This required additional development of a tensor library that worked in the context of InSight2 as well as the development of a dashboard that could run the algorithm and display the results in meaningful ways. RED Alert was developed as part of a greater project, InSight2, that provides several different network monitoring dashboards to aid network operators. In both cases, RED Alert was able to detect suspicious events and identify the root cause of the behavior from a sole IP. RED Alert is showcased on two network monitoring examples, packet loss detection and botnet detection, comparing results to DenseAlert. The tensors are built on-the-fly in streaming data, filtering data to only consider the parameters deemed anomalous in previous granularity levels. The Monit Telegraf Plugin collects metrics and status information about local processes, remote hosts, file, file systems, directories and network interfaces. host country), and events detected as anomalous in lower spaces are tracked down to higher granular data (e.g. That is, network traffic is first modeled at low granular data (e.g. This is done through the use of network parameters that are structured in a hierarchical fashion. Drawing from RED Alert, we developed an algorithm called RED Alert that uses recursive filtering and expansion to handle anomaly detection in large tensors of positive and negative valued data. However, from experimentation, DenseAlert fails on larger datasets. DenseAlert identifies events anomalous events in tensors through quick detection of dense sub-tensors in positive-valued tensors. Tensor-based network monitoring methods have been explored in recent years through work at Carnegie Mellon University through their algorithm DenseAlert. This increase in dimensionality lends itself to tensor-based analysis of network data as tensors are arbitrarily sized multi-dimensional objects. Network traffic has two directional flows, north-south and east-west. Network traffic, also called data traffic, is broken down into data packets and sent over a network before being reassembled by the receiving device or computer. As networks become larger and more complex, the data becomes more complex with increased size and more variables. Network traffic is the amount of data moving across a computer network at any given time. To join the Magic Network Monitoring Discord channel, click the button below, then scroll down the left side navigation menu, and select Products > Magic Network Monitoring. Network monitoring systems are important for network operators to easily analyze behavioral trends in flow data. Cloudflare’s Discord server has a channel that’s built around configuring, troubleshooting, and providing feedback on Magic Network Monitoring.
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