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As the integration of Internet of Things devices with cloud computing proliferates, the paramount importance of privacy preservation comes to the forefront. This survey paper meticulously explores the landscape of privacy issues in the…
The Internet traffic data produced by the Internet of Things (IoT) devices are collected by Internet Service Providers (ISPs) and device manufacturers, and often shared with their third parties to maintain and enhance user services.…
Computational task offloading based on edge computing can deal with the performance bottleneck of traditional cloud-based systems for Internet of things (IoT). To further optimize computing efficiency and resource allocation, collaborative…
Machine learning can analyze vast amounts of data generated by IoT devices to identify patterns, make predictions, and enable real-time decision-making. By processing sensor data, machine learning models can optimize processes, improve…
Wide scale interest and adoption of Internet of Things (IoT) technologies is fuelling innovation in the way individuals and even machines can interact to exchange knowledge. One area of particular interest is that of analytics. Ever…
A social approach can be exploited for the Internet of Things (IoT) to manage a large number of connected objects. These objects operate as autonomous agents to request and provide information and services to users. Establishing trustworthy…
The Internet of Things (IoT) consistently generates vast amounts of data, sparking increasing concern over the protection of data privacy and the limitation of data misuse. Federated learning (FL) facilitates collaborative capabilities…
The Internet of Things IoT is experiencing exponential growth in research and industry, but it still suffers from privacy and security vulnerabilities. Conventional security and privacy approaches tend to be inapplicable for IoT, mainly due…
Researchers find weaknesses in current strategies for protecting privacy in large datasets. Many anonymized datasets are reidentifiable, and norms for offering data subjects notice and consent over emphasize individual responsibility. Based…
The sharing of data and digital assets in a decentralized settling is associated with various legislative challenges, including, but not limited to, the need to adhere to legal requirements with respect to privacy (e.g. data protection…
Internet of things (IoT) produces massive data from devices embedded with sensors. The IoT data allows creating profitable services using machine learning. However, previous research does not address the problem of optimal pricing and…
The growing complexity of Internet of Things (IoT) environments, particularly in cross-domain data sharing, presents significant security challenges. Existing data-sharing schemes often rely on computationally expensive cryptographic…
The emergence of the Internet of Things (IoT) has resulted in a significant increase in research on e-health. As the amount of patient data grows, it has become increasingly challenging to protect patients' privacy. Patient data is commonly…
The Internet of Things, or IoT, refers to the billions of physical objects around the planet that are now connected to the Internet, many of which store and exchange the data without human interaction. In recent years the Internet of Things…
Smart devices are becoming inseparable from daily lives and are improving fast for providing intelligent services and remote monitoring and control. In order to provide personalized and customized services more personal data collection is…
The integration of Internet of Things (IoT) devices in healthcare has revolutionized patient care by enabling real-time monitoring, personalized treatments, and efficient data management. However, this technological advancement introduces…
A typical user interacts with many digital services nowadays, providing these services with their data. As of now, the management of privacy preferences is service-centric: Users must manage their privacy preferences according to the rules…
Blockchain has the potential to revolutionize the way we store, use, and process data. Information on most blockchains can be viewed by every node hosting the blockchain, which means that most blockchains cannot handle private data.…
The difficulty in acquiring a sufficient amount of training data is a major bottleneck for machine learning (ML) based data analytics. Recently, commoditizing ML models has been proposed as an economical and moderate solution to ML-oriented…
This paper deals with the problem of properly simulating the Internet of Things (IoT). Simulating an IoT allows evaluating strategies that can be employed to deploy smart services over different kinds of territories. However, the…