Picking the Right Database Tech for Cybersecurity Defense
Modern cybersecurity technologies produce massive quantities of data, which requires rethinking how to store and manage all the different types of information being generated. Many cybersecurity platforms are increasingly relying on one of two database technologies — graph or streaming databases — to efficiently represent and query databases of threat indicators, asset inventories, and other critical cybersecurity information.
Graph databases allow for the properties and relationships of various objects — whether threat groups, devices on the network, or software vulnerabilities — to be connected and searchable. Streaming database technology allows real-time threat data and status updates to be efficiently processed and stored. Both technologies help companies move beyond the lists used by defenders in the past to track everything and to do so in real time.
"All of us who work in this field have long lamented the difficulty of defending against cyber intruders, but there hasn't been a single moment of change, just a gradual increase in complexity over time," says Irene Michlin, staff engineer and application security lead at Neo4j, a graph-database provider. "We've reached that tipping point in difficulty, where data has become evermore interconnected with 'many-to-many' relationships."
The changing nature of data collection and use in cybersecurity has necessitated moving to other approaches to storing and processing data. Social networks of threat actors, connected assets in defenders' networks, and indicators of compromise are some types of data where the relationships among the elements of the dataset is extremely important.
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