McAfee‘s patent describes a computing apparatus and method for detecting malware. It involves feature-based analysis, assigning malware reputations, and adjusting these reputations using a bucketized reputation modifier table, ultimately leading to security actions based on the analysis results. GlobalData’s report on McAfee gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on McAfee, was a key innovation area identified from patents. McAfee's grant share as of June 2024 was 68%. Grant share is based on the ratio of number of grants to total number of patents.
Malware detection using feature-based analysis and reputation adjustment
The patent US12045349B2 outlines a computer-implemented method for detecting computer malware through a systematic approach that involves analyzing and categorizing objects based on shared features. The method begins with "bucketizing" analysis results, which entails grouping data into buckets according to specific characteristics. For each bucket, probabilistic curves are computed to represent the likelihood of an object being malicious. The method further includes establishing feature analysis thresholds for these curves, performing a feature analysis on the object in question, and calculating a malware score. This score is then compared to the relevant threshold, leading to a decision on whether to take a malware action against the object.
Additionally, the patent details various aspects of the bucketizing process, including the computation of URL and IP address reputations, as well as certificate reputations for the objects analyzed. The probabilistic curves generated do not consider the severity of maliciousness but rather indicate the probability of an object being associated with malicious activity. The method can be executed on cloud or backend services, and the patent also encompasses tangible, nontransitory computer-readable media that store executable instructions for implementing this malware detection process. The claims emphasize the flexibility of the method, allowing for various types of reputational data to be integrated into the analysis, thereby enhancing the overall effectiveness of malware detection.
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