Machine learning - IoT 23

• Author(s) / Creator(s)

  • Bains, Jayant Singh
  • Goyal, Rahul
  • Kopanati, Hemanth Varma
  • Savaram, Bhargav Krishna

• IoT devices have become the future of many industries like household, security, etc. but these devices have a requirement that is that they should be connected to a network. This makes them vulnerable to outside attacks. If security is built into each device, it would cost more and would not reliable but if machine learning is used in the IDS and IPS to protect the system. This paper shows how machine learning can be used to detect malicious traffic in IoT datasets. The accuracy recorded ranges from 98.9%-100% depending on the dataset.

• Date created

  2021-06-01

• Subjects / Keywords

  • Internet of Things
  • IoT
  • intrusion detection systems
  • intrusion prevention system
  • decision tree
  • logistic regression
  • Artificial Neural Network

• Type of Item

  Research Material

• DOI

  https://doi.org/10.7939/r3-r5xn-yz96

• License

  Attribution-NonCommercial 4.0 International