In the past several years, continual advancements in information technology have significantly heightened our need for an efficient means of managing information and cyber security. Of the many strategies generated for this purpose, one of the most crucial is system information and events management (SIEM).
SIEM is a security approach that collects, aggregates, and analyzes data according to a pre-defined correlation rule or corporate policy. SIEM-oriented technology can generate a comprehensive security report based on the collected security logs and present it in a readable format. Think of SIEM as a central repository that performs threat detection, mitigation, reporting, and other security functions across the various devices in your corporate or personal network. These devices may include firewalls, switches, access points, antivirus, and routers.
The breakthrough combination of security event management (SEM) and security information management (SIM) in 2005 led to the creation of system information and events management (SIEM).
However, the newly created SIEM had multiple scaling and performance issues. Further upgrades and modifications arrived in 2011 and introduced a centralized storage mechanism into the system instead of the initial big data paradigm. This evolution allowed for efficient events storage, notification and reporting. The problem with this iteration was the explosion of data which limited the ability of security experts to analyze the security logs collected effectively.
The third iteration of SIEM introduced in 2015 tried to solve this problem by adopting various analytics tools, like machine learning, for advanced data processing and threat detection. And so this brought about the efficient notification-based SIEM we have today.
Managing security information and events across a network of devices used to be a complex task involving incredible effort and resources. It entailed manually combing through millions of network logs to detect potential threats.
SIEM solutions reduce the complexities of managing logs and events by collecting all network information into a central repository, correlating the logs, and checking for hidden cybersecurity threats that would otherwise go unnoticed. When necessary, the technology can then trigger the pre-defined appropriate notification. Additionally, SIEM blends threat feeds, blocklists, and geolocation data to enhance further the accuracy and efficiency of threat identification and reporting.
Although the process might seem daunting, the advantages of adopting a complete SIEM solution for your enterprise or personal cyber security needs are numerous.
SIEM technology incorporates real-time threat recognition. Since it relies on real-time security logs from devices across the network, SIEM can cross-correlate this data across all network systems according to a pre-defined corporate security policy. SIEM also continuously incorporates machine learning algorithms and other automated logic to enhance real-time threat recognition.
SIEM technology can provide some of the most advanced threat detection and monitoring. It can detect suspicious behaviors and potential threats via constant monitoring of every event and user activity. From there, it can trigger the appropriate mitigation protocols and notifications whenever necessary. These advanced functions can significantly improve the integrity of a corporate or personal network, providing a way to stop security breaches before they happen.
Furthermore, SIEM improves the efficiency of security monitoring. With the help of powerful computing resources and machine learning automation, SIEM can easily handle a network’s security functions, including log collection, aggregation, parsing, and storage. It also generates reports in a simplified format, reducing or eliminating the need to compile security reports manually.
SIEM is also an optimal tool for easing compliance audits. Before the advent and adoption of SIEM solutions, generating system log audits for regulatory compliance was a considerable task that involved manually collecting and compiling hundreds of thousands of event logs across all devices on a network. Now, a properly implemented SIEM solution does all the heavy lifting — as event logs aggregate continuously and are read-ready.
An oversensitive security system that sends false positives only trains you to ignore security protocols. Fortunately, a complete SIEM solution considers the type of server you are operating, the applications running on the server, and most importantly, the server’s configuration to reduce false security notifications significantly. This intelligence-driven approach helps prevent unwarranted alerts and ensures that only actionable and credible notifications are triggered.
When an event does trigger a security alert, the SIEM structure proves instrumental in providing the ability to investigate the potential threat. SIEM technology design ensures that all red flags are vetted and correlated across threat feeds, blocklists, and geolocation data. This aligns with your corporate security policies and the data types needed to investigate threats properly.
As with most modern technologies, there are several best practices for SIEM that you should follow to ensure it works as comprehensively and efficiently as possible.
With a clearly defined scope and correlation rules, SIEM understands the structure and attributes of your corporate or private network. This enables the system to detect and mitigate security threats. Correlation rules may be understood as a set of clearly defined logical expressions or conditions that initiates a system response to security breaches. These systems’ responses could be in the form of alerts or the execution of threat mitigation protocols.
One of SIEM’s best practices is the integration of AI into the threat detection, analysis, and reporting process. This can significantly reduce the probability of errors while improving the speed and efficiency of the system. Artificial Intelligence can play an essential role in boosting your SIEM system’s overall capability and your network’s health.
A thoroughly established compliance requirement or corporate policy provides a robust framework in which the SIEM solution can operate. These requirements will likely include threat recognition and response standards, data processing, notifications, and reporting
Asset classification is an essential prerequisite for setting up the SIEM solution. It involves outlining the various network or corporate-critical infrastructures and assets on a scale of security priority levels, ensuring that the most sensitive resources receive the highest priority for threat detection and mitigation. Asset classification also helps to control resources, preventing the use of excessive computing power for low-priority or non-critical assets.
Performing proper system testing is the best way to evaluate the overall performance and compliance of the software. It often involves exposing the system to scenarios that trigger any number of functions to ensure that each component is working optimally. Any possible error is debugged at this level, and you can fine-tune the system for efficiency.
