Data Ethics and Privacy in the Age of the Internet of Things: Risks and Responsibilities of Social Trust

سال انتشار: 1404
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 12

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شناسه ملی سند علمی:

JR_IJETH-7-4_002

تاریخ نمایه سازی: 15 دی 1404

چکیده مقاله:

Introduction: The rapid expansion of the Internet of Things (IoT) as one of the most transformative technologies of the digital age has led to the production and processing of vast volumes of personal and contextual data. While this transformation offers significant opportunities to improve quality of life, it also generates profound ethical challenges, particularly in the areas of privacy and data management. The invisible, automated, and pervasive nature of data collection within the IoT ecosystem calls into question traditional concepts of informed consent, individual control over data, and ethical accountability, and intensifies risks such as pervasive surveillance, data misuse, information insecurity, and the erosion of individual autonomy. Material and Methods: This article adopts a review–analytical approach to examine the scientific literature related to data ethics and privacy in the Internet of Things. Based on existing studies, it explores the foundational aspects of the topic and ultimately draws conclusions from the information reviewed. Conclusion: The study demonstrates that privacy in this context requires a contextual and relational redefinition. The findings indicate that ethical responsibility within the IoT data cycle is distributed in nature, and that multiple actors-from designers and companies to governments-play a fundamental role in upholding principles of data ethics. Ultimately, it can be argued that adherence to data ethics and privacy principles is a prerequisite for the formation of social trust and the sustainable acceptance of the Internet of Things. Without simultaneous attention to technical, ethical, and social dimensions, the development of this technology will face serious challenges.

نویسندگان

Charith Perera

School of Computer Science and Informatics, Cardiff University, UK

Rajiv Ranjan

School of Computing, Newcastle University, Newcastle, UK

Lizhe Wang

School of Computer Science, University of Geoscience, China

Samee U. Khan

Department of Electrical and Computer Engineering, Mississippi State University Starkville, USA

Albert Y. Zomaya

Centre for Distributed and High Performance Computing, School of Computer Science, University of Sydney, Australia

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