Transforming Cybersecurity: The Rising Role of Generative AI and Large Language Models

These technologies are making phishing attacks more sophisticated and harder to detect, necessitating the implementation of new security measures.

GenAI, in combination with adversarial networks, is predicted to lead to more realistic and sophisticated cyber scams. Eric Skinner, VP of market strategy at Trend Micro, has particularly emphasized the evolution of phishing tactics due to advanced LLMs. He notes that these technologies can generate highly convincing phishing emails that can easily bypass traditional security measures.

In response, the cybersecurity industry may start self-regulating AI technology, potentially outpacing government efforts in policy development. This proactive approach could lead to more effective and timely countermeasures to emerging threats.

Without proper governance and supervision, a company's use of GenAI can create or exacerbate numerous risks. To mitigate these risks, companies must understand the problem they are trying to solve using GenAI. They must also establish proper governance to ensure that the technology is used appropriately and effectively.

Generative AI (GenAI) is a double-edged sword when it comes to cybersecurity. On one hand, it's a powerful tool for automating responses, predicting, and countering threats. It can automate defense responses, enabling organizations to respond swiftly and effectively to cyberattacks and enhance the capabilities of security orchestration automation and response (SOAR)-based solutions. It can also be used to train less-skilled security practitioners to expedite the decision-making process by being able to analyze future threats more quickly and accurately.

On the other hand, GenAI also poses significant challenges. It requires substantial training and cultural change to ensure confidential data is not compromised. The security data model training infrastructure requires a significant investment and strong business support. Without sufficient data and the necessary resources, AI systems can produce incorrect monitoring results and false positives, which can have consequences for organizations.

Sources:

[1]https://www.vectra.ai/blog/2024-predictions-generative-ais-role-in-cybersecurity

[2] https://www.crowdstrike.com/cybersecurity-101/secops/generative-ai/