Using Deep Learning and Graph Analysis against Cyberattacks


Business Intelligence & Analytics

Date and time

Thursday, 18. October 2018., 16:40


Hall C



If an IT network is modelled as an abstract graph with network devices represented as nodes in the graph, and connections between the components represented as edges, you can already derive interesting information from the resulting topological structure. If in addition the network traffic on this graph is captured, machine learning algorithms can be used to identify anomalous behaviour caused by network intruders.In this paper we'll look at the fundamentals of graph analytics and how these technologies can be used to detect anomalies in general. We will show how graph analysis can be combined with machine learning using the integration between Oracle Big Data Spatial and Graph and R through the OAAgraph package. And finally, we will describe a project in which network data was analysed by means of a deep learning engine to detect suspicious network activity.

Lecture details

Type: Lecture
Level of difficulty: General
Experience Level: No experience
Desirable listeners function: Developers , System Analist , Designer
Group of activity: Business Intelligence & Analytics

About speaker

Best Sponsor

Better Sponsor

Media Sponsor

The conference is organized by the Croatian Association of Oracle users. More about the association can be found at

Follow us on Twitter

Keep yourself up to date with all updates!

Follow us on Facebook