At Synaptect, data collection and analysis is not a drag. And as with the NFVgrid Analytics module, X-Barrier allows you to drill down to the packet level for actionable intelligence without compromising system performance. X-Barrier’s rigorous packet-and-log level data collection is also built for speed – on a single platform to simplify and accelerate data collection and graph-based enrichment. This Big-Data style solution includes all inbound and outbound packets as well as app/system logs. The processed data is cleaned, then utilized by the system as well as being outputted to the UI so that it can be acted upon by system operators.
X-Barrier watches the traffic itself, even down to the PID level, so there are no interoperability issues with legacy equipment and closed-source gear. The solution watches system-generated logs and other data, which makes it fit with limited-capability IoT devices. The analytics end is tailored for optimum results at speed as well. X-Barrier’s all-packet, all-log capacity data gathering is user definable so that analytics gives the level of granularity your intranet needs.
X-Barrier makes extensive use of our prior experience in Big Data analytics to provide a full picture of your network activity. Flow analysis, for example, works on both run-time and day of the week bases simultaneously to better capture flow dynamics. Threshold analytics is also user-definable for each microsegment so tailored responses are possible even for neighboring devices.
X-Barrier adds security features tailored for the monitoring and analysis results of each microsegment. Moreover, unlike a traditional firewall-based intranet perimeter defense, X-Barrier’s reporting and security measures can be engaged instantaneously and automatically. In verticals where regulatory compliance is increasingly couched in terms of response time and adequacy, X-Barrier presents a way forward.
Unlike legacy, hardware based security, X-Barrier adapts dynamically to the changing normal intranet environment. X-Barrier uses a blend of Bandwidth, Flow, and Network analytics applying Machine Learning techniques to constantly increase and maintain the module’s accuracy as conditions change. This is available for each microsegment so whether the device(s) in question needs an alarm or needs quarantining from the intranet - and whether that can change – can now be automated.