基于机器学习的欧洲社交网络入侵检测系统

N. Sengupta
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引用次数: 0

摘要

在现代社会,人们在个人生活和公司生活中都依赖于社交网络进行交流。社交网络有不同类型的用户,一些用户使用社交网络有不同的目的,如教育、娱乐、交换信息等。一些用户利用社交网络作为平台来交换对社会有害的信息。由于有些通信是有用的,有些是有害的,因此分析这些通信并识别有害的通信对于国家的利益非常重要。建立社会网络有害传播识别的分析模型是计算机科学研究的一个具有挑战性的领域。在研究方案中,设计了安装在网关中的入侵检测系统(IDS)。本文提出了IDS的四层体系结构。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine Learning Based Intrusion Detection System for Social Network of Europe
In modern age1, people have become dependent on social networking for communication for both in personal life and in corporate life. There are different types of users of social network, some users use social network for different good purposes like educational, entertainment, exchanging information, etc. Some users are using social network as a platform to exchange information for doing harmful work to the society. As some communications are useful and some are harmful, it's very important to analyze this traffic and to identify the harmful communication for the benefit of the country. Developing analysis model for identification of harmful communication of social network is a challenging area for computer science researchers. In the research proposal, Intrusion Detection System (IDS) is designed which should be installed in the gateways. The proposed research has four tier architectures for IDS.
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