Handling security across diverse IT environments can be difficult in today’s hybrid-cloud world. SIEM is a vital tool to help.
Why is SIEM important? With a SIEM solution, it can be easier for SOC analysts to manually sift through terabytes of plaintext data. A SIEM can help them quickly analyze and correlate security data with threat intelligence information.
Real-Time Alerts
With countless cyber threats targeting organizations daily, security teams can easily be overwhelmed by an onslaught of alerts. A SIEM security solution can help mitigate this challenge by delivering real-time alerts.
This is accomplished through a process known as log flow, where the system gathers data from various sources (error messages on servers, blocked connections in firewalls, incorrect password attempts in enterprise portals) and correlates them into one security event. Then, the system analyzes the events to look for abnormal patterns and flag them as potential threats.
In addition to the correlation capability, the best SIEM solutions provide other advanced security features. For instance, next-gen SIEMs can leverage AI and deep learning to detect malicious behavior by looking at patterns of human behavior and identifying when the activity deviates from the norm. This can help thwart insider threats that can often elude traditional tools by mimicking authorized network traffic.
It is also important that an SIEM security solution provides a way to prioritize and filter alerts. Otherwise, analysts may become desensitized to alerts and lose the ability to recognize critical ongoing threats. The best solutions, offer threat prioritization that enables security analysts to identify the highest-risk events and offload low-risk events to automated response processes. Then, they can continue focusing on identifying and responding to the most critical threats.
Predictive Analytics
Using predictive analytics, SIEM can identify patterns and anomalous activity that might signal a cyberattack. It can also detect the risk level of a given flag and help security teams prioritize their actions. SIEM can also monitor unauthorized access to critical data, which can help organizations reduce the number of breaches and protect customer information.
Unlike traditional firewalls and intrusion detection systems, which are based on rules, SIEM solutions use advanced analytics to recognize sophisticated data patterns that could be indicative of an attack. Moreover, next-gen SIEM solutions are designed to analyze automatically and correlate events gathered from disparate resources to help security staff quickly find the source of an attack. This can significantly improve mean time to detection (MTTD) and mean time to resolution (MTTR) for security incidents.
The best SIEM software also makes this unified view of system data and alerts available through a centralized dashboard, which can increase interdepartmental efficiencies by improving communication and collaboration. This can help IT security teams manage threats and respond to them in a coordinated, unified way while meeting strict regulatory compliance standards. Ultimately, this can minimize business risks and reduce the cost of IT operations. Moreover, the real-time visibility of SIEM tools’ IT environments can improve compliance with various business regulations, such as HIPAA, HITECH, and PCI.
Detection
SIEM technologies can help you keep a closer eye on security across departments. This is done by aggregating data from multiple systems and displaying it in a centralized dashboard for security teams to monitor activity, triage alerts, and identify threats. This helps reduce response times from days to hours.
Using machine learning and advanced algorithms, SIEM tools detect anomalies in system activity and send automated alerts to the SOC team. They also provide detailed information about the threat so analysts can determine the appropriate procedures to follow to contain and mitigate it.
By creating a baseline for the normal behavior of users, devices, and critical assets on the network, SIEM systems can detect any deviations from that pattern that may indicate an attack is in progress. For example, if a user account generates 30 failed login attempts in 25 minutes, the system would flag it as suspicious and set its priority to high.
Additionally, a good SIEM solution will correlate event data and link it to a specific user or device on the network. This information, along with threat intelligence and robust rules, allows for event prioritization so that high-risk events are addressed promptly, and low-risk events can be offloaded to automatic detection processes. It should also include a feature that identifies external entities so that security staff can respond to advanced persistent threats (APTs) immediately.
Response
In addition to detecting and preventing cyberattacks, an SIEM solution can help companies respond to threats that have already penetrated their defenses. It collects security data from multiple systems and solutions, aggregates it into a single usable dataset, and delivers it to security analysts for proactive threat hunting or post-attack digital forensics. This centralized approach significantly reduces the mean time to detect (MTTD) for advanced persistent threats and minimizes the damage they can cause.
SIEM also provides a central dashboard that delivers real-time visibility into an IT environment to improve interdepartmental communication and collaboration. This also helps organizations meet compliance reporting standards and enables them to identify the root cause of an incident quicker, leading to a faster mitigation and resolution process.
Integrated with powerful security orchestration, automation, and response (SOAR) solutions, an organization can use an SIEM tool to automate the response and remediation of detected threats. This reduces the manual work that security teams have to do, freeing them up for other critical tasks and improving their overall cybersecurity posture. These next-generation tools also employ machine learning to analyze patterns and behavior and spot threats that may be missed by rules-based detection. Moreover, they can help businesses detect and identify insider threats, such as phishing attacks that target specific employees.
