Generative AI is Reshaping Cybersecurity. Is Your Organization Prepared?

Integrating generative AI into cybersecurity can give your organization the power to strengthen its defenses, quickly detect attacks, and expedite remediation processes. It also gives threat actors a potent new tool to create complex and damaging attacks against your organization.

Though AI frequently dominates headlines, its presence in security operations is not new. Many of your solutions likely already incorporate AI capabilities. However, generative AI broadens accessibility to these security capabilities, requiring less technological knowledge and expertise to operate. This expanded access promises new security gains for your organization and invites a surge in your cyberthreats. To stay secure, your organization must proactively prepare for these changes.

Here are three key ways generative AI technology can revolutionize your cybersecurity tools and security operations teams to swiftly, efficiently, and effectively combat cyberthreats.

The impact of generative AI on your security operations 

Generative AI can empower your security solutions with natural language processing (NLP). NLP facilitates streamlined workflows, accelerates threat detection, and enhances how your security operations teams prioritize responses. 

Instead of sifting through results or analyzing complicated dashboards, NLP enables your teams to converse with security solutions. They can ask questions about specific events or analyses and promptly act on the responses. As NLP advances, your analysts will soon interact with generative AI-driven cybersecurity programs using plain language, eliminating the need for complex technical code. This evolution will drive productivity gains in your security operations center and reduce your analyst onboarding time. These gains will also foster broader access to critical information and elevate overall security awareness among your staff. 

Generative AI augments automation capabilities within your security operations, offering recommendations, surfacing insights, and autonomously executing your workflows and responses. This automation optimizes your resource allocation so your teams can focus on strategic work to improve organizational security. 

Predictive analytics can further enhance your security operations. These capabilities can shed light on your log source connections, identify your most common attack vectors, proactively hunt threats, and anticipate vulnerabilities before they materialize. These enhancements will make it easier for your teams to adopt a more proactive approach to security. 

The impact of generative AI on your organizational operations

Your security operations teams must understand how to use AI to shield the organization from external threats. You must also recognize the impact of generative AI-powered solutions on your organization’s operations.

The challenge lies in the inherent opacity of generative AI applications. Security teams aren’t always able to validate their functionality and rationale. These applications operate on complex, non-linear architectures and are trained on massive data sets, making them susceptible to producing misleading outputs, known as hallucinations. If your teams use generative AI for tasks like application coding, they could introduce the risk of hallucination-induced vulnerabilities, potentially exposing your organization to attacks. If your AI models continuously train on low-quality, AI-generated data, it increases the likelihood of model collapse and poses the threat of cascading failures within your operations. 

Generative AI also escalates the risk of mishandling sensitive or proprietary data, potentially leading to non-compliance issues and significant liability. Protecting the integrity of your data is critical to fortifying your operations against such liabilities and ensuring continued security.

The impact of generative AI on your cyberthreats

The good news is that your security operations team can use generative AI to improve operations and combat cyberattacks. The bad news is that your team is about to have its hands full defending against AI-augmented attacks. 

Your organization must brace for a spike in both attack volume and complexity. Threat actors will be able to automatically adapt and evolve to evade your detection mechanisms. 

While your AI-powered cybersecurity solutions will become more elaborate, your organizational human users remain vulnerable, serving as a weak link in security defenses. People who are already susceptible to phishing and social engineering attacks will struggle to fend off increasingly detailed and precisely targeted attacks. 

These attacks will make it harder for your users to differentiate between legitimate and malicious communications. For example, deepfakes have the potential to convincingly impersonate your executives or key customers during phone calls. This presents a significant risk to your employees with trusted access credentials or financial account controls. 

The Exabeam approach to AI-driven security operations

At Exabeam, we collaborate closely with our customers to address the impacts of generative AI on security operations. Our products have been rooted in AI and machine learning (ML) since day one. They are built from the ground up to make the most of Google Cloud’s flexible and resilient architecture, plus VertexAI. 

As pioneers in AI-driven security information and event management (SIEM), we have been at the forefront of applying AI to address cybersecurity challenges. For over a decade, we have employed ML and pattern matching to power user and entity behavior analytics (UEBA). These advanced capabilities excel in identifying anomalies and sudden deviations in log or event streams. They also excel in automating threat detection, investigation, and response (TDIR) workflows. 

In addition to our decade-long commitment to AI development, we are executing a robust solution roadmap. Starting with new NLP and GPT releases in early 2024, this roadmap aims to empower our customers with advanced AI and NLP capabilities across our platform. Our roadmap includes:

• NLP integration: We continue to embed NLP into our products to streamline the TDIR workflow and improve your user experience in searches, dashboards, and detection. Your analysts and engineers can use NLP to create complex search queries and deliver actionable cases based on risk.
• Data tagging and parsing: Through AI-driven processes, we tag and classify data from Log Stream to automatically generate regex phrases and summaries to efficiently parse data. This removes the need for your users to write complex search queries, simplifying data analysis and retrieval. 
• Exabeam Copilot: The generative AI experience of the Exabeam Security Operations Platform, Exabeam Copilot, gives your security teams powerful productivity and actionable insights. Your teams can operate more efficiently and become more informed about cybersecurity. 

Together, Exabeam and Google Cloud have created a cloud-native, AI-powered portfolio of security solutions, offering customers cloud-scale storage and robust TDIR capabilities. To learn more, read the solution brief or request a demo.

What Comes Next for Your AI Cybersecurity Strategy?

Exabeam and Google Cloud can help you answer these questions and build an AI-driven SOC function for your organization. Built on Google Cloud’s technology, Exabeam provides the industry’s most complete, AI-driven security operations platform for TDIR in security log management, behavioral analytics, and automation.

Download the brief now.