Internet of Things (IoT) sensors monitor temperature-sensitive goods throughout the supply chain. Nowadays, blockchain is being widely used for traceability, transparency, and immutable storage of this data. However, this approach lacks a mechanism to assess the trustworthiness of the data, and as a result, the reliability of the system is constrained by the quality of […]
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The convergence of blockchain and Internet of Things (IoT) has become increasingly prevalent recently, as it addresses challenges such as single point of failure and security concerns associated with IoT.Blockchain offers immutable data storage, availability, and transparency, but a significant drawback lies in its inability to verify the truthfulness of the data stored on it. […]
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Recently, there has been a surge of interest surrounding the integration of blockchain with the Internet of Things (IoT), aiming to address IoT’s inherent issues like single points of failure and concerns related to data integrity. However, although blockchain provides decentralization and transparency, it does not guarantee the accuracy and reliability of IoT-generated data. Therefore, […]
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The futuristic energy grids comprise of predominantly renewable generation, to align with the sustainable development goals. This would require integration of renewable energy sources at different levels of the power system out of which, consumers turning into power producers, often referred to as prosumers is an important aspect. Prosumers who generate excess power beyond self-consumption […]
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A wide adoption of Artificial Intelligence (AI) can be observed in recent years over networking to provide zero-touch, full autonomy of services towards the next generation Beyond 5G (B5G)/6G. However, AI-driven attacks on these services are a major concern in reaching the full potential of this future vision. Identifying how resilient the AI models are […]
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Federated learning (FL) is an intriguing approach to privacy-preserving collaborative learning. Decentralised FL is achieving increased favour for investigation due to the mitigation of vulnerability for a single point of failure and more controllability for end users over their models. However, many existing decentralised FL systems face limitations, such as privacy concerns, latency in aggregation, […]
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Federated Learning (FL) is an emerging privacy-preserved distributed Machine Learning (ML) technique where multiple clients can contribute to training an ML model without sharing private data. Even though FL offers a certain level of privacy by design, recent works show that FL is vulnerable to numerous privacy attacks. One of the key features of FL […]
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Blockchain offers cryptographically secure storage for recording transactions. However, one issue with blockchains is the problem of bad data and data reliability, where bad data refers to inaccurate, incomplete, or irrelevant data. This paper investigates how machine learning (ML) can be used to identify inaccurate sensor data added to a blockchain in Internet of Vehicles […]
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Network Slicing (NS) is a predominant technology in future telecommunication networks, including Fifth Generation (5G), which supports the realization of heterogeneous applications and services. It allows the allocation of a dedicated logical network slice of the physical network to each application. Security is one of the paramount challenges in an NS ecosystem. Several technologies, including […]
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Network slicing (NS) is a utilitarian technology that enables heterogeneous smart use cases in Fifth Generation (5G) and beyond networks. Smart hospitals require NS to realize its applications with diverse network requirements, which can not facilitate via traditional networks in hospital environments. NS can be performed under different strategies based on dynamicity, ownership, and application. […]
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