blockchain for IoT: The challenges and a way forward

Copyright © 2018 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved Bitcoin has revolutionized the decentralized payment system by excluding the need for a trusted third party, reducing the transaction (TX) fee and time involved in TX confirmation as compared to a conventional banking system. The underlying technology of Bitcoin is Blockchain, which was initially designed for financial TXs only. However, due to its decentralized architecture, fault tolerance and cryptographic security benefits such as user anonymity, data integrity and authentication, researchers and security analysts around the world are focusing on the Blockchain to resolve security and privacy issues of IoT. But at the same time, default limitations of Blockchain, such as latency in transaction confirmation, scalability concerning Blockchain size and network expansion, lack of IoT-centric transaction validation rules, the absence of IoT-focused consensus protocols and insecure device integration are required to be addressed before it can be used securely and efficiently in an IoT environment. Therefore, in this paper we analyze some of the existing consensus protocols used in various Blockchain-based applications, with a focus on investigating significant limitations in TX (Transaction) validation and consensus mechanism that make them inappropriate to be implemented in Blockchain-based IoT systems. We also propose a way forward to address these issues

Secure Sensor Prototype Using Hardware Security Modules and Trusted Execution Environments in a Blockchain Application: Wine Logistic Use Case

The security of Industrial Internet of Things (IIoT) systems is a challenge that needs to be addressed immediately, as the increasing use of new communication paradigms and the abundant use of sensors opens up new opportunities to compromise these types of systems. In this sense, technologies such as Trusted Execution Environments (TEEs) and Hardware Security Modules (HSMs) become crucial for adding new layers of security to IIoT systems, especially to edge nodes that incorporate sensors and perform continuous measurements. These technologies, coupled with new communication paradigms such as Blockchain, offer a high reliability, robustness and good interoperability between them. This paper proposes the design of a secure sensor incorporating the above mentioned technologies—HSMs and a TEE—in a hardware device based on a dual-core architecture. Through this combination of technologies, one of the cores collects the data extracted by the sensors and implements the security mechanisms to guarantee the integrity of these data, while the remaining core is responsible for sending these data through the appropriate communication protocol. This proposed approach fits into the Blockchain networks, which act as an Oracle. Finally, to illustrate the application of this concept, a use case applied to wine logistics is described, where this secure sensor is integrated into a Blockchain that collects data from the storage and transport of barrels, and a performance evaluation of the implemented prototype is providedEuropean Union’s Horizon Europe research and innovation program through the funding project “Cognitive edge-cloud with serverless computing” (EDGELESS) under grant agreement number 101092950FEDER/Junta de Andalucia-Consejeria de Transformacion Economica, Industria, Conocimiento y Universidades under Project B-TIC-588-UGR2

Generative Adversarial Learning for Intelligent Trust Management in 6G Wireless Networks

Emerging six generation (6G) is the integration of heterogeneous wireless networks, which can seamlessly support anywhere and anytime networking. But high Quality-of-Trust should be offered by 6G to meet mobile user expectations. Artificial intelligence (AI) is considered as one of the most important components in 6G. Then AI-based trust management is a promising paradigm to provide trusted and reliable services. In this article, a generative adversarial learning-enabled trust management method is presented for 6G wireless networks. Some typical AI-based trust management schemes are first reviewed, and then a potential heterogeneous and intelligent 6G architecture is introduced. Next, the integration of AI and trust management is developed to optimize the intelligence and security. Finally, the presented AI-based trust management method is applied to secure clustering to achieve reliable and real-time communications. Simulation results have demonstrated its excellent performance in guaranteeing network security and service quality

Blockchain and Reinforcement Neural Network for Trusted Cloud-Enabled IoT Network

The rapid integration of Internet of Things (IoT) services and applications across various sectors is primarily driven by their ability to process real-time data and create intelligent environments through artificial intelligence for service consumers. However, the security and privacy of data have emerged as significant threats to consumers within IoT networks. Issues such as node tampering, phishing attacks, malicious code injection, malware threats, and the potential for Denial of Service (DoS) attacks pose serious risks to the safety and confidentiality of information. To solve this problem, we propose an integrated autonomous IoT network within a cloud architecture, employing Blockchain technology to heighten network security. The primary goal of this approach is to establish a Heterogeneous Autonomous Network (HAN), wherein data is processed and transmitted through cloud architecture. This network is integrated with a Reinforced Neural Network (RNN) called ClouD_RNN, specifically designed to classify the data perceived and collected by sensors. Further, the collected data is continuously monitored by an autonomous network and classified for fault detection and malicious activity. In addition, network security is enhanced by the Blockchain Adaptive Windowing Meta Optimization Protocol (BAWMOP). Extensive experimental results validate that our proposed approach significantly outperforms state-of-the-art approaches in terms of throughput, accuracy, end-to-end delay, data delivery ratio, network security, and energy efficiency

La seguridad en redes SDN y sus aplicaciones

Introduction: The review article is the product of the research on Security in SDN networks and their applications, developed at the District University in 2020, presenting the latest advances, that have been made in security. Problem: The security weaknesses that SDN networks have had, due to being a new architecture. This has not allowed traditional networks to be replaced.   Objective: To carry out a review of the state of the art of SDN networks, focusing research on the security of the control layer and its advances. Methodology: The descriptive method is implemented, consulting databases such as Scopus, IEEE and ScienceDirect, using the following search criteria: SDN networks, security in SDN networks, applications with SDN networks and OpenFlow protocol. It is shown as a research sample: the Asian, European and American continents with years of research from 2014 to 2020. Results: Great advances have been made in terms of security for SDN networks, which allows us to see an early solution to the weaknesses that it currently faces.   Conclusion: SDN networks will solve all the challenges they face and will be consolidated as a solid and reliable architecture.   Originality: an important focus is taken on the security of SDN networks and the great development that has occurred in this regard is evident.   Limitations: SDN networks are a new architecture, so their development has been very little and advances in security have been significantly affected.Introducción: El artículo de revisión es producto de la investigación Seguridad en redes SDN y sus aplicaciones, desarrollada en la Universidad Distrital en el año 2020, presentando los últimos avances que se han logrado en seguridad. Problema: Las debilidades en seguridad que han tenido las redes SDN debido a ser una arquitectura nueva, esto no ha permitido que se reemplacen las redes tradicionales. Objetivo: realizar una revisión del estado del arte de las redes SDN enfocando la investigación la seguridad de la capa de control y sus avances. Metodología: se emplea el método descriptivo, se consultaron bases de datos como Scopus, IEEE y ScienceDirect, utilizando los siguientes criterios de búsqueda: SDN networks, security in SDN networks, applications with SDN networks y OpenFlow protocol, se tomó como muestra de investigación a los continentes asiático, europeo y americano con años de investigación desde el año 2014 hasta el año 2020. Resultados: se han desarrollado grandes avances en seguridad para las redes SDN, lo que permite ver una pronta solución a las debilidades que afronta en la actualidad. Conclusión: las redes SDN lograran resolver todos los retos a los que se enfrentan y se consolidara como una arquitectura sólida y confiable. Originalidad: se realiza un enfoque importante en la seguridad de las redes SDN y se evidencia el gran desarrollo que se ha presentado en este aspecto. Limitaciones: las redes SDN son una arquitectura nueva por lo que su desarrollo ha sido muy poco y los avances en seguridad se vieron afectados significativamente