首页> 外国专利> METHOD FOR INTRUSION DETECTION OF UBIQUITOUS HOME NETWORKS ENVIRONMENT, RECORDING MEDIUM THEREOF AND APPARATUS FOR INTRUSION DETECTION OF UBIQUITOUS HOME NETWORKS ENVIRONMENT

METHOD FOR INTRUSION DETECTION OF UBIQUITOUS HOME NETWORKS ENVIRONMENT, RECORDING MEDIUM THEREOF AND APPARATUS FOR INTRUSION DETECTION OF UBIQUITOUS HOME NETWORKS ENVIRONMENT

机译:泛型家庭网络环境的入侵检测方法,其记录介质和泛型家庭网络环境的入侵检测装置

摘要

An intrusion detection method of a ubiquitous home network environment, a recording medium thereof, and an intrusion detection device in the ubiquitous home network environment are provided to offer detailed information on an attacking type by using clustering, to ensure expansibility and escalation of a system, and to ensure fast and efficient study and updating by targeting a class only of an attacking type while another class is not influenced when the new attacking type is detected. Classification for normal data and attacking data is performed by using a single class support vector machine from network traffic data(510). The classified attacking data is classified into passive attacks and active attacks to determine a risk level of the attacking data(520). Attacking types of the classified attacking data are classified by using multiple class support vector machines(530). Clustering using a kernel ART is performed according to each attacking type, and detailed information on the attacking types is generated(540). A coping method of a system is determined by using the risk level, the attacking types, and the detailed information(550).
机译:提供一种无处不在的家庭网络环境的入侵检测方法,其记录介质以及该无处不在的家庭网络环境中的入侵检测设备,以通过使用群集来提供有关攻击类型的详细信息,以确保系统的可扩展性和可升级性,并且通过仅针对一种攻击类型的类来确保快速有效的学习和更新,而在检测到新的攻击类型时不影响另一类。正常数据和攻击数据的分类是通过使用单类支持向量机根据网络流量数据进行的(510)。分类的攻击数据被分为被动攻击和主动攻击,以确定攻击数据的风险等级(520)。通过使用多个类别支持向量机来对分类的攻击数据的攻击类型进行分类(530)。根据每种攻击类型执行使用内核ART的聚类,并生成有关攻击类型的详细信息(540)。通过使用风险等级,攻击类型和详细信息来确定系统的应对方法(550)。

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