Combating cyber attack with Apache AGE's link analysis
Bitnine Global Marketing team
Mon Jul 08 2024

Cybersecurity Background
In our increasingly connected world, the internet has transformed how we interact, work, and access information, bringing immense convenience. However, this digital revolution comes with challenges, especially in cybersecurity. As we depend more on technology, the need to protect sensitive data and counteract cyber threats becomes crucial.
Cybersecurity is all about safeguarding computer systems, networks, and data from theft, damage, or unauthorized access. A key part of this is network intrusion detection, which acts like a digital watchdog. It constantly monitors network traffic for any signs of suspicious activities, such as hacking attempts or unauthorized entries, aiming to catch and address these threats early, preventing harm to networks or data.
In essence, cybersecurity and network intrusion detection are vital in our tech-driven world, ensuring our digital safety and resilience against ever-evolving cyber threats.
Data Overview
In cybersecurity, graph analysis is essential. To illustrate this, we use the CIDDS-001 dataset, specifically designed for network intrusion detection. This dataset simulates a small business environment with clients and servers, including email and web servers. It captures network traffic flow data to help evaluate how different intrusion detection systems perform in identifying network attacks.

Figure1. Graph Modeling
Graph analysis involves transforming relational data into a graph format, consisting of nodes (points) and edges (connections)
There are two main types of graphs:
Homogeneous Graphs: These have nodes and edges of a single type, like user nodes connected by 'follow' edges in social networks
Heterogeneous Graphs: These contain multiple types of nodes and edges, like in e-commerce networks where interactions between users and items are tracked through different types of connections such as 'buy,' 'cart,' and 'view.'
Using the CIDDS-001 dataset, we create a graph for network flow analysis, including nodes representing start and end points in the network, and edges of various types like 'benign,' 'dos,' 'portscan,' 'pingscan,' and 'bruteforce.' Each node and edge is detailed with information such as ports, packet sizes, and timestamps, crucial for quick and precise responses in cybersecurity.
Cypher Query with Analysis Scenario
Now, let's explore how Apache AGE's graph analysis capabilities, particularly through Cypher queries, can be used in cybersecurity. We'll look at three scenarios demonstrating the power and flexibility of Cypher queries in analyzing network data.

Figure2. Graph Query with Condition
Figure 2 showcases a Cypher query focused on identifying network packets larger than a certain size. This is a prime example of the 'condition' function in Apache AGE, crucial for pinpointing specific scenarios. Here, the query filters out packets larger than 10 units, helping analysts spot potential anomalies or threats in network traffic. This function isn't limited to just packet size; it can be tailored to various criteria, making it a versatile tool for cybersecurity analysis.

Figure3. Multi-path Search with Union Query
In Figure 3, we see a union query in Apache AGE, demonstrating its ability to handle complex, multi-path searches. This is particularly useful in scenarios where you need to analyze data across different types of connections, like 'eg_portscan' and 'eg_pingscan.' Apache AGE also enhances this analysis with visual aids, like representing the weight of packets through the thickness of edges in the graph, making it easier to interpret the data visually.

Figure4. Bi-directional Path Search
The final example, illustrated in Figure 4, is a bi-directional path search. This Cypher query uncovers one-to-many relationships between nodes, providing a detailed view of network interactions and potential security incidents. It's particularly adept at revealing complex patterns and relationships that might be missed with traditional analysis methods. By tracing paths involving different types of nodes and connections, this query helps in identifying multi-step attack patterns and potential sources or targets of cyberattacks.
Conclusion
We've explored the essentials of cybersecurity, examined the CIDDS-001 dataset for cyber intrusion analysis, and delved into the dynamic use of Cypher queries in data analysis. The journey underscores the immense value of graph analysis in cybersecurity, offering profound insights and robust tools to combat digital threats.
Apache AGE stands out with its user-friendly approach to graph analysis. The use of Cypher queries, known for their power and intuitiveness, simplifies complex data analysis. This language enables cybersecurity experts to craft detailed queries, uncovering complex attack patterns and suspicious network activities, crucial for enhancing threat detection and response capabilities.
Graph visualization is key to making intricate cybersecurity data more understandable and actionable. By graphically representing network nodes, edges, and their attributes, it becomes easier for analysts to decode complex structures, spot anomalies, and respond swiftly to potential threats. This visual approach aids in proactive security measures, allowing teams to trace unusual activities, map out attack routes, and pinpoint potential sources of cyber threats, thereby improving overall security awareness and decision-making.
Another significant aspect of Apache AGE's graph analysis is the labeled property graph model. This approach enriches nodes and edges with detailed metadata, capturing essential information about cyber incidents. Such rich data representation not only aids in precise threat categorization but also supports thorough post-incident analysis. This helps organizations learn from past experiences, enhancing their defensive strategies against future cyber threats.
In conclusion, Apache AGE presents a powerful suite of tools for cybersecurity professionals, significantly bolstering their ability to detect, investigate, and neutralize cyber threats. The combination of easy-to-use Cypher queries and effective graph visualization positions Apache AGE as an indispensable asset in contemporary cybersecurity operations. By adopting graph analysis, organizations can effectively stay ahead of cyber adversaries, protect sensitive data, and maintain the integrity of their digital ecosystems.