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image of Data Security and Privacy Preservation in Cloud-Based IoT Technologies: an Analysis of Risks and the Creation of Robust Countermeasures

Abstract

The Internet of Things (IoT) is a revolutionary technology being used in many different industries to improve productivity, automation, and comfort of the user in the cloud and distributed computing settings. Cloud computing is essential because it makes data management and storage more effective by automatically storing and examining the enormous amounts of data generated by Internet of Things applications. End users, companies, and government data are consequently migrating to the cloud at an increasing rate. A survey of the literature, however, reveals a variety of issues, including data integrity, confidentiality, authentication, and threat identification, that must be resolved to improve data security and privacy. To effectively address contemporary data security concerns, the existing approaches need to be improved. Ensuring secure end-to-end data transmission in a cloud-IoT situation requires innovative and dependable protocol architecture. New technologies that address some of the issues related to cloud data include edge computing, fog, blockchain, and machine learning. This paper provides a thorough examination of security risks, classifying them and suggesting possible defenses to safeguard cloud-IoT data. It also highlights innovative approaches, such as blockchain technology and machine learning, applied to privacy and data security. The paper also explores existing issues with respect to data privacy and security in today's cloud-IoT environments. It suggests possible future directions, including the need for end-user authentication, enhanced security, and procedures for recovering data in the event of an attack.

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2024-10-16
2024-11-22

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/content/journals/rascs/10.2174/0126662558319054241003054922
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Data Security and Privacy Preservation in Cloud-Based IoT Technologies: an Analysis of Risks and the Creation of Robust Countermeasures
Bentham Science Publishers ; https://doi.org/10.2174/0126662558319054241003054922
/content/journals/rascs/10.2174/0126662558319054241003054922
/content/journals/rascs/10.2174/0126662558319054241003054922
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  • Article Type:     Review Article
Keywords: Big Data ; Privacy Protection ; Machine Learning ; Cloud-IoT Computing ; Data Securities

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