Primitive-Based Whitelist for False Positive Prevention
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Solution Overview
Problem
Security products frequently misclassify secure files as insecure, leading to false positives, which can be costly and frustrating for both vendors and customers, and existing file-indexed whitelisting methods fail to prevent recurrence of misclassification upon file modifications.
Innovation Solution
The system creates a whitelist of primitives that identify the source of origin for misclassified files, determining if the source is trustworthy based on the classification of other files from the same origin, and adjusts the security policy to prevent future false positives for files from that source.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If file-indexed whitelisting is used to prevent false positives, then false positive reduction is improved, but reliability deteriorates when files are modified since hash changes cause re-misclassification
Solution Approach 1:
The patent segments the file identification approach from hash-based to primitive-based. Instead of treating the entire file hash as the identifier, it extracts specific primitives (URL, publisher, IP address, digital signature) that can remain stable even when file content changes. This segmentation allows the system to maintain reliability for files from trustworthy sources while adapting to modifications.
Solution Approach 2:
The patent transitions from a single-dimension hash-based identification to a multi-dimensional primitive-based identification system. By considering multiple attributes (URL, publisher, IP address, digital signature) simultaneously, the system creates a more robust identification framework that can handle file modifications while maintaining false positive prevention.
2Measurement precision
If security products perform strict classification to improve security accuracy, then measurement precision is improved, but false positive rate increases leading to customer frustration
Solution Approach 1:
The patent introduces an intermediary mechanism - the primitive-based whitelist system - that sits between the strict security classification and the final file handling. Files from whitelisted primitives receive preferential treatment, allowing the system to maintain strict classification for unknown files while reducing false positives for files from trustworthy sources.
Solution Approach 2:
The patent changes the classification parameters from purely content-based hash analysis to include source-based primitive analysis. By incorporating primitives like URL, publisher, and digital signature as additional classification parameters, the system achieves more accurate and reliable security decisions that reduce false positives.
3Loss of time
If file-specific whitelisting is implemented to reduce false positives, then loss of time is reduced for individual files, but productivity decreases due to manual reporting requirements
Solution Approach 1:
The patent implements preliminary action by proactively identifying and whitelisting files based on their primitives before false positives occur. Instead of waiting for customer reports, the system automatically analyzes file primitives, determines source trustworthiness, and creates whitelists in advance, preventing false positives before they impact productivity.
Solution Approach 2:
The patent enables self-service by allowing the system to automatically identify false positive patterns and whitelist files without requiring manual customer reporting. The system monitors its own classification decisions, detects potential false positives based on primitive analysis, and autonomously adjusts whitelists, eliminating the need for time-consuming manual reporting processes.
Data Source
AI summary
A computer-implemented method for preventing chronic false positives may include (1) whitelisting a file based on a challenge notification that challenges a classification of the file as insecure, (2) obtaining attribute information about the file, (3) identifying, by analyzing the attribute information, a primitive that identifies a source of origin for the file, (4) determining, based on an analysis of files that originate from the source of origin, that the source of origin identified by the primitive is trustworthy, and (5) adjusting, based on the determination that the source of origin identified by the primitive is trustworthy, a security policy associated with the primitive to prevent future false positives for other files that originate from the source of origin. Various other methods, systems, and computer-readable media are also disclosed.