Training

Artificial Intelligence & Machine Learning

AI for Security: The Ghost in the Machine (Learning)

Presented by Lastline 60 minutes

In order to fully understand the impact of a breach, the detection of malware threats needs to be complemented by the proactive exploration of anomalous network behavior and inter-artifact relationships. This activity is supported by machine learning techniques, which can be leveraged to aggregate and classify events at an unprecedented scale.

Attend this presentation which highlights how machine learning and network anomaly detection can be valuable tools in identifying breaches.

Background

Lastline Enterprise detects the advanced malware in your network that other vendors miss. Lastline has demonstrated 100% accuracy & zero false positives in the most recent NSS Labs' Breach Detection System Group Test. Lastline uses a unique isolation and inspection approach, Deep Content Inspection, to achieve this accuracy. This approach enables it to interact with malware and see everything a piece of malware does-it can't execute a behavior that it can't see. Alternative methods to malware detection like OS emulation and virtualization cannot detect sophisticated evasion techniques, cannot interact with malware, and therefore miss many advanced threats.