Monitoring Quine Streaming Graph using Grafana + InfluxDB
Monitoring tools like Grafana work well with Quine but there are a few things to keep in mind when monitoring data in motion.
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thatDot is transforming cybersecurity with innovative Streaming Graph technology. By merging real-time event stream processing with powerful graph analytics, thatDot offers unparalleled capabilities in threat detection and response, ensuring robust protection against modern cyber threats.
Calculate Risk and Optimize Asset Allocation in Real Time
Asset allocation and risk calculations need to move from batch to real time to free assets and improve compliance. Quine Streaming Graph provides a path.
Create a Quine Icon Library with Python
Add some flair to your Quine streaming graph visualizations while learning about the API at the same time.
Dynamic Duo: Quine & Novelty Detector for Insider Threats
In a big update to the VAST Advanced Persistent Threat blog, we demonstrate an end-to-end Quine plus Novelty Detector workflow.
idFrom(): the simple function that’s key to Quine streaming graph
idFrom() seems like a simple function for generating node IDs but it is the key to Quine's ability to find complex patterns in high volume event streams.
Using Indicators of Behavior (IoB) Analysis for IoT data
Indicator of Behavior (IoB) analysis is extending beyond the cybersecurity domain to offer new value for finance, ecommerce, and especially IoT use cases.
Quine’s Real-time Temporal Event Sequencing Produces New Insights
Quine's standing queries, idFrom + deterministic labelling can be use to efficiently create any subgraph you need (e.g. sequence based) in real time. This makes alerts more timely and root cause analysis more efficient.
Graph Neural Networks for Quine
Quine 1.5 includes support for graph neural network techniques like Node2Vec and GraphSAGE. This post provides an overview and tutorial.