Advantages and disadvantages of SIEM
Advantages of SIEM
Security information and event management(SIEM) systems have several Advantages, including:
Real-time threat recognition
SIEM systems’ constant monitoring and real-time data processing help businesses identify anomalous behavior early, significantly lowering the possible impact of security events.
Identifying unknown and advanced threats
SIEM improves the detection capabilities for complex threats, such as ransomware and zero-day exploits, by integrating threat intelligence and advanced analytics. SIEM systems are able to identify intricate patterns and irregularities that point to the existence of sophisticated threats.
Simplifying forensic investigation
SIEM offers the comprehensive and useful logs required to follow the path of cybercriminals and comprehend the type of breach. The breadth and depth of logging, which includes network traffic, system modifications, user actions, and more, give investigators the means to carry out investigations quickly.
Disadvantages of SIEM
SIEM systems have several disadvantages, such as:
Complex integration
One major obstacle is the intricacy of connecting SIEM systems with the current IT architecture. To guarantee efficient functioning, compatibility problems, data format differences, and the sheer volume of data necessitate customization and fine-tuning.
Complex to use
SIEM systems need a skill set that many IT departments lack, which might result in a need for outside suppliers and higher management and training expenses. Long-term operational difficulties may arise from this reliance, which can make SIEM solutions more difficult to maintain and scale.
Rules-based identification
The majority of SIEM systems are focused on rules-based detection, which frequently produces a large percentage of false positives, overwhelming security staff and causing alert fatigue. To overcome this difficulty, contemporary SIEM solutions employ behavioral analysis and threat intelligence.
Invalidated contextual alerts
SIEM systems can have trouble giving the alerts they produce enough context, which makes it difficult to determine the seriousness and veracity of occurrences. As teams rush to comprehend the ramifications of each warning, this may cause reaction times to be delayed.
Best practices to implementing SIEM
When putting SIEM into practice, adhere to these recommended practices:
- Establish comprehensible objectives. Security objectives, compliance, and the organization’s possible threat landscape should all be taken into consideration while selecting and implementing the SIEM technology.
- Use the rules of data correlation. All systems, networks, and cloud deployments should use data correlation rules to make it easier to identify data that contains mistakes.
- Determine the requirements for compliance. This makes it easier to confirm that the SIEM software of choice is set up to audit and report on the appropriate compliance requirements.
- Enumerate your digital assets. It is easier to manage log data and keep an eye on network activity when all digitally recorded data is listed throughout an IT architecture.
- Keep track of incident response procedures and plans. This makes it possible for teams to react quickly to security problems.
- A SIEM administrator should be assigned. The correct upkeep of a SIEM solution is guaranteed by a SIEM administrator.
SIEM Architecture: Then and Now
SIEMs were once costly, monolithic business infrastructures that were equipped with specialized hardware and proprietary software to manage their massive data volumes. SIEMs are changing to become more intelligent, lightweight, and agile, much like the software industry as a whole.
Modern design is used by next-generation SIEM systems, which are easier to deploy, more reasonably priced, and assist security teams in identifying actual security threats more quickly:
- Big data storage with infinite scalability, affordability, and enhanced performance is possible with modern data lake technology.
- New alternatives for managed hosting and management: MSSPs are assisting businesses with SIEM implementation by managing security procedures and operating a portion of the infrastructure (on-site or in the cloud).
- SIEM administrators no longer have to carefully determine size and make architectural adjustments as data volumes increase to dynamic scalability and predictable prices. Now, SIEM storage may expand in a predictable and dynamic manner as volumes rise.
- Contextualizing data is crucial for removing false positives from the SIEM system so that data analysis can properly identify and address actual risks.
- User and Entity Behavior Analytics (UEBA) offers fresh perspectives. These days, SIEM infrastructures incorporate sophisticated analytics features like behavioral profiling and machine learning, which go beyond conventional correlations to find new patterns and abnormalities in massive data sets. See our UEBA chapter for additional information.
- Using Security Orchestration and Automation (SOAR) technology, which helps detect and automatically respond to security issues and facilitates incident investigation by Security Operation Centre personnel, modern SIEMs power incident response. See our incident response chapter for more information.
What Is the Difference Between SIEM and SOC?
| Aspect | SIEM (Security Information and Event Management) | SOC (Security Operations Center) |
|---|---|---|
| Definition | Tools/software for logging and analyzing security data. | Team and facilities dedicated to monitoring and improving security posture. |
| Purpose | Facilitates the collection, analysis, and reporting of security events. | Continuous monitoring, analysis, and response to security incidents. |
| Core Functionality | Provides automated logging, event correlation, and alerting. | Handles incident response, threat hunting, and remediation efforts. |
| Dependency | Can operate independently of a SOC. | Utilizes SIEM and other tools to enhance operational efficiency. |
| Implementation | Software-based, requiring proper setup and integration. | Human-centric, involving skilled personnel and physical/virtual infrastructure. |
| Scalability | Limited by the software and infrastructure. | Dependent on team size, expertise, and technology stack. |
| Key Output | Data-driven insights, alerts, and reports on potential threats. | Actionable decisions, threat mitigation, and system improvements. |
| Usage in Isolation | Can be deployed without a SOC. | Can operate without SIEM but may require other tools for functionality. |