Security Threat Prediction via Collaborative Filtering
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Solution Overview
Problem
Traditional methods for protecting computing resources from security threats are primarily retroactive and do not predict specific security attacks, lacking proactive measures to prevent them.
Innovation Solution
The implementation of systems and methods that perform non-collaborative and collaborative filtering calculations, combined with machine learning algorithms, to predict security threats and identify vulnerable targets, filtering predictions to provide customized and insightful threat information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional retroactive security methods (antivirus software, firewalls) are used, then computing resources are protected from security threats, but the system cannot predict specific security attacks before they occur
Solution Approach 1:
The patent applies preliminary action by using collaborative filtering calculations to predict security attacks before they occur. The system analyzes patterns from historical attack data and similar targets to generate predictions of future attacks, allowing security teams to take preventive measures before the actual attacks happen, rather than merely responding after detection.
2Measurement precision
If collaborative filtering calculations are performed to generate customized predictions, then prediction accuracy for specific targets improves, but the complexity of the system increases
Solution Approach 1:
The patent uses an intermediary approach by introducing a filtering mechanism that processes the outputs of collaborative filtering calculations. The system filters and prioritizes predictions based on confidence scores and relevance metrics, making the complex calculation results more manageable and actionable without requiring simplification of the underlying collaborative filtering algorithm itself.
3Reliability
If both non-collaborative and collaborative filtering calculations are performed, then comprehensive security predictions are generated, but the computational resources and time required increase
Solution Approach 1:
The patent applies partial action by implementing a two-stage filtering process where non-collaborative filtering provides a baseline set of predictions, and collaborative filtering is then applied selectively to enhance specific predictions. The system does not fully process all possible predictions through both methods, but rather uses the combination strategically to achieve comprehensive coverage while managing computational resources efficiently.
Data Source
AI summary
A computer-implemented method for predicting security threats may include (1) predicting that a candidate security target is an actual target of a specific security attack according to a non-collaborative-filtering calculation, (2) predicting that the candidate security target is an actual target of a set of multiple specific security attacks, including the specific security attack, according to a collaborative filtering calculation, (3) filtering, based on the specific security attack also being predicted by the non-collaborative-filtering calculation, the specific security attack from the set of multiple specific security attacks predicted by the collaborative filtering calculation, and (4) notifying the candidate security target to perform a security action to protect itself from another specific security attack remaining in the filtered set of multiple specific security attacks based on an analysis of the filtered set of multiple specific security attacks. Various other methods, systems, and computer-readable media are also disclosed.