| Title |
Monitored Access Distribution Method for Finding the Abnormality in the Internet of Things Based Smart City Application |
| ID_Doc |
37177 |
| Authors |
Vijayakumar, M; Angel, TSS |
| Title |
Monitored Access Distribution Method for Finding the Abnormality in the Internet of Things Based Smart City Application |
| Year |
2022 |
| Published |
|
| DOI |
10.1016/j.matpr.2022.03.661 |
| Abstract |
The support of the Internet of Things (IoT) in smart city applications improves the scalability of services regardless of the users' varying densities. The densely populated users demand heterogeneous security measures for reliable and robust application services. Here, the Permanent Denial of Service (PDoS) problem arises from improper user identification. In this authentication method, the application security is ensured by using monitored access distribution. The monitored access distribution exploits the user application's communication features and its synchronization with the user device. The abnormality in linking user device, application, and authentication is observed in BackPropagation (BP) learning. BP learning reduces the assigned weights based on the abnormality that is trained during the access distribution process. The proposed authentication method's performance is verified using the metrics authentication delay, false rate, synchronization failures, and hit rate.Copyright (c) 2022 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the International Conference on Innovative Technology for Sustainable Development. |
| Author Keywords |
Permanent denial of service; BackPropagation learning; IoT smart city application |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000828164500017 |
| WoS Category |
Materials Science, Multidisciplinary |
| Research Area |
Materials Science |
| PDF |
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