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The performance cost of software obfuscation for Android applications

机译:Android应用程序的软件混淆性能成本

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AbstractSoftware security of Android applications is especially susceptible (vulnerable) to malicious reverse engineer than the native code based software, because its Java bytecode is easier to decompile and to reconstruct the original Java source code. Therefore obfuscation is an essential criterion for the protection of Android applications. Meanwhile, the unpredicted performance loss will be caused by the obfuscation, which might seriously influence the user experience of the software. Therefore the obfuscation degree and the performance cost out of it require being optimized. In this paper, we are working on the problem that: to obfuscate an Android application to a target level of “difficulty” degree, while not substantially “slowing it down”. We measure “difficulty” by utilizing software complexity metrics and the “slow” in CPU cycles. Within the framework designed for obfuscating Android applications, we implement the “Naïve Bayesian Classifier” algorithm for the optimized obfuscation of the software complexity and the performance, and show that it outperforms the algorithm whose predictions rely on mean values. We furthermore investigate the performance penalty imposed by obfuscation process when framework targets different complexity values and metrics. We show that some obfuscation methods are more performance costly than others to achieve the same metric value increase. Our result shows that, for any given software complexity, the required performance benefits can be achieved if the right obfuscation techniques are used.
机译: 摘要 Android应用程序的软件安全性比基于本机代码的软件更容易受到恶意逆向工程的攻击(脆弱),因为其Java字节码更容易反编译并重建原始Java源代码。因此,混淆是保护Android应用程序的必要标准。同时,由于混淆会导致意外的性能损失,这可能会严重影响软件的用户体验。因此,需要优化混淆度和其中的性能成本。在本文中,我们正在解决以下问题:将Android应用程序混淆到“困难”程度的目标级别,而又不实质地“降低它的速度”。我们通过利用软件复杂性指标和CPU周期中的“慢”来衡量“难度”。在为混淆Android应用程序而设计的框架内,我们实现了“朴素贝叶斯分类器”算法,以优化混淆软件的复杂性和性能,并显示出优于预测依赖于平均值的算法。当框架针对不同的复杂度值和度量标准时,我们还研究了混淆处理对性能的影响。我们表明,对于相同的度量值增加,某些混淆方法比其他方法更加昂贵。我们的结果表明,对于任何给定的软件复杂度,如果使用正确的混淆技术都可以实现所需的性能收益。

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