Wipro Holmes for Cyber Defense
by Wipro Ltd
Wipro Holmes Reimagining Cyber-defense process using AI solution
Today’s Cybersecurity Analysts are able to identify False Positive triggers from SIEM (security information and event management) system only after investigating the offense. Hence, unable to focus actual threats on daily basis. Also majority of the offenses are False Positive, therefore more time is spent in investigating the false threats and the system enhancement becomes difficult for the domain experts.
The objective is to identify the false positive and
true positive alerts raised from SIEM (Q-Radar system) and to improve the cyber
defense process with Advance AI capabilities with greater accuracy.
About Solution:
Wipro Holmes Reimagining Cyber-defense process is a AI
solution to identify the root cause for False Positive alerts and provides AI
guided insights to cyber security analysts to reduce time & effort to focus
on actual alerts and reduce the associated risk of missing threat due to
pipeline issues. Also,
enabling the team with inferences to significantly reduce manual efforts &
human errors thus regaining associated benefits of time for more productive
activities. Microsoft Workloads such as Azure
Blob storage for storing the data from SIEM tools (QRadar)
and IP reputation data, Azure
Active Directory for user validation, Azure ML
Studio for ML pipelines for build, deploy & monitor
the AI models (the complete MLOps to automate & accelerate the machine
learning lifecycle) and Azure
Compute - container/cluster instance - For model
training, Azure inference for real time inference.
Key
features:
- Identifies false alerts due to data inconsistency with greater accuracy
- Empowers Cyber-Security Analysts with
Inferences to close the incidents or offenses
- Reduces
associated risk by correctly identifying the alerts which the
existing tool misses out
- Standalone System – Easily
pluggable to existing device as well as on any new devices
- Provide inferences on root cause of false positive.
- Incorporate dynamicity of data and use-case.
- More rapidly offense investigation.
- Significantly
reduces the time and effort in investigation