基于Android的手机恶意代码检测与防护技术

doi:10.16180/j.cnki.issn1007-7820.2019.06.011

Abstract

Abstract:

With the development of modern communication technology and the development of mobile terminal,Android system breeding a lot of malicious code, due to its own open source.In order to satisfy the requirement of the modern mobile secure, a professional malicious code detection model based on SVM was designed in this paper, realizing a malicious code detection and protection system. The system had been tested by Android mobile phone, which provided better detection accuracy and low false negative rate of malicious code.

Key words: mobile phone secure, Android, malicious code detection, SVM, depth detection

CLC Number:

TP311

YE Zi,LI Ruofan. Malicious Code Detection and Protection Technology of Mobile Phone Based on Android[J].Electronic Science and Technology, 2019, 32(6): 54-57.

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References 16

[1]	温敏, 艾丽蓉, 王志国 . Android智能手机系统中文件实时监控的研究与实现[J]. 科学技术与工程, 2009,9(7):1716-1719.
	Wen Min, Ai Lirong, Wang Zhiguo . Research and implementation of real-time file monitoring in android smartphone system[J]. Science and Technology and Engineering, 2009,9(7):1716-1719.
[2]	李多晓 . 基于移动通信网络的智能终端信息安全设计与实施[D]. 北京:北京邮电大学, 2012.
	Li Duoxiao . Design and implementation of information security for intelligent terminal based on mobile communication network[D]. Beijing:Beijing University of Posts and Telecommunications, 2012.
[3]	韩超, 梁泉 . Android系统原理及开发要点详解[M].北京: 电子工业出版社, 2010.
	Han Chao, Liang Quan. Android system principle and key points for development[M]. Beijing: Electronics Industry Press, 2010.
[4]	朱圣军, 刘功申, 罗俊 , 等. 智能手机病毒与信息安全[J].信息安全与通信保密, 2011(5):96-97.
	Zhu Shengjun, Liu Gongshen, Luo Jun , et al. Smart phone virus and information security[J].Information Security and Communication Confidentiality, 2011(5):96-97.
[5]	陈鸣, 柏逢明 . 数字音频中同时嵌入鲁棒水印和脆弱水印的算法研究[J]. 长春理工大学学报:自然科学版, 2012,35(4):164-166.
	Chen Ming, Bai Fengming . Algorithms for embedding robust and fragile watermarks in digital audio[J]. Journal of Changchun University of Technology:Natural Science Edition, 2012,35(4):164-166.
[6]	苑冰泉 . Android进程间通信机制Binder的分析与对比研究[D]. 南京:东南大学, 2014.
	Yuan Bingquan . Analysis and comparison of Android interprocess communication mechanism Binder[D]. Nanjing:Southeast University, 2014.
[7]	Felt A P, Chin E, Hanna S, et al. Android permissions demystified [C].Boston:Proceedingsof the 18 ^th ACM Conference on Computer and Communications Security,ACM , 2011.
[8]	王志强, 张玉清, 刘奇旭 , 等. 一种Android恶意行为检测算法[J]. 西安电子科技大学学报, 2015,42(3):8-14.
	Wang Zhiqiang, Zhang Yuqing, Liu Qixu , et al. An Android malicious behavior detection algorithm[J]. Journal of Xidian University, 2015,42(3):8-14.
[9]	李根 . Android系统恶意代码检测技术研究[D]. 哈尔滨:哈尔滨工业大学, 2014.
	Li Gen . Research on Android code malware detection system[D]. Harbin: Harbin Institute of Technology, 2014.
[10]	张文 . 基于Android的恶意程序原理分析及一种检测工具的实现[D]. 北京:北京大学, 2012.
	Zhang Wen . Principle analysis of malicious programs based on Android and implementation of a detection tool[D]. Beijing:Peking University, 2012.
[11]	刘阳 . 应用随机森林与神经网络算法检测与分析Android应用恶意代码[D]. 北京:北京交通大学, 2015.
	Liu Yang . Detection and analysis of Android application malicious code using random forest and neural network algorithm[D]. Beijing:Beijing Jiaotong University, 2015.
[12]	桂佳平, 周雍恺, 沈俊 , 等. 基于智能手机恶意代码防范模型的研究[J]. 计算机技术与发展, 2010,20(1):163-166.
	Gui Jiaping, Zhou Yongkai, Shen Jun , et al. Research on malicious code prevention model based on smartphone[J]. Computer Technology and Development, 2010,20(1):163-166.
[13]	李晓光 . Android软件恶意行为静态检测技术研究[D]. 哈尔滨:哈尔滨工程大学, 2015.
	Li Xiaoguang . Android software malicious behavior static detection technology[D]. Harbin:Harbin Engineering University, 2015.
[14]	吕晓庆 . Android软件动态行为监测系统的设计和实现[D]. 北京:北京邮电大学, 2013.
	Lv Xiaoqing . Design and implementation of Android software dynamic behavior monitoring system[D]. Beijing:Beijing University of Posts and Telecommunications, 2013.
[15]	高仁智, 尚丽辉, 涂煊 . 基于Android的环境监控系统的软件开发[J]. 电子科技, 2017,30(1):115-118.
	Gao Renzhi, Shang Lihui, Tu Xuan . Software development of environmental monitoring system based on Android[J]. Electronic Science and Technology, 2017,30(1):115-118.
[16]	刘丽华 . 基于Android沙箱的软件动态行为监测系统的设计与实现[D]. 北京:北京邮电大学, 2017.
	Liu Lihua . Design and implementation of software dynamic behavior monitoring system based on Android sandbox[D]. Beijing:Beijing University of Posts and Telecommunications, 2017.

Malicious Code Detection and Protection Technology of Mobile Phone Based on Android

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