A Study on The behavior-based Malware Detection Signature

被引：0

作者：

Oh, Sungtaek ^{[1
]}

Go, Woong ^{[1
]}

Lee, Taejin ^{[1
]}

机构：

[1] KISA, R&D Secur Team 1, Seoul, South Korea

来源：

ADVANCES ON BROAD-BAND WIRELESS COMPUTING, COMMUNICATION AND APPLICATIONS | 2017年 / 2卷

关键词：

android; malware; static analysis; dynamic analysis; detection; malicious signature;

D O I：

10.1007/978-3-319-49106-6_66

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

As smartphone are becoming more common, services using smartphones are becoming more pervasive too. Among them, as mobile banking transactions are increasing, payment fraud is also rapidly increasing. These services handle sensitive information, such as users' personal information and payment information, but as they have several security vulnerabilities, they are attacked by malicious apps. This paper proposes a method of deriving malicious app detection signatures based on the behavior information, obtained by analyzing malicious apps collected through several application distribution channels, and these signatures will be used for analysis of variants of malicious apps and development of rule-based malicious app detection systems.

引用

页码：663 / 670

页数：8