Open AccessEstimation and Prediction of the Presence of Hackers in the IoT based on the Kalman Filter
Author(s) -
Ghadeer Safaa Majeed,
Muayed Hanoon Salman
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1530/1/012044
Subject(s) - hacker , computer science , internet of things , the internet , computer security , kalman filter , control (management) , filter (signal processing) , network security , computer network , world wide web , artificial intelligence , computer vision
In general, the concept of the Internet of Things is to connect different devices to each other over the Internet. With the help of IoT, different applications and devices can interact and talk to each other, even with the humans, via the Internet. Examples include smart refrigerators that connect to the Internet and inform you of the expiration date of foods in the refrigerator. In fact, IoT enables you to remotely manage and control your used objects with the help of Internet infrastructure. However, an important criterion in such networks is security of the information in it. Because if the customers sense that their data will manipulate or hear with a hostile user they will not trust to such network. In this paper, we wants to present new method to intensify the security of the IoT network with use of Kalman Filtering. The Kalman filter has been used as an algorithm to estimate and predict the presence of the hackers and crackers in the network. It is demonstrated that if we equipped our network with such a smart algorithm not only the security of our network will increase but also more users will trust in our network and migrate to it.