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首页> 外文会议>2011 Sixth International Conference on Availability, Reliability and Security >Accurate Adware Detection Using Opcode Sequence Extraction
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Accurate Adware Detection Using Opcode Sequence Extraction

机译：使用操作码序列提取进行准确的广告软件检测

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摘要

Adware represents a possible threat to the security and privacy of computer users. Traditional signature-based and heuristic-based methods have not been proven to be successful at detecting this type of software. This paper presents an adware detection approach based on the application of data mining on disassembled code. The main contributions of the paper is a large publicly available adware data set, an accurate adware detection algorithm, and an extensive empirical evaluation of several candidate machine learning techniques that can be used in conjunction with the algorithm. We have extracted sequences of opcodes from adware and benign software and we have then applied feature selection, using different configurations, to obtain 63 data sets. Six data mining algorithms have been evaluated on these data sets in order to find an efficient and accurate detector. Our experimental results show that the proposed approach can be used to accurately detect both novel and known adware instances even though the binary difference between adware and legitimate software is usually small.
机译：广告软件对计算机用户的安全和隐私构成了潜在威胁。传统的基于签名和基于启发式的方法尚未被证明能够成功检测到此类软件。本文提出了一种基于反汇编代码数据挖掘应用的广告软件检测方法。该论文的主要贡献是大型可公开获得的广告软件数据集，准确的广告软件检测算法以及对可与该算法结合使用的几种候选机器学习技术的广泛经验评估。我们从广告软件和良性软件中提取了操作码序列，然后应用特征选择（使用不同的配置）来获得63个数据集。在这些数据集上评估了六种数据挖掘算法，以便找到一种有效且准确的检测器。我们的实验结果表明，即使广告软件与合法软件之间的二进制差异通常很小，所提出的方法仍可用于准确检测新颖的广告软件实例和已知的广告软件实例。

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