Covert Channel Detection Using Machine Learning

Date

2021-01-07

Author

Çavuşoğlu, İmge Gamze
Alemdar, Hande
Onur, Ertan

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

43
views

0
downloads

Cite This

A covert channel is a communication method that misuses legitimate resources to bypass intrusion detection systems. They can be used to do illegal work like leaking classified (or sensitive) data or sending commands to malware bots. Network timing channels are a type of these channels that use inter-arrival times between network packets to encode the data to be sent. In this study, we worked with two types of network covert channels: Fixed Interval and Jitterbug. We were able to distinguish these channels from legitimate ones by using decision trees that use four statistical features (mean, variance, skewness, and kurtosis).

Subject Keywords

Covert Channel, Covert Channel Detection, Machine Learning, Decision Tree

URI

https://hdl.handle.net/11511/88454

Collections

Department of Computer Engineering, Conference / Seminar