How AI is Transforming Cybersecurity: A Look at Key Use Cases

Artificial intelligence (AI) is on the brink of transforming cybersecurity as we know it. Recent research from Insight Partners indicates that security operations, along with application security, is a top priority for chief information security officers (CISOs) eager to leverage generative AI for improved results. This emphasis on AI isn’t surprising, considering the technology’s strengths in tackling complex challenges that have long plagued the field, such as:

• Anomaly and Threat Detection: Amidst increasing data volumes, security teams must sift through extensive information to pinpoint potential threats that warrant further investigation.
• Reducing Toil: The labor-intensive nature of manual tasks in security operations can diminish work quality and undermine team morale.
• Addressing Talent Shortages: The cybersecurity industry grapples with a scarcity of skilled professionals, making tools that enable junior staff to tackle complex assignments invaluable.

Five Game-Changing Use Cases for AI in Security Operations

Although we’re still in the infancy of integrating AI within the cybersecurity landscape, it has already demonstrated significant value in security operations. Here are five important use cases that spotlight the practical applications of AI in this domain:

1. Instant Summarization

Time is precious for security teams, especially when responding to alerts or incidents. AI can revolutionize this process by generating concise summaries of security incidents, allowing analysts to grasp the situation quickly. Team members can also request on-demand summaries of threat intelligence reports or incident response actions, speeding up triage processes significantly. For example, if a search returns thousands of results, AI can efficiently summarize them, providing clarity amid the chaos.

2. Streamlined Investigations

Investigations can be painstaking and time-consuming since they often require complex search queries. AI changes the game by enabling natural language searches. Analysts can simply ask questions like, “Show me all users from ‘X’ region who visited ‘XYZ’ site last week outside working hours,” which simplifies the investigation process. More sophisticated AI can even suggest next steps or present useful additional context, making junior analysts much more effective.

3. Proactive Threat Hunting

Historically, threat hunting has been the domain of highly skilled security teams. However, AI can democratize this function, enabling proactive searches for threats by identifying patterns that suggest malicious activity. For example, AI can work alongside threat intelligence tools to locate indicators of compromise (IOCs) associated with specific malware, simplifying queries like, “Hunt for Makop ransomware on my network.”

4. Detection and Response Automation

Creating detection rules and playbooks has traditionally required expert knowledge. With generative AI, the creation of these rules is made more accessible. Analysts can prompt AI with requests such as “Build a detection rule for this case,” allowing the AI to draft tailored responses based on the unique context of the situation. While the output may not be perfect, achieving 70% to 80% of the goal can significantly enhance productivity.

5. Accelerated Malware Analysis

Reverse engineering malware has previously been a task for a select few top-tier defenders. Thanks to advancements in AI technology, particularly with large language models, malware analysis can now be performed at lightning speed. In fact, some advanced AI models can reverse engineer sophisticated malware in under a minute, providing critical insights into its functionalities and, in certain cases, indicative routes for neutralization.

Cultivating an AI-Driven Culture

The effective use of AI in security operations isn’t just about deploying new technologies; it’s also about nurturing an AI-focused culture within teams. Here are some actionable steps to foster this:

• Educate and Train: Equip your team with the necessary knowledge to use AI tools effectively.
• Encourage Exploration: Create a space for team members to experiment with AI applications without fear of failure.
• Showcase Successes: Present real-world examples that illustrate how AI can continuously enhance cybersecurity efforts and make jobs easier.

As AI technology evolves, it promises to enhance efficiency, accuracy, and proactive measures in combating cyber threats. As the saying goes, the best time to start integrating AI was yesterday, but the second-best time is now.

Chris Corde, with over two decades of experience in cybersecurity, serves as director of product management at Google, overseeing the Security Operations PM team, including Chronicle, Siemplify, VirusTotal, and Mandiant.

The AI Buzz Hub team is excited to see where these breakthroughs take us. Want to stay in the loop on all things AI? Subscribe to our newsletter or share this article with your fellow enthusiasts.