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The Top 5 Benefits of Using SIEM

Security Information and Event Management (SIEM) represents a pivotal shift in the evolution of cybersecurity, aiding organizations in preemptively detecting, analyzing, and responding to security threats before attackers do. These systems aggregate event log data from various sources, employing real-time analysis to cut out noise and support lean, switched-on security teams.

The role of Artificial Intelligence (AI) within SIEM is gaining prominence as learning models evolve. Thanks to the fact that algorithms dictate how logging data is transformed into predictive analytics, advancements in AI and machine learning have allowed for even greater improvements in vulnerability management.

This article will cover why organizations need a SIEM solution in the first place, and what are some of the SIEM benefits they can expect as a result of the solution’s ability to collect and analyze log data from all digital assets in one place.

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Why Do Organizations Need a SIEM Solution?

Cyberattacks are no longer a rare occurrence: they’re everyday events, and an increasing component to international conflict. With the average organization now relying on hundreds of different applications – and thousands of devices, endpoints, and networks – the opportunity for attackers to slip in unnoticed is at an all-time high. Even industry heavyweights such as Google Chrome fall foul to vulnerabilities – and with zero-days such as the recent CVE-2023-6345 having been exploited in the wild – keeping a close eye on every single application has never been more vital. 

Oversights continue to be the root cause of almost every successful cyberattack. Security leaders such as password management organization Okta have fallen foul of large-scale breaches – following their breach in October, more information has shown that threat actors downloaded the names and email addresses of all Okta customer support system users.

How SIEM Helps Bust Security Oversights

SIEM (you can learn more about what SIEM is here) systems play a pivotal role in proactively detecting security threats that allow attackers in. Essentially, this 360-degree visibility is achieved by continuously monitoring real-time changes to IT infrastructure. These real-time alerts allow security analysts to identify anomalies and promptly lock suspected vulnerabilities down. In addition to proactive threat detection, SIEM significantly contributes to incident response efficiency. This drastically accelerates the identification and resolution of security events and incidents within an organization’s IT environment. This streamlined incident response enhances an organization’s overall cybersecurity posture.

The application of AI in SIEM further grants new depth to network visibility. By rapidly uncovering blind spots in networks and extracting security logs from these newfound areas, they greatly extend the reach of SIEM solutions. Machine learning empowers SIEM to proficiently detect threats across wide ranges of applications – further applications funnel this information into an easy to use reporting dashboard. The time and money saved by this helps to ease the burden of threat hunting on security teams. SIEM tools offer a centralized view of potential threats, presenting security teams with a comprehensive perspective on activity, alert triage, threat identification, and the initiation of responsive actions or remediation. This centralized approach proves invaluable in navigating complex chains of software flaws that are so often the basis of attack.

A SIEM provides enhanced transparency in monitoring users, applications, and devices, offering comprehensive insights to security teams. Below, we take a look at some of the most significant SIEM benefits organizations can expect.

5 Benefits of SIEM

SIEM is greater than the sum of its parts. At the heart of its security positioning is the ability to sort through thousands of logs and identify the ones that are cause for concern.

#1. Advanced Visibility

SIEM has the capability to correlate data spanning an organization’s entire attack surface, encompassing user, endpoint, and network data, as well as firewall logs and antivirus events. This capability offers a unified and comprehensive view of data – all through a single pane of glass.

In generic architecture, this is achieved by deploying a SIEM agent within your organization’s network. When deployed and configured, it pulls this network’s alert and activity data into a centralized analytics platform. While an agent is one of the more traditional ways of connecting an app or network to the SIEM platform, newer SIEM systems have several methods to gather event data from applications that adapt to the data type and format. For instance, connecting directly to the application via API calls allows SIEM to query and transmit data; accessing log files in Syslog format allows it to pull info directly from the application; and utilizing event streaming protocols like SNMP, Netflow, or IPFIX enables real-time data transmission to the SIEM system.

The variety in log collection methods is necessary thanks to the sheer range of log types that need to be monitored. Consider the 6 main log types:

Perimeter Device Logs

Perimeter devices play a crucial role in monitoring and controlling network traffic. Among these devices are firewalls, virtual private networks (VPNs), intrusion detection systems (IDSs), and intrusion prevention systems (IPSs). The logs generated by these perimeter devices contain substantial data, serving as a key resource for security intelligence within the network. Log data in syslog format proves essential for IT administrators conducting security audits, troubleshooting operational issues, and gaining deeper insights into the traffic flowing to and from the corporate network.

However, Firewall log data is far from easy reading. Take this generic example of a firewall log entry:

2021-07-06 11:35:26 ALLOW TCP 63064 135 0 – 0 0 0 – – – SEND

The provided log entry includes a timestamp of the event followed by the action taken. In this case, it denotes the specific day and time when the firewall permitted traffic. Additionally, the log entry includes details about the protocol employed, along with the IP addresses and port numbers of both the source and destination. Analyzing log data of this nature would be near impossible for manual security teams – they’d swiftly be swamped by the overwhelming number of entries.

Windows Event Logs

Windows event logs serve as a comprehensive record of all activities occurring on a Windows system. As one of the most popular OS on the market, Windows’ Security Log holds significant importance in almost every use case, offering valuable information about user logins, failed login attempts, initiated processes, and more.

Endpoint Logs

Endpoints are one of the most vulnerable areas of any network. As end-users interact with external web pages and data sources, keeping a close eye on concerning developments can keep you on top of novel phishing and malware attacks. System monitoring grants a deeper look into events such as Process Creation, Network Connections, Processes Terminated, File Creation, and even DNS requests.

Application Logs

Organizations rely on immense arrays of applications, including databases, web server applications, and in-house apps, to fulfill specific functions crucial for their efficient operation. Logs produced by various applications capture user requests and queries, which prove valuable for detecting unauthorized file access or attempts at data manipulation by users. Additionally, these logs serve as valuable tools for troubleshooting issues.

Proxy Logs

Similar to endpoints themselves, proxy servers hold a crucial role in an organization’s network, offering privacy, access control, and bandwidth conservation. As all web requests and responses traverse through the proxy server, the logs generated by proxies can provide valuable insights into usage statistics and the browsing behavior of endpoint users.

IoT Logs

With IoT devices now at the highest risk of DDoS manipulation, it’s vital to keep all of your peripherals adequately monitored. IoT logs include details around network traffic and suspicious behavior that keeps the entirety of your device inventory within your view. With almost every log type collected by a SIEM solution, it needs to start building a view of your overall security – and quickly!

#2. Efficient Log Handling

While the depth of log data included in SIEM is impressive, the sheer volume and variety of these have already induced a cold sweat into any nearby security analyst. SIEM’s unique advantage is in its ability to rapidly consolidate interconnected security events into prioritized alerts. Logs from the aforementioned sources are typically directed to a centralized logging solution, which then performs correlation and analysis of the data. The mechanisms for doing this may look intimidating from the outside, but breaking it down helps to show its inner workings:


Even within unstructured log data, discernible patterns can emerge. A parser plays a crucial role by taking unstructured log data in a particular format and transforming it into readable, pertinent, and structured data. Employing multiple parsers tailored for different systems allows SIEM solutions to handle the diverse range of log data.


This process entails consolidating various events with diverse data, minimizing the log data volume by incorporating common event attributes like shared field names or values, and transforming it into a format compatible with your SIEM solution.


Organizing the data and categorizing it based on various criteria such as events (e.g., local operation, remote operation, system-generated events, or authentication-based events) is vital to determine a structural baseline.

Log enrichment

This enhancement process incorporates crucial details like geolocation, email address, and the operating system used into the raw log data, enriching it to be more relevant and meaningful. The ability to aggregate and normalize this data allows for efficient and easy comparison.

#3. Analysis and Detection

Finally, the critical SIEM advantage can take place. The three primary methods of log analysis are a correlation engine, a threat intelligence platform, and user behavior analytics. A fundamental component in every SIEM solution, the correlation engine identifies threats and notifies security analysts based on predefined or customizable correlation rules. These rules can be configured to alert analysts – for example, when abnormal spikes in the number of file extension changes is detected, or eight consecutive login failures within a minute. It’s also possible to set up automated responses that follow on from the correlation engine’s findings.

While the correlation engine keeps a close eye on logs, the Threat Intelligence Platform (TIP) works to identify and safeguard against any known threats to an organization’s security. TIPs provide threat feeds, which contain crucial information such as indicators of compromise, details about known attacker capabilities, and source and destination IP addresses. Integration of threat feeds into the solution through an API or connection to a separate TIP powered by different feeds further strengthens the SIEM’s threat detection capabilities.

Finally, User and Entity Behavior Analytics (UEBA) leverage ML techniques to detect insider threats. This is achieved by continuously monitoring and analyzing the behavior of every user. In the event of any deviation from the norm, UEBA records the anomaly, assigns a risk score, and alerts a security analyst. This proactive approach allows analysts to assess whether it’s an isolated event or part of a larger attack, enabling appropriate and timely responses.

#4. Action

Correlation and analysis play a crucial role in threat detection and alerting within a Security Information and Event Management (SIEM) system. When a SIEM is appropriately configured and tuned to align with your environment, it can reveal indicators of compromise or potential threats that may result in a breach. While some SIEMs come with preconfigured alert rules, finding the optimal balance between false positives and false negatives is essential to minimize alert noise, ensuring that your team takes timely action for effective remediation. With these defenses in place, SIEM log analysis can help you spot the following threats:
  • Spoofing: This sees attackers use a fraudulent IP address, DNS server or address resolution protocol (ARP), in order to infiltrate a network under the guise of a trusted device. SIEM rapidly discovers intruders by alerting when two IP addresses are sharing the same MAC address – a surefire sign of network intrusion. 
  • Denial of Service (DoS) or Distributed Denial of Service (DDoS) attacks: DDoS attacks see attackers flood a target network with requests, in order to make it inaccessible for its intended users. These attacks often target DNS and web servers, and an increasing number of IoT botnets have allowed attackers to build staggering 17-million-request-per-second attacks.
Historically, the primary approach to defending against Distributed Denial of Service (DDoS) attacks has been reactive. In response to an attack, organizations would typically seek assistance from a content delivery network partner to mitigate the impact of the traffic surge on their sites and servers. With SIEM, however,  it’s possible to detect early warning signs such as sudden changes in IP address and traffic behavior. Sniffing and Eavesdropping: Attackers intercept, monitor and capture sensitive data flowing between a server and a client using packet sniffer software. For eavesdropping, threat actors listen to data flowing between networks – similar to sniffing attacks, this process is usually passive and may not involve full data packets.

#5. Compliance Support

Having the tools is vital to attack prevention: but proving you have these abilities ahead of time is the essence of regulatory compliance.

Instead of manually compiling data from various hosts within the IT network, SIEM automates the process, reducing the time required to meet compliance requirements and streamlining the audit process. Additionally, many SIEM tools come equipped with built-in capabilities, enabling organizations to implement controls aligned with specific standards such as ISO 27001.

The range of SIEM advantages is poised to re-align your organization with cutting-edge defenses. However, traditional SIEM has not fully lived up to its potential – complex configuration requirements have placed greater demand on lean teams than can be fulfilled.

Next-Gen SIEM Pushes Security To New Heights

The benefits of next-gen SIEM lie in striking a happy medium between collecting enough data such that you get a comprehensive view of the network but aren’t overwhelmed by the sheer volume of information. Stellar Cyber’s built-in AI and advanced analytics provide a responsive and ultra-transparent foundation – and its open architecture further allows for development on top of the platform. Customized and unified, experience cross-departmental security with Stellar’s Next Gen SIEM Platform.
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