Machine Learning in Security

Machine Learning in security involves using algorithms that analyze large amounts of data to identify patterns and detect potential threats automatically. Instead of relying solely on predefined rules, these systems learn from past incidents to recognize new or evolving cyber threats, such as malware or unauthorized access. This allows security measures to become more proactive and adaptive, reducing false alarms and improving response times. Essentially, machine learning enhances cybersecurity by enabling systems to understand and respond to threats more intelligently and efficiently.