Security Information and Event Management (SIEM) combines real-time monitoring, analysis, and response to security events with the collection and storage of security data. It helps organizations detect, respond to, and prevent cyber threats efficiently. As technology advances, SIEM evolves to meet new challenges. Here are several trends shaping the future of SIEM.
Clouds
Many organizations are now shifting their IT infrastructure to cloud services. The way systems interact and transmit information in the cloud is different from traditional local infrastructure. With this move towards cloud-based solutions, SIEM systems are also transitioning to the cloud. However, for some clients, it is still important to maintain some on-premises components. For vendors, it is essential to expand the visibility scope to include both network devices and cloud environments.
New Formats
In cloud infrastructures, the rethinking of SIEM system architecture has led to new formats of operation, such as SIEM-As-a-Service. Previously, the primary format for SIEM outsourcing was through MSSP providers. However, recently, there has been a growing number of providers offering SIEM as pre-configured software combined with cloud computing resources.
New Features
In addition to changes in the platforms for implementing SIEM systems, the required capabilities have evolved as well. For example, SOAR systems used to be separate products that were sold independently. Now, many manufacturers have started including orchestration components within SIEM systems. Some vendors have acquired existing SOAR systems and integrated them into their SIEM offerings, while others have developed their own orchestration components from scratch.
Automation and orchestration features are now available in many SIEM systems, but they come with their challenges. These features can significantly enhance SIEM usage, but only if the organization has a sufficient level of maturity. SOAR requires prior training in systematizing and formalizing processes. As the functionality of SIEM systems expands, the demands on the SOC team also increase.
XDR Integration Trend
Today, SIEM has evolved beyond just a correlation tool to become the central hub of a SOC that is responsible for monitoring and responding to cyber incidents. As a result, there is a trend towards closer integration with third-party solutions, with such interactions being more natively incorporated into the product's architecture from the outset.
SIEM systems are evolving from advanced log management tools into complex solutions for responding to and also removing Trojans and other types of cyber threats. The XDR concept embodies this shift by integrating multiple types of solutions into a single platform, ideally managed through a unified interface.
This system expansion demands highly qualified specialists to work with SIEM. On one hand, SOC management becomes easier because the number of different interfaces is reduced and their logic is unified. On the other hand, it becomes more challenging because a highly skilled specialist is needed who is well-versed in all the components of this integrated system.
The product needs to be simplified as much as possible in terms of user interaction, while customer companies still have high expectations for pre-installed content. Finding a balance between simplicity and comprehensive features is another emerging trend.
Machine Learning
Machine learning remains relevant and has advanced significantly over the past few years. However, its applicability depends on the specific and narrow focus of the field. SIEM systems perform specialized tasks, and machine learning technologies are only suitable for some of these tasks. Currently, some SIEM system vendors include a UBA module, which typically helps analysts identify important events from user activities and assets within large data streams.
This sphere is transitioning from using correlation rules to creating datasets for training models to analyze events and potential attacks. Analysts will primarily focus on developing these datasets and verifying alerts from such intelligent systems.
Currently, these modules are primarily in demand by large organizations with a high level of IT and information security maturity. This is because machine learning requires significant investments while addressing a relatively narrow business task - assisting information security specialists in automating the decision-making process.
Many organizations prioritize perimeter protection before focusing on detecting anomalies in user behavior. As a result, not all companies are integrating machine learning technologies into their SIEM systems yet. This is not a widespread practice but rather a trend for the future.
SIEM's Future Landscape
The trends described above have been developing for some time and remain relevant, but they are not permanent. It is expected that some of them will decline soon. There is even speculation that within the next two to three years, SIEM may disappear as a distinct category. Vendors might create ecosystems where some functions are absorbed by data analytics platforms for security events while comprehensive solutions like XDR take others over. However, these are bold predictions, and their likelihood is uncertain.
What is certain is that SIEM systems will continue to evolve, offering more advanced analytical capabilities to detect complex and hidden threats, such as anomaly-based attacks, insider threats, and the use of distributed traversal techniques.
Best software developers will continue to improve the user experience by providing a more intuitive interface and enhanced data visualization. This will help security analysts better understand information and speed up the process of detecting and responding to incidents. High-quality expertise is also expected to be available out of the box, making it accessible to a wide range of specialists.
Additionally, it will be important to supplement SIEM systems with data on external risks using threat assessment services tailored to specific organizations. This will enable SIEM systems to consider the information that attackers may already have.
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