DomainDynamics: Lifecycle-Aware Risk Timeline Construction for Domain Names

TL;DR

DomainDynamics is a lifecycle-aware system that constructs risk timelines for domain names, significantly improving detection accuracy of malicious domains by considering their temporal evolution.

Contribution

It introduces a novel lifecycle-based approach to domain risk assessment, addressing limitations of static models and enhancing detection performance.

Findings

Achieved 82.58% detection rate on malicious domains.

Low false positive rate of 0.41%.

Outperformed previous methods and commercial services.

Abstract

The persistent threat posed by malicious domain names in cyber-attacks underscores the urgent need for effective detection mechanisms. Traditional machine learning methods, while capable of identifying such domains, often suffer from high false positive and false negative rates due to their extensive reliance on historical data. Conventional approaches often overlook the dynamic nature of domain names, the purposes and ownership of which may evolve, potentially rendering risk assessments outdated or irrelevant. To address these shortcomings, we introduce DomainDynamics, a novel system designed to predict domain name risks by considering their lifecycle stages. DomainDynamics constructs a timeline for each domain, evaluating the characteristics of each domain at various points in time to make informed, temporal risk determinations. In an evaluation experiment involving over 85,000 actual malicious domains from malware and phishing incidents, DomainDynamics demonstrated a significant improvement in detection rates, achieving an 82.58\% detection rate with a low false positive rate of 0.41\%. This performance surpasses that of previous studies and commercial services, improving detection capability substantially.