Ai Powered security analytics that strenghten detection accuracy
Rating: 8 out of 10
IncentivizedUse Cases and Deployment Scope
In our orgnisation IBM watsonx.ai is primarily used to enhance threat detection automate security analytics and it helps to improve accuracy of incident triage within our soc Operations as security analyst I leverage this platform to analyze large volume of log and alert data to interpret them against threats and malwares or malicious behaviour from Qradar logs
Pros
- AI driven LOG ANALYST and Investigation processing large volume of alerts and security events for incident categorisation and its identification that helps to detect attac at earlier stages of security incidents
Cons
- while AI driven insights are accurate the reasoning behind alert prioritization or anomalu scoring is somtimes opaque analyst often need more transperancy into why specific event was flagged or how a confidance score was derived
Likelihood to Recommend
IBM watsonx.ai is highly effective in environment where multiple security data sources generate large volume of the data and alert wherein tool will be helpful in corlate login anomalies and lateral movement detection and data access patterns to identify early signs of incidents and its alert prioritizationd and false positive refuctions helps analyst to focus on genuine alerts