Top 5 Applications of Machine Learning in Cyber Security

Cyber security is a rapidly growing field, and machine learning is playing an increasingly important role in protecting computer systems and networks from attack. Machine learning can be used to automate many of the tasks involved in cyber security, such as identifying and responding to threats, and it can also be used to develop new ways to protect systems from attack. Here are the top 5 applications of machine learning in cyber security: Intrusion detection: Machine learning can be used to identify potential intrusions by analyzing network traffic and other data. Malware detection: Machine learning can be used to detect malware by analyzing its code or behavior. Fraud detection: Machine learning can be used to detect fraud by analyzing financial transactions and other data. Vulnerability assessment: Machine learning can be used to assess the vulnerabilities of computer systems and networks. Security orchestration, automation, and response (SOAR): Machine learning can be used to automate many of the tasks involved in cyber security, such as responding to threats and managing security incidents. These are just a few of the many ways that machine learning is being used in cyber security. As the field of machine learning continues to evolve, we can expect to see even more innovative applications of machine learning in cyber security in the future.