Virus Detection Using Preset Bloom Filter Bit Indices
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Solution Overview
Problem
Current virus detection methods face challenges due to the large memory resources required to store hash digests of hundreds of millions of viruses, leading to inefficiencies and reduced accuracy in identifying low-activity virus files.
Innovation Solution
The use of a preset Bloom filter to compute bit indices of a file to be detected, where parameter values corresponding to bit indices of known virus files are set to a preset value, allowing for efficient determination of whether the file is a virus file without occupying large memory resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If hash digests of all virus files are stored in memory for detection, then virus detection accuracy is improved, but memory resources are excessively occupied
Solution Approach 1:
The patent extracts only the essential information from virus files (their hash digests) and stores them in a compressed Bloom filter structure, rather than storing complete virus file data. This extraction reduces memory requirements while preserving the ability to accurately identify virus files through hash matching.
Solution Approach 2:
The patent changes the storage parameter from complete virus file data to compressed Bloom filter structures that store only hash digest information. This parameter transformation enables memory-efficient storage while maintaining virus detection capability through the Bloom filter's probabilistic matching mechanism.
2Adaptability or versatility
If a comprehensive virus database is used for detection, then detection coverage is improved, but processing efficiency for low-activity viruses deteriorates
Solution Approach 1:
The patent implements a dynamic virus detection mechanism that adapts to different virus types and activity levels. The Bloom filter structure allows efficient querying for known viruses while the system can dynamically update its database, enabling it to maintain high detection coverage for both active and low-activity viruses without sacrificing processing efficiency.
Data Source
AI summary
Method apparatus, storage medium, and electronic device for virus detection are provided. The method includes: computing a target hash digest of a file to be detected, and based on the hash functions of a preset Bloom filter and the target hash digest, computing the bit indices of the file to be detected in the preset Bloom filter; the bit indices of each known virus file in the preset Bloom filter are determined based on a hash digest of the corresponding known virus file, and all of parameter values corresponding to the bit indices of each known virus file in the preset Bloom filter are a preset value; determining whether the file to be detected is a virus file based on the preset Bloom filter and the corresponding bit index of the file to be detected.