How Machine Learning Can Help Identify Cyber Vulnerabilities

People are undoubtedly your company’s most valuable asset. But, if you ask cybersecurity experts if they share that sentiment, most would tell you that people are your biggest liability. But an emerging discipline in cybersecurity focused around user behavior analytics can help. It leverages a combination of big data and machine learning, allowing security teams to quickly identify when things may be happening that are out of the norm. Data points such as the typical location of an employee’s IP address, the time of day they usually log into the networks, the use of multiple machines/IP addresses, the files and information they typically access, and more can be compiled and monitored to establish a profile of common behaviors. For example, if an employee in the HR team is suddenly trying to access engineering databases hundreds of times per minute, it can be quickly flagged to the security team to prevent an incident. The combination of understanding employees’ everyday interactions with IT and having the power to analyze every possible scenario in real-time can help security teams define more appropriate levels of authentication for the entire workforce.