發(fā)布時(shí)間：2018-11-11 08:48

【摘要】：Android平臺(tái)應(yīng)用數(shù)量迅速增長,隨之而來的安全問題也日益增多。但現(xiàn)有分析工具大多數(shù)只對(duì)應(yīng)用進(jìn)行簡單的掃描,較少涉及深層次的數(shù)據(jù)流分析,因此某些漏洞無法有效地被發(fā)現(xiàn)。該文基于對(duì)已有Android應(yīng)用漏洞特征的歸納,提出一種Android應(yīng)用漏洞的靜態(tài)分析框架。從Manifest文件掃描、Smali代碼危險(xiǎn)函數(shù)分析、數(shù)據(jù)流分析等3個(gè)層面歸納了7類主流安全漏洞模式,依此構(gòu)建了漏洞檢測規(guī)則,并結(jié)合相關(guān)靜態(tài)分析技術(shù)對(duì)應(yīng)用進(jìn)行分析,以發(fā)現(xiàn)其中存在的安全漏洞。通過對(duì)323個(gè)Android應(yīng)用程序的實(shí)驗(yàn)分析,結(jié)果表明:該框架的有效檢出率在70%以上,誤報(bào)率在30%以下。因此,該框架能夠有效發(fā)現(xiàn)Android應(yīng)用中常見的安全漏洞,提高用戶安全性。
[Abstract]:The number of Android platform applications is increasing rapidly, and the security problems are increasing day by day. However, most of the existing analysis tools only scan applications simply, and less involved in deep-level data flow analysis, so some vulnerabilities can not be effectively found. Based on the characteristics of existing Android application vulnerabilities, this paper proposes a static analysis framework for Android application vulnerabilities. From three aspects of Manifest file scanning, Smali code hazard function analysis and data flow analysis, this paper concludes 7 kinds of mainstream security vulnerability patterns, and constructs vulnerability detection rules according to them, and analyzes the application with the relevant static analysis technology. To detect a security flaw in it. The experimental results of 323 Android applications show that the effective detection rate of the framework is more than 70% and the false positive rate is less than 30%. Therefore, the framework can effectively discover common security vulnerabilities in Android applications and improve user security.
【作者單位】： 中國信息安全測評(píng)中心;
【基金】：國家自然科學(xué)基金資助項(xiàng)目(61272493)
【分類號(hào)】：TP316;TP309

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