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ویرایش:
نویسندگان: Fehmi Jaafar. Schallum Pierre
سری:
ISBN (شابک) : 9781032130989, 9781003227656
ناشر: CRC Press
سال نشر: 2023
تعداد صفحات: 196
زبان: English
فرمت فایل : PDF (درصورت درخواست کاربر به PDF، EPUB یا AZW3 تبدیل می شود)
حجم فایل: 9 Mb
در صورت تبدیل فایل کتاب Blockchain and Artificial Intelligence-Based Solution to Enhance the Privacy in Digital Identity and IoT به فرمت های PDF، EPUB، AZW3، MOBI و یا DJVU می توانید به پشتیبان اطلاع دهید تا فایل مورد نظر را تبدیل نمایند.
توجه داشته باشید کتاب راه حل مبتنی بر بلاک چین و هوش مصنوعی برای افزایش حریم خصوصی در هویت دیجیتال و اینترنت اشیا نسخه زبان اصلی می باشد و کتاب ترجمه شده به فارسی نمی باشد. وبسایت اینترنشنال لایبرری ارائه دهنده کتاب های زبان اصلی می باشد و هیچ گونه کتاب ترجمه شده یا نوشته شده به فارسی را ارائه نمی دهد.
Exploiting the data generated in the context of sensors, IoT and industrial environments remains a great challenge. It is estimated that today only 20% of industrial data has already been used. This amount of data needs to be valorized to be put at the service of research, citizens, and the advancement of the understanding of climate issues. This is why data plays a key role in digital transformation. It must be collected, stored, and processed. Because of their ability to deal with targeted and personalized information, IoT has become very present in our environment. Its place in our daily lives explains this scope: from the moment we wake up until late at night. For example, during the pandemic, different segments of the world’s population, especially the elderly, were confronted with sleep problems. Faced with this need, IoT technologies have been used in monitoring the quality of sleep, without the need for a person to go to the hospital to expose himself to risks of contagion. Various categories of personnel data are generated by IoT: health data, geolocation data, financial data, sociodemographic data, biometric data, etc. Several standards govern IoT that are the source of unstructured data such as movement, gesture recognition, and biometric measurement, proximity; infrared luminosity; sound, and; smell. These standards include IEEE 802.11. Two technologies are helping to leverage this data and accelerate digital transformation: Artificial Intelligence (AI) and blockchain. The chapters in this book explore the main domains that represent considerable risks for the respect of privacy, such as education, health, finance or social media. Through its place in the massive data production industry, the Internet of Things participates in the development of Artificial Intelligence and is increasingly attracting the attention of web giants, governments and especially all types of hackers. Thanks to this book, private and public organizations will have at their disposal a tool that highlights, on the one hand, the major challenges raised by privacy in the context of the Internet of Things and, on the other hand, recommendations for improving good practices. Digital identity is presented as a bulwark for the protection of privacy. It opens up new avenues for improving digital trust. Concretely, there are a set of challenges that are associated with the management of digital identity, mainly in relation to the compliance and governance of personnel data in order to eliminate privacy and security risks.
Cover Half Title Title Page Copyright Page Contents About the Authors List of Contributors Introduction SECTION I: Digital Identity Era Chapter 1: Demystifying the Digital Identity Challenges and the Blockchain Role Chapter 2: Blockchain for Digital Identity SECTION II: Privacy Dilemma Chapter 3: Security and Corporate Violation to Privacy in the Internet of Things Age Chapter 4: Security, Privacy, and Blockchain in Financial Technology SECTION III: Sensitive Data Challenges Chapter 5: Where Does the Novel Legal Framework for AI in Canada Stand against the Emerging Trend of Online Test Proctoring? Chapter 6: Blockchain, AI, and Data Protection in Healthcare: A Comparative Analysis of Two Blockchain Data Marketplaces in Relation to Fair Data Processing and the ‘Data Double-Spending’ Problem Chapter 7: Cyber Influence Stakes Postface Index