What is SIEM?
Threat and incident detection is a top priority for every organization. Security information and event management (SIEM) provides a comprehensive view of an organization’s security posture by enabling real-time monitoring of all of an organization’s information security systems (Sekharan & Kandasamy, 2017). Event log management is based on consolidated data from multiple sources, drawing conclusions from raw data via logical connections between events found in various logs or security sources via if-then rules. Dashboards and other direct alerting mechanisms for security incidents are standard features of security information and event management systems.
SIEM works by combining two technologies: a) Security information management (SIM), which analyzes data from log files and reports on security threats and events, and b) security event management (SEM), which monitors systems in real-time, alerts network administrators about fundamental problems while finding a correlation between security events (Imperva, 2021). The purpose of a SIEM tool is to centrally collect security information to detect threats and incidents. Therefore, by connecting various logs, SIEM solutions offer security analytics for either current or past events. It incorporates human security analysts by providing visual security analytics capabilities and integrates with cybersecurity intelligence exchange platforms to share threat information. The efficiency of SIEM also includes log management features, such as long-term storage for event data, threat detection, compliance, reporting, and real-time alert notifications. Some popular SIEM tools include Splunk, IBM Q-Radar, and Microsoft Azure Sentinel (Imperva, 2021).
SIEM Security Awareness in the Business Organizations
Most SIEM systems rely on industry-standard security software that has evolved to combat contemporary threats. Furthermore, digital transformation and the rising use of the Internet of Things (IoT) create new entry points for cybercriminals to exploit, aggravating the current state of security within IT infrastructures. Furthermore, complex attacks such as advanced persistent threats (APTs) are challenging to detect using a standalone security solution due to their distributed nature and multiple attack surfaces. SIEM systems provide a bird’s-eye view of the company’s IT security posture, which is an excellent approach to enhance everyone’s awareness of the importance of securing the IT infrastructure. Thus, SIEM solutions collect, correlate, store, and coordinate events created by controlled IT infrastructures. They serve as the foundation of today’s security operations centers (SOC), collecting data from a wide range of sensors, threat detection systems, antivirus systems, and firewalls, coordinating that data, and generating synthetic images of alerts for use in threat processing and security reporting.
Components of a SIEM Solution
Data collection, storage, policies, data consolidation and correlation are all aspects of SIEM solutions that need careful management. SIEM systems are getting better at correlating information from various organizational sources and applying artificial intelligence (AI) techniques to determine whether actions constitute a security incident or breach. The SIEM process is broken down into the following phases (Imperva, 2021);
Most SIEM systems collect data through collection agents installed on endpoint devices, servers, network equipment, and other security systems (such as firewalls and antivirus software) or through protocols such as Syslog forwarding, Windows Management Interface, and others (WMI). Company-obtained protocol network devices or other such equipment. To collect log data regarding cloud-deployed infrastructure such as SaaS Software as a Service (SaaS) applications, modern SIEMs interact with cloud services and can readily consume data from other non-standard sources. Pre-processing may happen at edge collectors, with only some events and event data passing to centralized storage.
In the past, SIEM solutions had to rely on data center-deployed storage, which presented challenges when dealing with massive amounts of data. As a result, not all of the log information was saved. Modern data lake technologies like Hadoop (open-source) provide the foundation of next-generation SIEMs, enabling cheap, almost infinite storage scalability. This paves the way for keeping and analyzing all log data across a wider variety of systems and platforms.
Policies and rules
SIEM solutions enable security personnel to develop profiles that detail how typical business systems operate. That way, they can determine what kind of deviations warrant a security response by establishing rules and thresholds. To automatically detect abnormalities and dynamically construct rules on the data to discover security events requiring investigation, SIEM solutions increasingly rely on machine learning and automated behavioral profiling.
Data consolidation and correlation
The primary goal of a security information and event management system is to centralize all relevant information and facilitate the correlation of logs and events across all relevant systems in an organization. It is possible to link a firewall blocking a connection and a failed password attempt on an enterprise portal to an error message on the server. Security events are derived from various data sources and sent to analysts via alerts and visual displays.
How to Choose a SIEM Solution
All the SIEM systems are robust solutions with a broad user base. When selecting a SIEM solution, evaluate the vendor’s track record and market position, and pay special attention to functionality. The best SIEM solutions cover the core capabilities and add next-generation features suitable for emerging security threats.
Core SIEM Capabilities
Threat detection: SIEM solutions provide accurate threat detection with rules and behavioral analytics (IBM, 2022). They also aggregate threat feeds, backlists, and geo-locations to correlate events. SIEM systems analyze the sum of all data from its log management feature for signs of a threat infiltration or data breach. For example, a failed login is generally not a concern. However, a failed login from one user on applications across the IT environment could signify a threat. You can only see the relationship between the data of these applications via SIEM tools.
Threat intelligence and security alerts: Many SIEM tools connect security systems to threat intelligence feeds (Rosencrance, 2020). SIEM solutions have the ability to connect to threat intelligence streams, including third-party and solution-provider feeds. Isolated feeds often maintain distinct threat data; however, combining data from multiple feeds might help the analyst make the best use of the SIEM solution. This keeps the organization up to date on the latest security risks. SIEM solutions also aggregate and normalize security data, cross-check various sources, assess system activities, and send alerts anytime they identify suspicious activity (Rosencrance, 2020). Thus, SIEM solutions constantly update the security team on potential threats. Finally, when determining which SIEM solution to choose, remember that SIEM is not a standalone solution but should be a component of a larger security strategy.
Compliance Assessment and Reporting: To keep up with the ever-increasing complexity of regulations is one of the most significant challenges for every business. Article 7 of Cobac law 2010/012 is just one example of the rules that specify what kind of data must be kept and for how long. Not complying with regulations can have devastating effects on the company. SIEM solutions provide compliance reporting and can help businesses identify the business’ effectiveness in meeting regulatory requirements (IBM, 2022).
Real-time Notifications: Every second matters when it comes to security, which is why SIEM systems alert security analysts as soon as a security breach or incident is identified. Consequently, when a threat is identified, organizations are in a position to take prompt action to protect the company’s resources.
Data Aggregation: The capacity of a SIEM system to collect data from several locations and show it as a unified picture of all network activity is its greatest strength (Rosencrance, 2020). Dark spots on the network would be difficult to monitor without SEIM solutions, especially as the company expands. Cybercriminals can readily take advantage of this lack of transparency to launch attacks against enterprise networks.
Data normalization: A security system has a plethora of information gathered from a variety of sources. All this information needs to be presented in the same way so that patterns in security occurrences may be easily recognized. By standardizing security data, SIEM solutions make it much simpler to perform in-depth analyses and develop valuable conclusions (IBM, 2022).
Next-Gen SIEM Capabilities
Data Collection and Management: Next-gen built-in connectors make it easy to integrate various data sources into a SIEM solution. Cloud resources and services, network data, on-premise log data, and external devices like cell phones are all key data sources.
Cloud Delivery: Cloud SIEM solutions leverage data lakes and elastic cloud storage to store and manage data obtained from various sources (Jeyashankar, 2022). Thus, cloud SIEM solutions have adequate storage and are very adaptable compared to on-premises SIEM solutions, which are limited by hardware that cannot handle the enormous data quantities produced by today’s organizations.
User and Entity Behavior Analysis (UEBA): Using Machine Learning (ML) techniques, UEBA can establish a baseline of normal user behavior and then spot any deviations from it (IBM, 2022). With this innovation, current SIEM solutions can efficiently identify insider and zero-day attacks that don’t match any known attack signatures.
Security Orchestration and Automation Response (SOAR): Security information and event management systems can now do more than just monitor and notify security analysts thanks to the advent of SOAR (Jeyashankar, 2022). Next-gen SIEM solutions now work with IT and security operation hubs to provide actionable insights to security teams. They can also automate threat response using incidence response playbooks, orchestrate threat detection and response on multiple systems while managing security systems such as firewalls, email servers, and access control management systems.
Automated attack timelines: To make sense of an attack timeline using a conventional SIEM, analysts must compile data from various sources. This can be time-consuming and requires unique knowledge. Next-gen SIEM solutions can generate an attack timeline automatically and display it graphically for easy comprehension by less specialized analysts. With this, it takes substantially less time to conduct an investigation and incident triage while prioritizing incidents.
Imperva. (2021). Security information and event management (SIEM). Imperva. https://www.imperva.com/learn/application-security/siem/#:~:text=Security%20Information%20and%20Event%20Management%20(SIEM)%20is%20a%20set%20of,consolidates%20data%20from%20numerous%20sources.
Jeyashankar, A. (2022). Next Generation SIEM features – Transform your soc with Next-gen SIEM. Socinvestigation. https://www.socinvestigation.com/next-generation-siem-features-transform-your-soc-with-next-gen-siem/
Rosencrance, L. (2020). security information and event management (SIEM). TechTarget. https://www.techtarget.com/searchsecurity/definition/security-information-and-event-management-SIEM
Sekharan, S. S., & Kandasamy, K. (2017). Profiling SIEM tools and correlation engines for security analytics. 2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET),