The dual role of AI in cybersecurity - part 1: AI for defenders

By Lili Marleen Moser | 997 words | Read time: 5 minutes

For decades, cybersecurity has been a constant tug-of-war between attackers exploiting vulnerabilities and defenders striving to patch them. Now, with Artificial Intelligence (AI), both sides have been introduced to a new weapon.

In this two-part blogpost, we will explore how AI can be leveraged by both cyber defenders to build more robust protections, and by malicious actors to orchestrate more sophisticated attacks. In this first part, we briefly cover the history of AI, leading into a discussion on how it empowers cyber defenses. 

From von Neumann to ChatGPT: A brief history of AI

The dream of creating artificial intelligence is centuries old, with early concepts appearing in myths, legends, and philosophical discussions. The formal journey of AI began in the mid-20th century, where pioneers like Alan Turing, with his groundbreaking Turing Test, and early programs like the Logic Theorist, developed by Newell and Simon, demonstrated the potential of machines to mimic human intelligence. 

Early AI research focused on symbolic AI, where systems were programmed with explicit rules and knowledge. This led to breakthroughs like chess-playing computers that could defeat human champions, showcasing the potential of AI to tackle complex tasks.

However, symbolic AI had limitations. It struggled with tasks that required intuition, learning, and adaptation. This led to the exploration of other approaches, such as machine learning, where systems learn from data rather than explicit programming.

The rise of machine learning, fueled by advances in computing power and the availability of massive datasets, has led to significant progress in AI. Today, we have AI systems that can recognize images, translate languages, generate text, and drive cars.

AI is becoming increasingly integrated into our everyday lives. We interact with AI-powered systems like ChatGPT and Gemini, virtual assistants, and recommendation engines on a daily basis. And in the realm of cybersecurity, AI is playing an increasingly critical role in defending against threats and enhancing security operations.

AI for the defenders

One of the most significant uses of AI on the defensive front is in threat detection and prevention. Machine learning algorithms (algorithms that identify patterns and make predictions based on vast amounts of data), can help detect new threats quickly by analyzing network traffic, system logs, and user behaviour to establish baselines of “normal” activity.

By continuously learning and adapting to these patterns, AI can identify subtle anomalies and deviations that might indicate a malicious intrusion or insider threat, even if the attack doesn’t match known signatures. 

Another area on the defensive side that leverages AI is incident response. While traditional incident response relies on human expertise and manual tasks, AI-powered incident response transforms cybersecurity automation, as it efficiently processes and analyzes security data, quickly performs incident triage to assess the impact of the detected anomalies or incidents, and automates and orchestrates response actions[1]. 

Also, by automating repetitive and time-consuming tasks, AI frees up human security analysts to focus on the more complex aspects of incident analysis and remediation, which can significantly reduce response times and minimize the potential damages of an attack. 

Artificial intelligence can also be applied to vulnerability management. Again, the fact that machine learning algorithms can identify patterns and make predictions based on huge amounts of data, offers several benefits, such as discovering and mitigating vulnerabilities in real-time[2]. Algorithms can also analyze data in order to prioritize the identified weaknesses/vulnerabilities based on their severity and exploitability. 

Lastly, artificial intelligence is significantly enhancing threat intelligence gathering and analysis. Similarly to incident response, threat intelligence gathering and analysis require manual efforts, which can be time-consuming. AI can automate processes related to data collection (e.g., via web scraping or natural language processing), and analyze the information to identify threats by using algorithms that spot patterns, anomalies and correlations within the data[3]. 

Trifork Security: Embracing AI-driven platforms

At Trifork Security, we recognize the transformative potential of AI in bolstering cybersecurity defenses and strategically use the power AI to empower our customers.

We partner with industry-leading platforms like Splunk and CrowdStrike, who are at the forefront of AI innovation in cybersecurity. These platforms offer sophisticated AI functionalities that we utilize to deliver tangible security improvements:

Enhanced threat detection: Utilizing Splunk Enterprise Security and CrowdStrike’s Falcon Prevent and Insight, we help organizations harness machine learning to identify subtle anomalies and sophisticated attack patterns that traditional rule-based systems might miss. This allows for earlier detection and faster response to potential breaches.
Proactive threat hunting and incident response: By leveraging the AI capabilities within Splunk UBA and CrowdStrike’s Falcon Insight and OverWatch, we assist security teams in proactively hunting for hidden threats and automating crucial aspects of incident triage and response. This reduces manual effort and accelerates the containment of security incidents.
Intelligent vulnerability management: The pattern recognition capabilities of machine learning, inherent in the platforms we utilize, enable us to help clients prioritize and address vulnerabilities based on real-world risk, optimizing patching efforts and strengthening their overall security posture.

Our expertise lies in translating the power of these AI-driven platforms into practical security outcomes for our clients. Our certified Splunk and CrowdStrike experts work closely with organizations to:

Strategically implement and configure AI-powered security tools to align with their specific security objectives and infrastructure.
Develop and fine-tune AI models within these platforms to address unique threat landscapes and security requirements.
Seamlessly integrate AI capabilities into their existing security workflows, maximizing efficiency and effectiveness.
Provide ongoing guidance and support to ensure they stay ahead of the evolving threat landscape and the latest advancements in AI for cybersecurity.

The integration of artificial intelligence is no longer a futuristic concept but a fundamental shift in how we approach cybersecurity. By strategically leveraging AI-driven platforms and our deep expertise, Trifork Security is dedicated to equipping organizations with the intelligent defenses necessary to navigate the complexities of modern cyber threats and build a more resilient security posture.

Contact us to learn more about how we can help you build a resilient and AI-powered cybersecurity foundation.

[1] https://radiantsecurity.ai/learn/ai-incident-response/
[2] https://www.linkedin.com/pulse/autonomous-vulnerability-management-role-agentic-ai-proactive-mitra-q4v7c/
[3] https://cyble.com/knowledge-hub/ai-in-cybersecurity-cyble-vision-role-in-modern-threat-intelligence/