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Lightweight-class Android malicious software fast judging method

A malware, lightweight technology, applied in computer security devices, instruments, electrical digital data processing, etc., can solve problems such as malware, and achieve the effect of improving accuracy

Inactive Publication Date: 2015-07-29
TIANJIN UNIV
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the rapid development of the smartphone market has also brought about a malware problem that is closely related to users

Method used

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  • Lightweight-class Android malicious software fast judging method

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Embodiment Construction

[0016] The technical solution of the present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments.

[0017] The overall idea of ​​the present invention is to adopt a static detection method based on software authority information, firstly train through a large number of samples to obtain a better classification model, then extract authority information from the program to be detected, input the classification model, and obtain the detection result.

[0018] Describe the process of the present invention with a specific embodiment, including the following steps:

[0019] The first stage:

[0020] The first step is to obtain the marked malicious program set A from the Genome project (a "genome project" for the purpose of combating Android-based device malware in this technical field), and collect the normal program set B from the Google electronic market. Each selects 150 samples therefrom to form the sample l...

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Abstract

The invention discloses a lightweight-class Android malicious software fast judging method. According to the method, software samples are collected from different sources, and two software bases including a malicious software base and a benign software base are respectively formed; configuration files of Android program installing files in the two sample bases are respectively obtained; the configuration files are decoded, permission vectors are extracted, and permission sets of each program are obtained; the sample base is subjected to feature extraction to obtain 46 permissions, each sample generates one corresponding 46-dimension binary feature vector; 10 feature vectors with the highest relevancy with the software property are worked out, and each sample feature is subjected to class calibration; classification models are trained for the sets of 10 feature sets; installing files of software to be tested are obtained, and the feature vectors corresponding to the program to be tested are generated; according to the classification models, the feature vectors are used as the input, the software to be tested is classified, and the detection result of the software to be tested is obtained. Compared with the prior art, the lightweight-class Android malicious software fast judging method has the characteristics of high speed and simplicity and can be used as a primary auditing tool for each Android application market.

Description

technical field [0001] The invention relates to various fields such as software detection and network security technology, in particular to a fast malicious software judging method under the Android platform. Background technique [0002] Smartphones are an important carrier of the mobile Internet. With the rapid development of the mobile Internet, the market size of smart phones is also growing. Due to the open source nature of the Android system, software written by any organization or individual can be uploaded to the "app store" for Users download and install it, so it already accounts for 75% of global smartphone shipments. However, the rapid development of the smartphone market has also brought about the problem of malware that is closely related to users. [0003] At present, the methods used in the international research on smartphone malware detection can be mainly divided into two categories: rule-based detection methods and anomaly-based detection methods. Among...

Claims

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Application Information

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IPC IPC(8): G06F21/56
CPCG06F21/563G06F2221/033
Inventor 刘昱张亦弛李海宾李圣龙王映雪方诚
Owner TIANJIN UNIV
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