Security

Cybersecurity Analytics

In the ever-evolving realm of cybersecurity, where digital threats mutate at an alarming rate, Cybersecurity Analytics stands as the linchpin fortifying digital defenses.

What Is Cybersecurity Analytics?

Cybersecurity Analytics involves aggregating data to collect evidence, build timelines, and analyze capabilities to design a proactive cybersecurity strategy that detects, analyzes, and mitigates cyber threats. Diverging from the constraints of a traditional Security Information and Event Management (SIEM) system, cybersecurity analytics embraces a holistic approach, considering the network as a whole, spotting trends and changes that might elude a singular snapshot.

New Technology Can Bring Greater Agility, Scalability and Efficiency

Cybersecurity Analytics for Businesses

As cyber threats become more sophisticated, the need for proactive defense becomes paramount. Cybersecurity analytics, employing machine learning (ML) and behavioral analytics, monitors network activities, identifies changes, and empowers organizations to address threats in real-time. This transition from protection to detection is a game-changer, allowing businesses to thwart potential threats before they impact systems. Moreover, it provides a unified view of the enterprise, ensuring comprehensive oversight of network activities and device configurations.

Benefits of Cybersecurity Analytics Tools

Prioritized Alerts: Cybersecurity analytics enables the prioritization of alerts, reducing time spent on false or less critical notifications.
Automated Threat Intelligence: Through ML tools, cybersecurity analytics automates threat intelligence, detecting, categorizing, and filing away threats for future identification.
Proactive Incident Detection: By adopting a proactive strategy, cybersecurity analytics provides a global view of current and potential future threats, offering advanced intelligence profiles.

SIEM vs. Cybersecurity Analytics

While SIEM systems excel in collecting log data and understanding the current state of a network, they may struggle with the demands of continuous integration/continuous deployment (CI/CD). Cybersecurity analytics, leveraging cloud infrastructure, efficiently manages the intense storage and processing needs associated with CI/CD.

Big Data Security Analytics

Governance regulations necessitate processing extensive data swiftly to ensure system security and minimize cyber risks. Big data security analytics automates the collection and analysis of information from various endpoints, user behaviors, and subnetworks. Fortinet's management and analytics solution exemplify this, offering robust network orchestration, threat response, and automation.

FAQs

What is the need for cybersecurity analytics?

With cybersecurity analytics, networks can detect threats before they impact systems, managing large data volumes to identify and mitigate potential threats.

What are the benefits of cybersecurity analytics tools?

Benefits include prioritized alerts, automated threat intelligence, proactive incident detection, and improved forensic incident investigation.

What are the most common use cases of cybersecurity analytics?

Common use cases encompass analyzing traffic, monitoring user behavior, detecting threats, identifying data exfiltration attempts, monitoring remote and internal employee activity, detecting insider threats, identifying compromised accounts, demonstrating compliance, investigating incidents, and detecting improper use of user accounts.