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| Title | Authentication Framework For Healthcare Devices Through Internet Of Things And Machine Learning |
|---|---|
| ID_Doc | 11129 |
| Authors | Kute S.; Shreyas Madhav A.V.; Tyagi A.K.; Deshmukh A. |
| Year | 2022 |
| Published | Lecture Notes on Data Engineering and Communications Technologies, 116 |
| DOI | http://dx.doi.org/10.1007/978-981-16-9605-3_27 |
| Abstract | The rise in the application and use of IoT has made tech gadgets and gizmos smarter and interconnected than ever before. IoT has expanded in a number of fields including smart cities and homes, healthcare, finance, etc. A typical IoT device is likely to integrate computation, networking, and physical processes from embedded computational gadgets. To monitor and extract valuable existential patterns from the large volume of data that is generated, Machine Learning (ML) helps a lot by the different number of algorithms that can be developed. Typically, ML is a discipline that covers the two major fields of constructing intelligent computer systems and governing these systems. ML has progressed dramatically over the past two decades and has emerged as one of the major methods for developing computer vision systems and other pedagogies. Rapid advancements and enhancements in these fields are leading to extensive interactions among the devices in the heterogeneous pool of gadgets. However, with advancements, there always will be a few bottlenecks that hinder the security and safety of the device or the gadget. Making use of such methodologies and techniques for user access control exposes this to endless vulnerabilities including numerous attacks and other complications. It is extremely important to protect the authenticity and privacy of the users and the data that is stored in these smart devices. This paper discusses the variety of ways in which a smart device can validate the user with proper authentication and verification. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. |
| Author Keywords | Biometric authentication; Cloud computing; Internet of Things; Secure machine learning |
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