Jennifer Reif

Cyber Sleuth: Finding Hidden Connections in Cyber Data

Defenders think in lists, but attackers think in graphs. Learn how to map your network's hidden connections and find critical vulnerabilities before they do.

Cyber Sleuth: Finding Hidden Connections in Cyber Data
#1about 6 minutes

Understanding the complexity of modern cybersecurity threats

Cybersecurity involves diverse domains and multi-step attack chains that require compiling data from multiple sources to prevent breaches.

#2about 6 minutes

Why attackers think in graphs, not lists

Attackers exploit interconnected pathways to hop between systems, while defenders often focus on static lists of permissions, creating a strategic disadvantage.

#3about 6 minutes

Modeling connected data with graph databases

Graph databases use nodes, relationships, and labels to create a holistic view of a network, making it easier to surface hidden connections.

#4about 6 minutes

Getting started with Neo4j and the Cypher query language

Learn how to load data into Neo4j using dump files or the APOC library and write basic `CREATE` and `MATCH` queries with the Cypher language.

#5about 7 minutes

Investigating a user's direct and indirect access

A live demo shows how to use Cypher to trace a user's access from direct machine permissions to multi-hop group memberships.

#6about 5 minutes

Visualizing threats with rule-based styling in Bloom

Use Neo4j Bloom to visually explore the graph with natural language queries and apply rule-based styling with algorithms like PageRank to highlight critical assets.

#7about 5 minutes

Analyzing the blast radius of a compromised account

Discover how to find the shortest attack path to a high-value target and visualize the full blast radius of a single compromised account.

#8about 3 minutes

Resources for learning more about Neo4j

Find resources to continue learning, including a GitHub repository with the dataset, Neo4j sandboxes, and the Graph Academy.

#9about 16 minutes

Q&A on graph databases for cybersecurity

The speaker answers audience questions about required skills, tracking malware, and integrating machine learning with graph databases for threat detection.

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Matching moments

An introduction to graph analytics for software systems
02:41 MIN

An introduction to graph analytics for software systems

Data Science on Software Data

Why graph technology was embedded into the Kusto engine
03:20 MIN

Why graph technology was embedded into the Kusto engine

From Tables to Graphs in Minutes: Supercharging Kusto Graph Analytics with AI-Powered Development

AI demo for generating cybersecurity graph models
06:03 MIN

AI demo for generating cybersecurity graph models

From Tables to Graphs in Minutes: Supercharging Kusto Graph Analytics with AI-Powered Development

Understanding graph databases and the Cypher query language
03:28 MIN

Understanding graph databases and the Cypher query language

Putting the Graph In GraphQL With The Neo4j GraphQL Library

Representing complex data with knowledge graphs
03:48 MIN

Representing complex data with knowledge graphs

Large Language Models ❤️ Knowledge Graphs

Understanding the fundamentals of graph databases
04:34 MIN

Understanding the fundamentals of graph databases

Martin O'Hanlon - Make LLMs make sense with GraphRAG

Why developers make basic cybersecurity mistakes
02:26 MIN

Why developers make basic cybersecurity mistakes

Don't Be A Naive Developer: How To Avoid Basic Cybersecurity Mistakes

Querying connected data with Cypher in Neo4j Browser
06:22 MIN

Querying connected data with Cypher in Neo4j Browser

Putting the Graph In GraphQL With The Neo4j GraphQL Library

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