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Cyber Analytics is all about those numbers and their organization to launch a search and analysis process that results in a solution.
FREMONT, CA: Cyber analytics, also known as security analytics, is the process through which computer scientists analyze data to develop, implement, and manage digital security. It is accomplished by monitoring the network and determining when it was compromised. Ideally, the goal should be to avert such attacks in the first place. However, security analytics is more than a technology or system; it is a way of thinking about cyber security proactively. It entails analyzing data from a variety of sources to create and maintain security measures for the network.
Algorithms, behavioral analytics, machine learning, statistical analysis, and other types of research are used to solve cyber security challenges and mitigate threats in ways that traditional security measures cannot. While these analytics are frequently likened to indicators of compromise (IoCs), the difference is in applying analysis to discover possible and unknown threats that signature-based IoCs overlook.
Sources and Tools for Cyber Analytics
Numerous data sources are available for the cyber security analytics strategy, including cloud resources, user data obtained from endpoints, and logs from network security appliances. These appliances could be firewalls, intrusion prevention systems, or intrusion detection systems. Additionally, logs from identity and access management systems, network traffic and its patterns, threat intelligence, geolocation data, Ethernet and USB, mobile devices and storage media connected through Wi-Fi, antivirus programs, and business-specific apps are sources.
Use Cases for Cyber Analytics
Users can implement cyber analytics for several use cases, ranging from monitoring user behavior to network traffic analysis. Several of the most common usage scenarios include the following:
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