BRIDEMAID: An Hybrid Tool for Accurate Detection of Android Malware

被引：47

作者：

Martinelli, Fabio ^{[1
]}

Mercaldo, Francesco ^{[1
]}

Saracino, Andrea ^{[1
]}

机构：

[1] CNR, Ist Inforrnat & Telemat, Pisa, Italy

来源：

PROCEEDINGS OF THE 2017 ACM ASIA CONFERENCE ON COMPUTER AND COMMUNICATIONS SECURITY (ASIA CCS'17) | 2017年

基金：

欧盟地平线“2020”;

关键词：

D O I：

10.1145/3052973.3055156

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents BRIDEMAID, a framework which exploits an approach static and dynamic for accurate detection of Android malware. The static analysis is based on n-grams matching, whilst the dynamic analysis is based on multi-level monitoring of device, app and user behavior. The framework has been tested against 2794 malicious apps reporting a detection accuracy of 99,7% and a negligible false positive rate, tested on a set of 10k genuine apps.

引用

页码：899 / 901

页数：3

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