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Whether you’re looking to purchase a SIEM solution or are already using one, understanding its value will help you make the most of it. Identify your security requirements and determine what log sources your SIEM should collect based on them.
Correlation and log data analysis will allow you to detect attacks, such as lateral movement across systems, by analyzing IP addresses, credentials or machines.
Threat detection in SIEM refers to the tools used to find threats, like malware and viruses, lurking inside your network. Using an approach similar to smoke detectors, one of the reasons why is SIEM important is that SIEM software monitors your system in real-time for signs of malicious activity, such as unauthorized access or a sudden change in data behavior. It also alerts the relevant teams and helps them contain or eradicate those threats to reduce dwell times and prevent further damage to your organization.
Each creates terabytes of plaintext data every month With all the components that make up your IT ecosystem, including devices, apps, servers and databases. Manually identifying events suggestive of a breach is an impossibly large task. Still, SIEM solutions centralize and standardize all your logs for easy correlation and security analysis.
Some SIEM platforms even integrate with third-party threat intelligence feeds to recognize known attack signatures and profiles automatically. This enables analysts to quickly focus on identifying and escalating only events they prioritize as truly risky. They can then send instructions to other security tools, such as firewalls or endpoint protection tools, to stop or contain the threat and reduce damage to your business. As a result, it can significantly reduce incident response times and the amount of time attackers have to do damage.
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SIEM accelerates the identification of cyberattacks by providing IT analysts with a centralized view of their IT environment. Its centralized collection, categorization, monitoring, synchronization and analysis features allow IT teams to detect cyberattacks faster and more accurately than manual methods while improving interdepartmental efficiencies.
A SIEM solution can also reduce cyber risk by monitoring data access, detecting anomalous behavior and tracking BYOD policies and IT configurations. It can also assist with demonstrating compliance with regulations such as PCI, SOX, HIPAA and GDPR by creating reports of IT activity.
The most critical feature of a SIEM system is the ability to provide context around security alerts. Without this capability, it’s easy for security teams to get overwhelmed with false alarms and otherwise insignificant issues. This is why Varonis adds intelligence to every alert, enabling IT staff to prioritize and resolve security incidents easily. With this intelligence, IT personnel can prevent cyberattacks from escalating into major breaches by implementing response plans and stopping them at the source. To improve alert prioritization, next-gen SIEM solutions can perform preprocessing at edge collectors before sending them to a central management console, eliminating the need for analysts to sift through millions of fragmented and siloed data bits manually. They can also automatically connect the dots to prioritize incidents based on common attributes, such as file integrity changes, a blocked connection on a firewall or a wrong password attempt in an enterprise portal.
The core of SIEM is its ability to filter massive amounts of security data and alerts so that only the most important events are acted on. This is done by creating correlation rules and using machine learning techniques to detect anomalies in the data that could indicate a security threat.
While it’s true that SIEM cannot stop threats independently, it can communicate with your other cybersecurity tools to block them or make them harder to find and remove. It can also send them instructions on prioritizing a threat so that it receives the attention it deserves.
Conventional SIEM uses threat profiles and correlation rules to evaluate security data and events. Still, this approach can result in many false positives that bury more urgent incidents. It also needs to consider various sources and contexts that can improve the scrutiny of actions and events.
In contrast, the predictive analytics component of an SIEM platform can use user and entity behavior analysis to monitor the behaviors of individuals and systems in the network. This allows the system to detect lateral movement and other indicators of a security threat. It can also identify critical assets in the network and track their usage over time to see unauthorized access. These capabilities can speed up your incident response and reduce the impact of an internal breach.
In addition to reducing false alerts and improving forensic investigations, SIEM offers reporting features that provide security analysts with business context when handling security alerts. This helps them more effectively interpret and respond to a given security incident. SIEM also simplifies and centralizes security monitoring, allowing teams to monitor their security infrastructure and detect suspicious behavior more quickly.
When selecting a SIEM solution, make sure it can identify and prioritize your organization’s business needs. While many vendors offer pre-configured correlation rules, identifying your priorities and requirements allows you to fine-tune the software to increase detection efficacy and reduce false alerts.
For example, suppose you have a business requirement to prioritize aggregating data related to PII (personally identifiable information). In that case, you can ensure that your SIEM system collects and analyzes this data in real time. This will help you thwart attacks targeting this sensitive data.
You can also analyze logs for evidence of a data breach by searching for traces left behind by hackers. These reports can help you discover when a violation occurred, the systems and data affected, and the hacker’s entry point. These reports can then be used to investigate the incident and improve your business’s security controls. This is especially important as data breaches are more common than ever before and can lead to costly penalties for violations of compliance standards, such as GDPR or CCPA.