Digital transformation is underway in the business world. IT networks are becoming more sophisticated and complex. Organizations quickly realize that a reactive approach to managing cyber risk is no longer sufficient in today’s digital world.
Security teams now use security analysis tools to get insights from data to detect and inspect threat alarms as they occur.
What is cybersecurity analytics?
Cybersecurity analytics uses data aggregation, attribution, and analysis to find the necessary information for proactive cybersecurity approaches. Traditional security information and event management system (SEIMs), rely on point-in-time testing. This leaves room for error because things change constantly within a network.
Therefore, an assessment of an organization’s cybersecurity position at one time will not reflect the actual day-to-day security efforts. Security analytics uses machine learning to continuously monitor a network, identify changes in traffic or patterns and address threats immediately.
Why is cybersecurity analytics so important?
Cybersecurity analytics is important because It enables IT, security professionals, to take cybersecurity monitoring into their own hands. Security analytics provides visibility into your entire IT ecosystem and allows for faster threat detection and automation of more manual security tasks.
Security analytics tools have many benefits
Security analytics tools offer external threat intelligence as well as the context required to identify correlations between alerts, events or changes. Security analytics tools are able to combine large amounts of data into one location, which allows for rapid detection.
1. Prioritized alerts
Cyber analytics tools can give specific information about potential vulnerabilities and rank alerts, sorted by severity, so security teams can quickly determine what needs to be addressed.
2. Automated threat intelligence
Due to the large amount of data available, Automated Threat Intelligence is extremely useful as it reduces time spent on manual security tasks and improves accuracy, and can be used to help you identify potential vulnerabilities in your network.
3. Proactive incident detection
Security analytics tools combine historical analysis with new security data analysis to detect anomalies in network traffic and user behavior. These patterns may indicate a possible attack or negligence by the user. Security teams can respond to threats proactively.
4. Investigation of forensic incidents improved
It is crucial to prevent similar incidents from occurring in the future by conducting forensic investigations. Security analytics tools can identify the source of the threat, the data or accounts that were compromised, and the severity of the attack. These data can be used to inform future security efforts.
Use cases for cybersecurity analytics
Cybersecurity analytics can also be used by many companies and organizations, such as technology companies, insurance, and rating agencies, compliance auditors, and security teams.
These are the most popular uses of security analytics:
- To identify potential attacks, analyze network traffic
- Detect malicious activity and insider threats
- Forensics and incident response
- Manage third- and fourth-party vendor risks
- Find out which accounts might have been compromised and detect the data exfiltration
Governance, compliance, and risk
- Threat hunting allows you to identify threat indicators