Malicious software clustering method expressed based on TLSH feature
US10289848B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 10, 2017 |
| Grant date | May 14, 2019 |
| Priority date | — |
| Expiry date | Jul 10, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2221/033
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
This invention public a kind of malicious software clustering method expressed based on TLSH feature, which belongs to the analysis and test area of malicious software. Firstly, the Cuckoo Sandbox is used to analyze the malicious software to acquire three kinds of character string features, which are the static feature of the software, resource assess record during operation and API; And then the character strings are disassembled, filtered and sorted and the TLSH algorithm is used to compress them into three groups of feature values with size of 70 characters; Finally the OPTICS algorithm is utilized to realize the automatic classification on the malicious software family. This invention adopts unsupervised learning methods, which does not need the manual tab for the training in advance. The features which are extracted are compressed and expressed by using the TLSH. Under the situation that the feature is not lost, the data dimension is largely lowered and the clustering speed is improved; Through adoption of OPTICS clustering algorithm based on the density, it can not only recognize the cluster of any shape or any number but also largely reduce the influence of the input paramet…
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.