Speakers
Synopsis
In the rapidly evolving landscape of cyber threats, Australia faces an urgent need for innovative approaches that empower security operations to stay ahead of malicious actors. Traditional reactive methods of threat detection, which focus on shutting down threats after malware appears, are no longer sufficient. To address this challenge, our presentation introduces a new paradigm of early threat detection, aimed at exposing threat actor infrastructure, toolkits, and suspicious behaviours before cybercriminals can activate the malware they disseminate.
The Need for Proactive Threat Detection
The speed at which cyber threats evolve necessitates a shift from reactive to proactive threat detection and remediation, especially in the realm of DNS-based attacks, which are among the most prevalent and insidious. Most security measures respond only after malware or other threats emerge, leaving organisations vulnerable to sophisticated attacks. Certain DNS-based approaches, such as a Protective Domain Name System (PDNS) and Australia’s implementation, AUPDNS, play vital roles in identifying DNS-based threats, but even these innovations can respond only to known threats. This discussion will articulate the benefits of detecting and anticipating threat activity before attacks are initiated, disrupting cybercriminal operations at their inception.
Moving Beyond Malware-Centric Detection
Our presentation advocates for a proactive approach that leverages advanced DNS analysis augmented with algorithms, artificial intelligence (AI), and machine learning to detect anomalies and early indicators of compromise before malware and other threats can become active in networks.
We will discuss the critical components of early threat detection, including:
Advanced DNS analysis capabilities that go beyond traditional query inspection to identify subtle anomalies.
Early detection of Indicators of Compromise (IoCs) through sophisticated data analysis techniques.
The importance of two-way data integration between DNS threat analysis platforms and Extended Detection and Response (XDR) ecosystems for shared visibility and seamless threat mitigation.
Case studies and examples
Our presentation will feature real-world examples demonstrating the effectiveness of advanced DNS analysis in exposing threat actor activity originating in Eastern Europe, Mainland China and elsewhere. We will illustrate how proactive detection methods have successfully identified malicious infrastructure that evaded traditional detection mechanisms for extended periods.
Our discussion will conclude by emphasising the unique capabilities that proactive threat detection, powered by advanced DNS analysis, AI, and machine learning, brings to the fight against evolving cyber threats. By integrating proactive detection strategies into cybersecurity frameworks, organisations can disrupt threat actor operations before they inflict damage, strengthening Australia's cybersecurity resilience.
