Analysis and prevention of IoT vulnerabilities by implementing a lightweight AD-IoT intrusion detection system model
Laberanio Andrade-Arenas, Jhoel Anthony Ramos-Romero · 2020 IEEE Congreso Bienal de Argentina (ARGENCON) · 2020
Until a few years, the Internet of Things (IoT) has been continually evolving and today it is giving a great welcome to a paradigmatic style of technology, for this reason new electronic devices are being invented that are used continuously by many people. But these devices must be protected in a certain way since there are many attacks on the IoT web, with which, by integrating new algorithms, certain network security will be obtained. In addition, the use of new model systems; such as the IoT Anomaly Detection System (AD-IoT) that uses the Random Forest (RF) machine learning algorithm to detect web attacks; It will help us reduce attacks from bad IoT computer users. In this present article, a very effective evaluative metric was obtained through a group of data that will help us develop and modify the communication security paradigms of IoT devices.