Threat and Vulnerability
Security Analytics to understand and detect risk level of vulnerabilities. Artificial Intelligence, Machine Learning and Depp Learning techniques to reduce human error. Identify security breaches and eliminate obstructions.
Artificial Intelligence Solutions involve right collection of data, representation Learning Application, Machine Learning customisation, Cyber Threat Analysis, and identification of Model Security Problem. It involves Perspective Analytics, Diagnostic Analytics, Predictive Analytics, Detective Analytics and Descriptive Analytics.
It involves removal of unnecessary data, Feature Extraction and Selection, Data Cutoff, Parallel Processing, Machine Learning and Deep Learning Algorithms, Result Polling and Optimised Notification.
It involves Alert Correlation, Signature Based Anomaly Detection, Attack Detection Algorithm and combination of Multiple Detection Methods, Algorithm Selection.
It involves Dropped Netflow Detection, Dynamic Load Balancing and MapReduce. Netflow Detection involving Netflow Sequence Monitoring, Netflow Collection, Netflow Storage and Data Analysis, generating warning messages.
It involves Source Data Transformation comprising User Activity, Application Activity, DataBase Activity, Network Activity, Distributed Data Storage, Public Key Infrastructure and Encryption.
The pre-processed security event data forwarded to the Data Analysis module, which analyses the data for detecting Cyber attacks. The results of the analysis (i.e., alerts) forwarded to the alert ranking component, which ranks the alerts based on a predefined criterion.
It involves Data Ingestion Monitoring, Maintenance of Multiple Copies, Dropped Netflow Detection and Alert Ranking.
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