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A Cloud-based Malware Detection Framework

机译:基于云的恶意软件检测框架

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摘要

Malwares are increasing rapidly. The nature of distribution and effects of malwares attacking several applications requires a real-time response. Therefore, a high performance detection platform is required. In this paper, Hadoop is utilized to perform static binary search and detection for malwares and viruses in portable executable files deployed mainly on the cloud. The paper presents an approach used to map the portable executable files to Hadoop compatible files. The Boyer–Moore-Horspool Search algorithm is modified to benefit from the distribution of Hadoop. The performance of the proposed model is evaluated using a standard virus database and the system is found to outperform similar platforms.
机译:恶意软件正在迅速增加。恶意软件对几种​​应用程序的攻击的分布性质和影响需要实时响应。因此,需要高性能的检测平台。在本文中,Hadoop用于对主要部署在云上的便携式可执行文件中的恶意软件和病毒执行静态二进制搜索和检测。本文提出了一种用于将可移植可执行文件映射到Hadoop兼容文件的方法。修改了Boyer-Moore-Horspool搜索算法,以受益于Hadoop的分布。使用标准病毒数据库评估了建议模型的性能,发现该系统的性能优于类似平台。

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