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Discovering Suspicious APT Behaviors by Analyzing DNS Activities.

Guanghua Yan¹, Qiang Li¹, Dong Guo²

¹College of Computer Science and Technology, Jilin University, Changchun 130012, China.

Sensors (Basel, Switzerland)

|February 5, 2020

Summary

This study introduces a novel deep learning method to detect Advanced Persistent Threat (APT) attacks by analyzing the relationship between DNS requests and responses. The new system effectively identifies suspicious DNS behavior with high accuracy, improving network security.

Keywords:

APT attack DNS behavior detection deep learning sensor network

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Area of Science:

Cybersecurity
Network Security
Machine Learning

Background:

Sensor networks are increasingly targeted in Advanced Persistent Threat (APT) attacks due to their vulnerability.
Existing detection methods struggle with the unique characteristics of APT attacks, such as low traffic and evolving attack vectors.
Analysis of Domain Name System (DNS) requests is a promising avenue for identifying suspicious network behavior during APTs.

Purpose of the Study:

To develop a novel method for detecting APT attacks by analyzing DNS request records.
To address the limitations of existing methods that overlook the relationship between DNS requests and responses.
To enhance the comprehensive detection capabilities for sophisticated cyber threats targeting sensor networks.

Main Methods:

A deep learning approach was employed to analyze DNS request records.
A new feature representing the relationship between DNS requests and response messages was engineered.
The system was trained and validated using a large dataset of DNS records from a campus network and simulated attack data.

Main Results:

The proposed method achieved an average accuracy of 97.6% in detecting suspicious DNS behavior.
The system demonstrated a low false positive rate of 2.3% and a recall of 96.8%.
Experimental results validated the system's effectiveness in identifying hidden and suspicious DNS activities.

Conclusions:

The developed deep learning model significantly improves the detection of APT attacks through enhanced DNS log analysis.
Considering the request-response relationship in DNS data is crucial for comprehensive threat detection.
The system offers a robust solution for bolstering network security against advanced persistent threats.