Estimated reading time: 5 minutes
The data that a corporate IT infrastructure generates every day has always been a lot, but never as in recent years has there been an event overload (event overload) of such vast proportions. This is due to the increasing number of applications used by companies and employees for routine operations.
Each of the applications used, in fact, generates a certain amount of characteristic “events”. This data is collected and analyzed to identify any problems of any kind as soon as possible. However, when the data to be analyzed becomes too much, an event overload problem arises, i.e. the analysis tools cannot keep up.
However, by adopting a suitable solution, you can also deal with large amounts of data while maintaining the high standard of reactivity and response of the analysis tools. Let’s see how in this article.
Relational databases are now out of the game
In 2018, relational databases were the best you could get when it came to data management. The size of the databases used to extend to a maximum of around 50GB. Security solutions could afford these databases to provide the space that enabled Security Operations Centers (SOCs), which were generally part of a larger data center. This is no longer true.
As organizations have gotten bigger, both data volumes and corporate networks have grown exponentially , making it necessary to move to the public cloud to accommodate the size needed to store and process these information. In addition to enabling scalability, public cloud services are also providing an increasingly broad range of services that are required to use modern technologies such as AI, DevOps, and continuous integration / delivery (CI / CD).
The support of requirements such as identity integrations and connectors between multiple business applications adds to the huge amounts of data that are being transferred. The number of applications a business leverages today can be in the hundreds , if not more, and all generate their own logs and security alerts . It’s easy to see how frequent event overload situations can be.
This brings a cascade of events into the SOC from a variety of sources every day, requiring massive storage as well as fast research, operations and analytics for effective detection and response to cyber threats.
The operational centers (SOC) of today
As we’ve seen, growing volumes of data, regulatory compliance requirements, and security concerns require companies to collect and store more data than ever before. Furthermore, security monitoring is more challenging as the attack surface increases due to various factors. Among these we can identify digital transformation, bring your own device policies. (BYOD), cloud migration and other modern infrastructure trends.
There are many reasons why today’s SOC struggles with legacy solutions that hinder its ability to detect and respond to advanced threats. Here are some of the challenges he faces.
Most medium-sized businesses handle daily events in the millions . Large enterprise SOCs ingest about one billion events per day. This can generate up to several terabytes of data every day. A quantity that certainly cannot be managed by traditional relational databases because they cannot scale to manage these volumes while maintaining the same level of performance and operational speed. Relational databases, such as mySQL or SQL Server, provide limited support for consolidated analyzes that use structured, unstructured, or hybrid data due to architectural limitations. However, this capability is essential for detecting today’s sophisticated threats.
Analysts need the ability to sift through all of these events multiple times a day to search and find threats. Slow search queries are no longer an option in handling an event overload of these proportions.
The characteristics of an adequate solution against event overloads
There are solutions that overcome these obstacles to better arm the SOC and detect advanced threats. We need to implement a solution that has the following characteristics:
– It is a cloud-native, scalable platform that enables faster search with state-of-the-art analytics and efficient space management.
– Scale resources on demand instead of statically.
– Maintains low infrastructure and storage costs by intelligently allocating resources. All to store and process security data.
– Provides secure and privileged access management for users.
– Offers robust data security and granular control over data which are stored in the cloud.
SOD’s solution to event overload
One of the most advantageous solutions is the decentralization of operations centers. By adopting a SOC as a Service , you immediately get the advantage of scalability. But it does not end here, in fact the tools provided in the SOC, such as the Next Generation SIEM , have an edge in terms of data collection and analysis. . Here are some of the main advantages of the service offered:
– More efficient use of resources which helps reduce costs and provide scalability for peak activity and test environments through auto scaling and ‘dynamic orchestration.
– Faster searches with improved analytics and management through direct integration of the AWS platform with improved AWS S3 access capabilities.
– Critical data protection at a lower cost by using activity and data-based cluster segregation to reduce resource use for ad-hoc research and testing.
Benefits for analysts
The corporate security team can now take advantage of real-time threat hunting and faster long-term search. This is benefited by the efficient use of AWS EMR and S3 together for data storage of 12 months or more.
Real-time research and long-term research combine to provide comprehensive threat hunting capability for analysts .
Adopting a truly next-generation and cloud-native SIEM brings the power of the cloud to SOC, enabling better search , better use of resources and far fewer hours spent chasing false positives and managing infrastructure overload.
To find out how this solution can help your business, do not hesitate to contact us, we will be happy to answer any questions.
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