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
#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 10.40.4.182 10.40.1.11 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
Endpoint Logs
Application Logs
Proxy Logs
IoT Logs
#2. Efficient Log Handling
Parsing
Consolidation
Categorization
Log enrichment
#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
- 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.
#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.