along withcyber securityThreats are increasing day by day, and businesses areThreat intelligenceThe demand is also growing. However, according to ESG's latest survey, 98% companies plan to increase threat intelligence spending in 2024, but they also face a series of challenges. These challenges include that threat intelligence is too "academic" and difficult to understand and apply; the amount of threat intelligence data is large and it is difficult to filter out valuable information; there is a lack of sufficient professional talents to process threat intelligence, etc. However, withgenerative artificial intelligenceWith the development of (Generative AI), these pain points may be alleviated.

The top five pain points of threat intelligence

According to ESG research, the top five pain points enterprises face when it comes to threat intelligence include:

Threat intelligence reporting is too technical:Cybersecurity professionals at 33% said threat intelligence reports contain too many technical details, making them difficult for non-professionals to understand.
The amount of threat intelligence data is too large:Cybersecurity professionals at 28% said that threat intelligence data is large and complex, making it difficult to find truly valuable information.
Threat intelligence processing consumes resources:Cybersecurity professionals at 27% said that identifying and processing threat intelligence takes up a lot of resources and energy, hindering the implementation of security strategies.
Lack of professional talents:Cybersecurity professionals at 25% said they have few professionals with threat intelligence skills.
Insufficient analysis of attackers:Cybersecurity professionals at 22% said their analysis of the attackers was insufficient.

Generative Artificial Intelligence Solutions

Generative AI may be an effective tool to solve the above pain points:

Simplify threat intelligence reporting:Generative AI can help threat intelligence teams create reports suitable for users with different technical and business backgrounds, making threat intelligence understandable to non-experts.
Filter valuable information: Generative AI can help threat intelligence teams determine the most relevant threat intelligence data to companies, industries, and regions, and reduce the noise of threat intelligence.
Optimize resource allocation:Generative AI can accelerate the discovery and remediation of threat intelligence, freeing up resources for higher-value security strategy implementation.
Training professionals:Although generative AI cannot replace professionals, it can serve as an effective training tool to help junior personnel improve their threat intelligence processing skills.
Enhance attacker analysis capabilities:Generative AI can help threat intelligence teams analyze attackers’ strategies and methods more deeply and improve defense capabilities.

Despite the potential of generative AI in threat intelligence processing, there are some issues that enterprises need to be aware of. First of all, generative AI does not replace threat analysts, but can only serve as an auxiliary tool for them. Second, businesses using generative AI need to ensure that the training data for their models is of high quality, otherwise it may result in false positives or false negatives. Finally, the misuse of generative AI may introduce new security threats, such as fake news generation or deepfakes.

in conclusion

Generative artificial intelligence offers new possibilities for processing enterprise threat intelligence. Although there are some potential challenges, if used correctly, generative AI can help enterprises understand, process and respond to security threats more effectively, ultimately improving the enterprise's cybersecurity defense capabilities.