Attack Graph Analysis for Multi-Stage Network Intrusions
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Solution Overview
Problem
Existing intrusion detection systems struggle to effectively detect and mitigate complex, advanced persistent threats (APT) involving multiple phases and varied techniques, as they often rely on signature-based methods that are ineffective against unknown attacks and lack comprehensive network analysis.
Innovation Solution
A computer-implemented method using similarity matrices and attack graphs to analyze security alerts, generating different perspectives (one-to-one, many-to-one, one-to-many, many-to-many) to identify patterns and classify attacks, allowing for targeted mitigation actions based on attack graph classifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If signature-based intrusion detection systems are used to detect attacks, then known attacks can be effectively identified, but new types of attacks cannot be detected due to unknown signatures
Solution Approach 1:
The patent segments the attack detection process into multiple similarity matrices, each focusing on different aspects of attack behavior (e.g., source-destination pairs, temporal patterns, protocol characteristics). This segmentation allows the system to analyze attacks from multiple perspectives simultaneously, improving both precision for known attacks and adaptability for new attacks by comparing against diverse behavioral patterns rather than relying on a single signature database.
Solution Approach 2:
The patent transitions from traditional signature-based detection to a multi-dimensional similarity analysis approach. By generating multiple similarity matrices that capture different dimensions of network behavior (spatial, temporal, protocol-level), the system adds dimensional depth to attack detection, enabling it to identify both known and novel attacks through pattern similarity across multiple dimensions rather than relying solely on predefined signatures.
2Reliability
If multiple similarity matrices are generated using different similarity functions to analyze security alerts, then comprehensive attack pattern recognition is achieved, but system complexity increases
Solution Approach 1:
The patent merges multiple similarity matrices into a unified attack graph structure that integrates information from different similarity functions. By combining the results of multiple similarity analyses into a single coherent representation, the system achieves comprehensive attack pattern recognition while managing complexity through integrated visualization and analysis rather than treating each matrix independently.
Solution Approach 2:
The attack graph serves as an intermediary structure that mediates between multiple similarity matrices and the final detection decisions. This intermediary layer consolidates the complex output from multiple similarity functions into a manageable format, allowing the system to leverage diverse similarity analyses without directly managing their individual complexities in the decision-making process.
3Difficulty of detecting and measuring
If attack graphs are generated from multiple similarity matrices to represent sets of security alerts, then complex APTs can be identified, but processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary actions by pre-computing and storing similarity matrices for different attack dimensions before generating attack graphs. By preparing these similarity relationships in advance and organizing them into structured matrices, the system reduces the computational burden during actual attack detection, enabling faster generation of attack graphs even for complex APT scenarios.
Solution Approach 2:
The patent implements dynamic attack graph generation that adapts to the specific characteristics of incoming security alerts. Rather than generating complete attack graphs for all possible alert combinations, the system dynamically constructs graphs only for relevant alert sets identified through the similarity matrices, reducing processing time while maintaining detection capability for complex attacks.
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AI summary
A computer-implemented method of protecting a network is provided. The method receives security alert data from one or more intrusion detection systems. The security alert data comprises a plurality of security alerts relating to the network. The method generates a plurality of similarity matrices from the security alert data. Each similarity matrix is generated using a different respective similarity function and indicates a respective similarity between each of the security alerts according to that similarity function. The method generates one or more attack graphs from the plurality of similarity matrices. Each attack graph represents a respective set of security alerts, wherein a similarity between each of the security alerts in the set, according to at least one of the similarity matrices, is above a predefined threshold. The method causes one or more predetermined actions to be taken with respect to the network to mitigate a respective attack represented by each of the attack graphs.