Find out in this report how the two Network Monitoring Software solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
Cisco Secure Network Analytics is a highly effective network traffic analysis (NTA) solution that enables users to find threats in their network traffic even if those threats are encrypted. It turns an organization’s network telemetry into a tool that creates a complete field of vision for the organization’s administrators. Users can find threats that may have infiltrated their systems and stop them before they can do irreparable harm.
Cisco Secure Network Analytics Benefits
A few ways that organizations can benefit by choosing to deploy Cisco Secure Network Analytics include:
Cisco Secure Network Analytics Features
Some of the many features that Cisco Secure Network Analytics offers include:
Reviews from Real Users
Cisco Secure Network Analytics is a solution that stands out even when compared to many other comparable products. Two major advantages that it offers are the way that it enables users to define the threshold at which the solution will issue a warning to administrators and the predefined alerts that it offers straight out of the box.
Gerald J., the information technology operations supervisor at Aboitiz Equity Ventures, Inc., writes, “StealthWatch lets me see the ports running in and out and the country. It has excellent reporting, telemetry, and artificial intelligence features. With the telemetry, I can set thresholds to detect sudden changes and the alarms go through the PLC parts. I can see all the ports running on that trunk.”
A senior security engineer at a tech services company, says, “Cisco Stealthwatch has predefined alerts for different types of security issues that might happen in the network. Whether it's PCs or servers that are used for botnets or Bitcoin mining we receive the alerts automatically. This functionality is what we receive from the solution out of the box.”
Splunk User Behavior Analytics is a behavior-based threat detection is based on machine learning methodologies that require no signatures or human analysis, enabling multi-entity behavior profiling and peer group analytics for users, devices, service accounts and applications. It detects insider threats and external attacks using out-of-the-box purpose-built that helps organizations find known, unknown and hidden threats, but extensible unsupervised machine learning (ML) algorithms, provides context around the threat via ML driven anomaly correlation and visual mapping of stitched anomalies over various phases of the attack lifecycle (Kill-Chain View). It uses a data science driven approach that produces actionable results with risk ratings and supporting evidence that increases SOC efficiency and supports bi-directional integration with Splunk Enterprise for data ingestion and correlation and with Splunk Enterprise Security for incident scoping, workflow management and automated response. The result is automated, accurate threat and anomaly detection.
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