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A Review on Behavior-Based Detection for Network Threats

机译:基于行为的网络威胁检测综述

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摘要

With the appearance and development of the technology of malicious codes and other unknown threats, information security has drawn people's attention. In this paper, we investigate on behavior-based detection which is different from traditional static detection technology. Firstly, we discuss the procedure in detail, especially feature extraction and classification. Several machine learning methods such as SVM, bayesian decision are adopted to solve these problems. What's more, we outline the architecture to specify operating mechanism. The features and conclusion are discussed finally.
机译:随着恶意代码和其他未知威胁技术的出现和发展,信息安全已引起人们的关注。在本文中,我们研究了与传统的静态检测技术不同的基于行为的检测。首先,我们详细讨论该过程,特别是特征提取和分类。为了解决这些问题,采用了多种机器学习方法,例如SVM,贝叶斯决策。此外,我们概述了用于指定操作机制的体系结构。最后讨论了特征和结论。

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