Fortifying Federated Learning in IIoT: leveraging blockchain and digital twin innovations for enhanced security and resilience

Ensuring robustness against adversarial attacks is imperative for Machine Learning (ML) systems within the critical infrastructures of the Industrial Internet of Things (IIoT). This paper addresses vulnerabilities in IIoT systems, particularly in distributed environments like Federated Learning (FL) by presenting a resilient framework - Secure Federated Learning (SFL) specifically designed to mitigate data and model poisoning, as well as Sybil attacks within these networks. Sybil attacks, involving the creation of multiple fake identities, and poisoning attacks significantly compromise the integrity and reliability of ML models in FL environments. Our SFL framework leverages a Digital Twin (DT) as a critical aggregation checkpoint to counteract data and model poisoning attacks in IIoT's distributed settings. The DT serves as a protective mechanism during the model update aggregation phase, substantially enhancing the system's resilience. To further secure IIoT infrastructures, SFL employs blockchain-based Non-Fungible Tokens (NFTs) to authenticate participant identities, effectively preventing Sybil attacks by ensuring traceability and accountability among distributed nodes. Experimental evaluation within IIoT scenarios demonstrates that SFL substantially enhances defensive capabilities, maintaining the integrity and robustness of model learning. Comparative results reveal that the SFL framework, when applied to IIoT federated environments, achieves a commendable 97% accuracy, outperforming conventional FL approaches. SFL also demonstrates a remarkable reduction in loss rate, recording just 0.07 compared to the 0.14 loss rate experienced by standard FL systems. These findings highlight the efficiency and applicability of the SFL framework in enhancing data security and traceability within the IIoT ecosystem

Machine learning-driven intelligent water quality assessment for enhanced drinking safety and real-time consumer awareness

As to the sphere of smart water management and managing water Internet of Things (IoT) systems, water condition safety for drinking is very important. The proposed methodology, known as the Smart Water Consumption Monitoring System (SWCMS), is based on the WaterNet dataset acquired from a standard data repository for training the selected machine learning (ML) models. For water quality parameters such as temperature, turbidity, pH, and some chemical concentrations, the system uses real-time sensors. At the testing phase, information received from the sensors is time-stamped, and with the utilization of applicable ML approaches, potential challenges; assessment of water quality is processed. This encompasses the employment of advanced instruments for the detection of water quality with concentration on pH and other chemical values through a detection accuracy rate of over 95% on any other signs of abnormalities. This processed information is further availed with the timestamps to the consumers' mobile phones through a user interface application for real-time awareness and timely response. With the aid of timely information about their drinking water, the SWCMS increases the water safety parameter by 90% and the overall consumer awareness by 92.5%, thereby creating an effective health parameter among the public

Device-to-device communication in 5G heterogeneous network based on game-theoretic approaches: A comprehensive survey

In the evolution of Fifth-Generation (5G) oriented wireless communication technology, the conventional wireless communication performance indicators, including network capacity, spectrum efficiency, and Quality of Services (QoS), need to be continuously improved to optimize the utilization of the wireless spectrum. As a key candidate technology for 5G, Device-to-Device (D2D) communication improves system performance, enhances user experience, and expands cellular communication applications. D2D communication provides a better quality of services with minor communication delays, improving overall network performance, efficient utilization of network resources, and enhanced network capacity by utilizing short-distance communication between devices in close proximity. D2D communication technology has recently received widespread attention due to its promising nature. This survey comprehensively reviews D2D communication and the techniques involved in different phases of successful D2D communication. In addition, this survey paper also presents an extensive review of proposed solutions based on game-theoretic approaches aiming to optimize the performance of D2D communication in 5G. The major objectives of this survey paper are to thoroughly analyse current developments in D2D communication and review game theory applications in D2D communication. This survey also identifies challenges in D2D communication, opens issues, and suggests future research areas

A survey on Zero touch network and Service Management (ZSM) for 5G and beyond networks

Abstract Faced with the rapid increase in smart Internet-of-Things (IoT) devices and the high demand for new business-oriented services in the fifth-generation (5G) and beyond network, the management of mobile networks is getting complex. Thus, traditional Network Management and Orchestration (MANO) approaches cannot keep up with rapidly evolving application requirements. This challenge has motivated the adoption of the Zero-touch network and Service Management (ZSM) concept to adapt the automation into network services management. By automating network and service management, ZSM offers efficiency to control network resources and enhance network performance visibility. The ultimate target of the ZSM concept is to enable an autonomous network system capable of self-configuration, self-monitoring, self-healing, and self-optimization based on service-level policies and rules without human intervention. Thus, the paper focuses on conducting a comprehensive survey of E2E ZSM architecture and solutions for 5G and beyond networks. The article begins by presenting the fundamental ZSM architecture and its essential components and interfaces. Then, a comprehensive review of the state-of-the-art for key technical areas, i.e., ZSM automation, cross-domain E2E service lifecycle management, and security aspects, are presented. Furthermore, the paper contains a summary of recent standardization efforts and research projects towards the ZSM realization in 5G and beyond networks. Finally, several lessons learned from the literature and open research problems related to ZSM realization are also discussed in this paper

Industry 5.0:a survey on enabling technologies and potential applications

Abstract Industry 5.0 is regarded as the next industrial evolution, its objective is to leverage the creativity of human experts in collaboration with efficient, intelligent and accurate machines, in order to obtain resource-efficient and user-preferred manufacturing solutions compared to Industry 4.0. Numerous promising technologies and applications are expected to assist Industry 5.0 in order to increase production and deliver customized products in a spontaneous manner. To provide a very first discussion of Industry 5.0, in this paper, we aim to provide a survey-based tutorial on potential applications and supporting technologies of Industry 5.0. We first introduce several new concepts and definitions of Industry 5.0 from the perspective of different industry practitioners and researchers. We then elaborately discuss the potential applications of Industry 5.0, such as intelligent healthcare, cloud manufacturing, supply chain management and manufacturing production. Subsequently, we discuss about some supporting technologies for Industry 5.0, such as edge computing, digital twins, collaborative robots, Internet of every things, blockchain, and 6G and beyond networks. Finally, we highlight several research challenges and open issues that should be further developed to realize Industry 5.0