Security News > 2023 > June > Unveiling the Unseen: Identifying Data Exfiltration with Machine Learning

Data exfiltration often serves as the final act of a cyberattack, making it the last window of opportunity to detect the breach before the data is made public or is used for other sinister activities, such as espionage.

While prevention of data exfiltration through security controls is ideal, the escalating complexity and dispersion of infrastructures, accompanied by the integration of legacy devices, makes prevention a strenuous task.

Machine learning algorithms aid in context-specific learning of diverse thresholds for varying devices and networks, crucial in the current diverse infrastructure landscape.

As a result, effective data exfiltration detection becomes indispensable.

Through volume-based detections and traffic behaviour monitoring, one can identify data exfiltration, pinpointing abnormal alterations in data volume and upload/download traffic patterns.

Request a demo to find out how to leverage ML-driven NDR to detect data exfiltration and anomalous network behaviours for your organisation.

News URL

https://thehackernews.com/2023/06/unveiling-unseen-identifying-data.html