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Data Quality To Compute Risks Early

Proper data management helps ensure that your security team as well as Board of Directors will be making the most accurate decisions based on the most accurate information. 

The Challenge

One of the common mistakes we observe in many Security Operations Centers (SOC) and Managed Security Services Providers environments is data overload as a result of heavy integration of sources and their logs into SIEM platforms. An unfocused strategy could trigger a chain of reaction. In other words, the digestion of unclassified logs in every single source will not just blur the visibility, but also will increase the EPS consumption. As a result, your security team will find it challenging to detect valuable logs, and eventually, false-positive rate will provide a wrong misconception of your organization's security posture. In order to avoid it, we need to consider specific data structure at the beginning of data management project.

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Key Factors

 

Logs are the first defensive tool, and lack of visibility could be critical in the moment to research a security incident. Since compliance alignment is mandatory to store certain data types, It is necessary to understand and classify the types of logs for each source that will be integrated, avoid at all cost discarding valuable logs in terms of visibility and compliance. Therefore, one of the key factors to reach out effectiveness on security monitoring is data selection.

Our Strategy

To eradicate this issue from the root,  we conduct a study about client's requirements in-depth, scoping correctly and defining a plan considering the risks. To sum up, provide a suitable SIEM service without to promise castles in the clouds. For us,  the synchronization between Sales & Operation teams is crucial to be successful.  Well-designed by-default.

 

Relevant Services / Products

 

  • Technical Consultancy  

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