Perspectives On Solving Cybersecurity Using AI Techniques

The increasing sophistication and frequency of cyberattacks, including incidents like those experienced by CrowdStrike, have propelled the need for innovative defenses in cybersecurity. These breaches, often resulting in substantial data loss and financial damage, pose significant risks to organizations globally, highlighting the urgent demand for advanced technological solutions. Artificial Intelligence (AI) and Large Language Models (LLMs) can play a critical role in transforming cybersecurity protocols by automating threat detection, improving incident response times, and analyzing vast datasets for anomaly identification. As traditional security measures often fail to keep pace with evolving threats, these technologies provide a means to stay ahead of cybercriminals who increasingly leverage AI for malicious purposes. Despite their potential, the integration of AI and LLMs into cybersecurity frameworks raises several challenges, including the need for continuous adaptation to new threats and the ethical implications associated with data handling and privacy concerns. This study provides an in-depth review of the different use cases using AI techniques and a way to modify those techniques to fit the purposes of different organizations.