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1. 发明申请

US20150121461A1 METHOD AND SYSTEM FOR DETECTING UNAUTHORIZED ACCESS TO AND USE OF NETWORK RESOURCES WITH TARGETED ANALYTICS 审中-公开
标题翻译：用于检测未经授权的访问和使用具有指定分析的网络资源的方法和系统
公开(公告)号：US20150121461A1
公开(公告)日：2015-04-30
申请号：US14061835
申请日：2013-10-24
申请人： Cyber-Ark Software Ltd.
发明人： Andrey DULKIN , Yair Sade , Roy Adar , Aviram Shmueli
IPC分类号： H04L29/06
CPC分类号： H04L63/1408
摘要： Methods and systems are disclosed for detecting improper, and otherwise unauthorized actions, associated with network resources, the actions including access to the resource and activity associated with the resource. The unauthorized actions are detected by analyzing action data of user actions employing accounts managed by a privileged access management system and associated with a network resource against profiles and rules to discover anomalies and/or deviations from rules associated with the network resource or accounts.
摘要翻译：公开了用于检测与网络资源相关联的不正当的或未经授权的动作的方法和系统，所述动作包括对资源的访问和与资源相关联的活动。通过分析使用由特权访问管理系统管理并且与网络资源相关联的账户的用户动作的动作数据来检测未授权动作，以针对配置文件和规则来发现与网络资源或帐户相关联的规则的异常和/或偏离。

2. 发明授权

US09712548B2 Privileged analytics system 有权
公开(公告)号：US09712548B2
公开(公告)日：2017-07-18
申请号：US14524145
申请日：2014-10-27
申请人： Cyber-Ark Software Ltd.
发明人： Aviram Shmueli , Andrey Dulkin , Yair Sade , Assaf Weiss
IPC分类号： H04L29/06
CPC分类号： H04L63/1425
摘要： A computer-implemented method for determining whether a computer network is compromised by unauthorized activity on the computer network. The computer-implemented method comprises identifying a behavioral anomaly of an entity on the computer network, classifying the anomaly as a system event based on an assigned score for the anomaly being at least at a predetermined score threshold, updating an incident based on at least one common parameter between the system event and other system events which comprise the incident, each system event of the incident including an assigned score from when the event was an anomaly, updating a system status based on at least the incident, and assigning a system status score to the system status, and, determining whether the system status score is at least at a predetermined threshold system status score indicating that the computer network may be compromised.

3. 发明申请

US20150304349A1 ANOMALY DETECTION IN GROUPS OF NETWORK ADDRESSES 有权
标题翻译：网络地址组异常检测
公开(公告)号：US20150304349A1
公开(公告)日：2015-10-22
申请号：US14253945
申请日：2014-04-16
申请人： Cyber-Ark Software Ltd.
发明人： Ruth Bernstein , Andrey Dulkin , Assaf Weiss , Aviram Shmueli
IPC分类号： H04L29/06
CPC分类号： H04L63/1425 , H04L63/0227
摘要： A method for identifying anomalies in a group of network addresses includes building a model of the group of network addresses and identifying a network address as anomalous based on the deviation of the network address from the model. The model is built from a group of network addresses. The network addresses are input and parsed into one or more address trees. A ripeness score is maintained for each of the nodes in the address trees, based, at least in part, on the number of occurrences of the network address portion represented by the node. Nodes having respective ripeness scores within a specified range are classified as ripe nodes, and may be indicative of normal behavior, and nodes having respective ripeness scores outside the specified range of ripeness scores are classified as unripe, and may be indicative of anomalous behavior.
摘要翻译：一种用于识别一组网络地址中的异常的方法包括基于网络地址与模型的偏差建立网络地址组的模型并将网络地址识别为异常。该模型是从一组网络地址构建的。网络地址被输入并解析成一个或多个地址树。至少部分地基于由节点表示的网络地址部分的出现次数，为地址树中的每个节点保持成熟度分数。具有规定范围内的成熟度分数的节点被分类为成熟节点，并且可以指示正常行为，并且具有超出特定成熟度分数的成熟度分数的节点被分类为未成熟，并且可以指示异常行为。

4. 发明授权

US09497206B2 Anomaly detection in groups of network addresses 有权
标题翻译：网络地址组异常检测
公开(公告)号：US09497206B2
公开(公告)日：2016-11-15
申请号：US14253945
申请日：2014-04-16
申请人： Cyber-Ark Software Ltd.
发明人： Ruth Bernstein , Andrey Dulkin , Assaf Weiss , Aviram Shmueli
IPC分类号： H04L29/06
CPC分类号： H04L63/1425 , H04L63/0227
摘要： A method for identifying anomalies in a group of network addresses includes building a model of the group of network addresses and identifying a network address as anomalous based on the deviation of the network address from the model. The model is built from a group of network addresses. The network addresses are input and parsed into one or more address trees. A ripeness score is maintained for each of the nodes in the address trees, based, at least in part, on the number of occurrences of the network address portion represented by the node. Nodes having respective ripeness scores within a specified range are classified as ripe nodes, and may be indicative of normal behavior, and nodes having respective ripeness scores outside the specified range of ripeness scores are classified as unripe, and may be indicative of anomalous behavior.
摘要翻译：一种用于识别一组网络地址中的异常的方法包括基于网络地址与模型的偏差建立网络地址组的模型并将网络地址识别为异常。该模型是从一组网络地址构建的。网络地址被输入并解析成一个或多个地址树。至少部分地基于由节点表示的网络地址部分的出现次数，为地址树中的每个节点保持成熟度分数。具有规定范围内的成熟度分数的节点被分类为成熟节点，并且可以指示正常行为，并且具有超出特定成熟度分数的成熟度分数的节点被分类为未成熟，并且可以指示异常行为。

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