Next-Gen SOC: Enhancing the efficiency of a SOC with Machine Learning and Automation

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Maroc Mohammed VI Polytechnic University Temps plein

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UM6P CEDOC- CC: Next-Gen SOC: Enhancing the efficiency of a SOC with Machine Learning and Automation

Mohammed VI Polytechnic University is an institution dedicated to research and innovation in Africa and aims to position itself among world-renowned universities in its fields

The University is engaged in economic and human development and puts research and innovation at the forefront of African development. A mechanism that enables it to consolidate Morocco's frontline position in these fields, in a unique partnership-based approach and boosting skills training relevant for the future of Africa.

Located in the municipality of Benguerir, in the very heart of the Green City, Mohammed VI Polytechnic University aspires to leave its mark nationally, continentally, and globally.

Security Operation Centers (SOC) have become a pillar in the defense of an organization. Indeed, they bring a first line of defense for detecting threats and taking immediate response. However, in the last decade, SOC analysts have become submerged with alerts as the volume of data manipulation is increasing. One way to solve this is by recruiting more SOC analysts. However, this is very difficult because of the lack of security experts in general and recruiting more analysts does not resolve all the problems. Recently, organizations have started to look for automation and Machine learning capabilities to increase efficiency. In fact, automation reduces the time spent by analysts by applying playbooks for a known threat. Machine Learning (ML) enhances detection of anomalies by understanding the normal behavior. Typically, UEBA technologies are based on ML algorithms designed to detect abnormal behavior of a network. The challenge for Next-Gen SOC is to use Machine learning and automation in an efficient way to assist SOC analysts.

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Next-Gen SOC: Enhancing the efficiency of a SOC with Machine Learning and Automation

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