Enhancing Cybersecurity With Artificial Immune Systems and General Intelligence: A New Frontier in Threat Detection and Response

This study explores how integrating Artificial General Intelligence (AGI) with Artificial Immune Systems (AIS) could potentialy enhance the efficiency of Security Operations Centers (SOCs). By employing a hypothetical case study and mathematical models, this research compares AGI-driven AIS with traditional AI-driven AIS across key SOC metrics such as True Positives, Benign Positives, False Positives, and False Negatives. Our analysis reveals that AGI-driven AIS solution offers notable improvements in detection accuracy and operational efficiency while reducing costs. These findings highlight the transformative potential of AGI in bolstering cybersecurity defenses. This research emphasizes the importance of AGI for SOCs, presenting it as a critical advancement over current AI technologies. This is particularly relevant for government regulators, original equipment manufacturers (OEMs), cybersecurity professionals, and investors. This study attempts to provide a compelling evidence that AGI can drive more effective and efficient SOC operations, encouraging stakeholders to consider investing in and adopting these advanced AI technologies. In a landscape where cybersecurity threats are becoming increasingly sophisticated, the integration of AGI with AIS to build security threat detection and response, represents a promising frontier. This research underscores the potential of AGI to not only enhance detection and response capabilities but to also streamline operations and optimize resource allocation within SOCs. The findings in this study, we argue, suggest that AGI could play a pivotal role in the future of cybersecurity, making it an essential consideration for those looking to stay ahead in the ongoing battle against cyber threats.