| Pub. Date | : Aprill, 2022 |
|---|---|
| Product Name | : The IUP Journal of Computer Sciences |
| Product Type | : Article |
| Product Code | : IJCS020422 |
| Author Name | : Yusuf Alkali, Indira Routray and Pawan Whig |
| Availability | : YES |
| Subject/Domain | : Management |
| Download Format | : PDF Format |
| No. of Pages | : 10 |
The Internet of Things (IoT), one of the leading cutting-edge innovations, has become an economically attractive field of focus for the scientific community. It requires several system interconnections and device interactions with humans. In order to manage its data exchange and analysis, IoT needs a cloud computing environment; Artificial Intelligence (AI) is needed at the same time via the Internet and cloud-based network of networks. These interconnected IoT systems can interact and share information with each other using their respective identifiers and embedded sensors on each device. We live in the age of big data, and it has become very important to easily and reliably interpret the captured big data. However, while AI is currently playing a greater role in strengthening conventional safety, there are significant challenges to cloud security and IoT computer networking. There are many security concerns that cloud be a danger to the community. In comparison, several of the IoT systems installed on a public network that is wirelessly accessible are now under persistent cyber attack. The paper suggests a hybrid identification paradigm as a response strategy that utilizes Machine Learning (ML) and AI to mitigate and combat IoT cyberattacks both at the host and network levels in cloud computing environments.
The Internet of Things (IoT) is by far the next strongest technological gamble. The role of big data in IoT is to process a large amount of data on a real-time basis and storing them using different technologies. Roughly 127 new Internet-enabled devices are connected every second. The number of connected devices worldwide is projected to rise by "more than 25 billion by 2025, which is almost a threefold increase from 2017. The larger the deployment of IoT applications, the greater the tendency for growth in
Internet of Things (IoT), Cyberattacks, Machine Learning (ML), Convolutional Neural Network (CNN), Multilayer perceptron