LOGTITAN SIEM comes with advanced correlation engine, behavioral analytics and Machine Learning (ML) models to automate pattern discovery while facilitating intelligent rule creation.
As a subfield of Artificial Intelligence (AI), LOGTITAN’s ML uses algorithms to find patterns in data and models them to detect anomalous behavior of users and entities. LOGTITAN’s machine learning library, pre-packaged with over 1,000 models and correlation rules, enables organizations to better identify advanced persistent threats (APTs) that have previously been flying under the radar.
The emergence of large volumes of fast-moving unstructured data by web, cloud, email, social media, and IoT poses a challenge to all organizations. Combining the information gleaned from machine learning models with the log and event data, LOGTITAN SIEM detects known threats in real time while supporting advanced incident response processes. In a time that cybersecurity talent is stretched thin, this is a huge benefit and relief to IT security teams.
Having access to powerful intelligence feeds, LOGTITAN SIEM provides predictive analytics, continuously learning from historical and present data via machine learning techniques, that helps predict and prevent future attacks on your IT systems. Operating up to 100 times the speed of manual threat investigations, it spots attacks, uncovers new threat patterns, triages threats and identifies the root cause of an attack.
LOGTITAN ML models profile a given user or asset behavior on a particular aspect of interacting with the corporate or IT environment. Here are a few examples of ML detection models: