信息网络安全 ›› 2016, Vol. 16 ›› Issue (10): 80-88.doi: 10.3969/j.issn.1671-1122.2016.10.013
• • 上一篇
收稿日期:
2016-09-01
出版日期:
2016-10-31
发布日期:
2020-05-13
作者简介:
作者简介: 林佳萍(1991—),女,山东,硕士研究生,主要研究方向为网络安全、移动安全;李晖(1968—),男,河南,教授,博士,主要研究方向为密码学、无线网络安全、云计算安全、信息论与编码。
Dalvik字节码语义丰富,包含了类、方法和指令。类信息可以用来验证应用程序的行为。基于控制和数据流的详细分析,具有洞察危险的功能,如隐私泄露和电话服务误用[11,23]。控制流和数据流的分析有利于重建字节码,去除混淆码[24],如抵消无效琐碎的转化技术的影响。
为了抵抗PETSAS[40]提出的静态启发式,安卓模拟器很容易被我们修改。移动设备的标识符,如IMEI和IMSI,在Android模拟器上都可配置。通过查看电话管理服务在Android模拟器的源代码,通过代码分析,可以找到现代设备模拟的地方,作为QEMU[41]部分实现。因此,IMEI、IMSI以及其他功能可以进行修改,使模拟器类似于一个真实的设备。通过修改建Android模拟器加载的属性,在安卓模拟器源代码的build.prop文件上定义这些属性,应用可以很容易被欺骗。
4)当应用程序调用隐私信息或发送短信拨打电话时,要小心和注意。
基金资助:
Received:
2016-09-01
Online:
2016-10-31
Published:
2020-05-13
摘要:
随着无线通信技术的发展,智能手机已经成为人们身边必不可少的移动设备,与人们的信息交流与娱乐生活息息相关,但是手机上安装的软件可能会给用户带来潜在的危险。目前,80%以上的智能手机采用的是安卓操作系统,然而安卓恶意软件数量呈现爆炸式增长,各种恶意行为层出不穷,对用户的安全构成了极大的威胁。智能手机上用户的隐私泄露和财产安全问题亟待解决,因此对安卓系统上的恶意软件进行有效准确的检测具有非常重要的意义。文章调查了安卓恶意软件的现状和危害,介绍了恶意软件的分类和特征,分析了恶意软件的权限和行为,总结了恶意软件的渗透和隐身技术,然后提供了恶意软件检测可采用的工具,研究了目前的检测方法,分析了现在的挑战和提出了应对方法,比较了几种机器学习的恶意软件分类方法,最后对未来恶意软件的检测方向进行了展望,对减轻恶意软件的危害提出了建议。
中图分类号:
林佳萍, 李晖. 安卓恶意软件检测研究综述[J]. 信息网络安全, 2016, 16(10): 80-88.
Jiaping LIN, Hui LI. Review of Android Malware Detection[J]. Netinfo Security, 2016, 16(10): 80-88.
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