AI-Powered Security Operations Centers (SOC) in the Cloud: Automating Threat Detection and Response
DOI:
https://doi.org/10.63282/3050-9246.IJETCSIT-V2I2P102Keywords:
AI-driven SOC, security operations center, cybersecurity, threat detection, incident response, machine learning, automation, threat intelligence, behavioral analyticsAbstract
AI-powered Security Operations Centers (SOCs) represent a significant evolution in cybersecurity, leveraging artificial intelligence and machine learning to automate and enhance threat detection and response. An AI-driven SOC utilizes machine learning, data analytics, and automation to help security teams detect and mitigate risks faster than before, learning from past threats and predicting new ones. These advanced SOCs enhance an organization's ability to handle threats efficiently by quickly analyzing large datasets, identifying patterns, and recognizing anomalies that may indicate a cyber-threat, thus minimizing the impact of cyberattacks. By integrating AI-driven automation, SOCs can navigate and mitigate the evolving challenges posed by automated threats in contemporary cybersecurity. AI-powered SOCs offer numerous benefits, including faster threat detection and response, reduced human error, cost efficiency, and proactive threat hunting. AI algorithms can analyze vast amounts of security data in seconds, distinguish between false positives and real cyber threats, and automate responses to contain threats more quickly. Moreover, AI systems provide continuous 24/7 monitoring, ensuring threats are detected at any time. The future of AI in SOC operations includes autonomous systems that continuously learn from incidents, real-time threat intelligence, advanced behavioral analytics, and cross-platform security integration, leading to more efficient and effective security operations
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References
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