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1. 发明申请

WO2020120429A1 SYSTEMS AND METHODS FOR BEHAVIORAL THREAT DETECTION 审中-公开
公开(公告)号：WO2020120429A1
公开(公告)日：2020-06-18
申请号：PCT/EP2019/084312
申请日：2019-12-10
申请人： BITDEFENDER IPR MANAGEMENT LTD
发明人： DICHIU, Daniel , NICULAE, Stefan , BOSINCEANU, Elena A. , ZAMFIR, Sorina N. , DINCU, Andreea , APOSTOAE, Andrei A.
IPC分类号： G06F21/55 , H04L29/06
摘要： In some embodiments, a behavioral computer security system protects clients and networks against threats such as malicious software and intrusion. A set of client profiles is constructed according to a training corpus of events occurring on clients, wherein each client profile represents a subset of protected machines, and each client profile is indicative of a normal or baseline pattern of using the machines assigned to the client respective profile. A client profile may group together machines having a similar event statistic. Following training, events detected on a client are selectively analyzed against a client profile associated with the respective client, to detect anomalous behavior. In some embodiments, individual events are analyzed in the context of other events, using a multi-dimensional event embedding space.

2. 发明申请

WO2013112062A1 SYSTEMS AND METHODS FOR SPAM DETECTION USING CHARACTER HISTOGRAMS 审中-公开
标题翻译：使用字符组态进行垃圾邮件检测的系统和方法
公开(公告)号：WO2013112062A1
公开(公告)日：2013-08-01
申请号：PCT/RO2012/000023
申请日：2012-09-05
申请人： BITDEFENDER IPR MANAGEMENT LTD , DICHIU, Daniel , LUPESCU Z. Lucian
发明人： DICHIU, Daniel , LUPESCU Z. Lucian
IPC分类号： H04L12/58
CPC分类号： H04L63/0263 , H04L51/12
摘要： Described spam detection techniques including string identification, pre-filtering, and character histogram and timestamp comparison steps facilitate accurate, computationally-efficient detection of rapidly-changing spam arriving in short-lasting waves. In some embodiments, a computer system extracts a target character string from an electronic communication such as a blog comment, transmits it to an anti-spam server, and receives an indicator of whether the respective electronic communication is spam or non-spam from the anti-spam server. The anti- spam server determines whether the electronic communication is spam or non-spam according to certain features of the character histogram of the target string. Some embodiments also perform an unsupervised clustering of incoming target strings into clusters, wherein all members of a cluster have similar character histograms.
摘要翻译：描述的垃圾邮件检测技术包括字符串识别，预过滤以及字符直方图和时间戳比较步骤有助于准确，计算高效地检测快速变化的垃圾邮件到达短波。在一些实施例中，计算机系统从诸如博客评论的电子通信中提取目标字符串，将其发送到反垃圾邮件服务器，并且从反对方接收关于各个电子通信是垃圾邮件还是非垃圾邮件的指示符 - 垃圾邮件服务器。反垃圾邮件服务器根据目标字符串的字符直方图的某些特征来确定电子通信是垃圾邮件还是非垃圾邮件。一些实施例还将传入目标字符串的无监督聚类执行为群集，其中群集的所有成员具有相似的字符直方图。

3. 发明申请

WO2020120428A1 SYSTEMS AND METHODS FOR BEHAVIORAL THREAT DETECTION 审中-公开
公开(公告)号：WO2020120428A1
公开(公告)日：2020-06-18
申请号：PCT/EP2019/084311
申请日：2019-12-10
申请人： BITDEFENDER IPR MANAGEMENT LTD
发明人： DICHIU, Daniel , NICULAE, Stefan , BOSINCEANU, Elena A. , ZAMFIR, Sorina N. , DINCU, Andreea , APOSTOAE, Andrei A.
IPC分类号： G06F21/55 , H04L29/06
摘要： In some embodiments, a behavioral computer security system protects clients and networks against threats such as malicious software and intrusion. A set of client profiles is constructed according to a training corpus of events occurring on clients, wherein each client profile represents a subset of protected machines, and each client profile is indicative of a normal or baseline pattern of using the machines assigned to the client respective profile. A client profile may group together machines having a similar event statistic. Following training, events detected on a client are selectively analyzed against a client profile associated with the respective client, to detect anomalous behavior. In some embodiments, individual events are analyzed in the context of other events, using a multi-dimensional event embedding space.

4. 发明申请

WO2013112061A1 SYSTEM AND METHODS FOR SPAM DETECTION USING FREQUENCY SPECTRA OF CHARACTER STRINGS 审中-公开
标题翻译：使用特征频带的频谱进行垃圾检测的系统和方法
公开(公告)号：WO2013112061A1
公开(公告)日：2013-08-01
申请号：PCT/RO2012/000022
申请日：2012-09-05
申请人： BITDEFENDER IPR MANAGEMENT LTD , DICHIU, Daniel , LUPESCU, Z. Lucian
发明人： DICHIU, Daniel , LUPESCU, Z. Lucian
IPC分类号： H04L12/58
CPC分类号： H04L51/12 , G06F17/30011
摘要： Described spam detection techniques including string identification, pre-filtering, and frequency spectrum and timestamp comparison steps facilitate accurate, computationally-efficient detection of rapidly-changing spam arriving in short-lasting waves. In some embodiments, a computer system extracts a target character string from an electronic communication such as a blog comment, transmits it to an anti-spam server, and receives an indicator of whether the respective electronic communication is spam or non-spam from the anti-spam server. The anti-spam server determines whether the electronic communication is spam or non-spam according to features of the frequency spectrum of the target string. Some embodiments also perform an unsupervised clustering of incoming target strings into clusters, wherein all members of a cluster have similar spectra.
摘要翻译：描述的垃圾邮件检测技术，包括字符串识别，预过滤，频谱和时间戳比较步骤有助于准确，计算高效地检测快速变化的垃圾邮件到达短波。在一些实施例中，计算机系统从诸如博客评论的电子通信中提取目标字符串，将其发送到反垃圾邮件服务器，并且从反对方接收关于各个电子通信是垃圾邮件还是非垃圾邮件的指示符垃圾邮件服务器。反垃圾邮件服务器根据目标字符串的频谱的特征来确定电子通信是垃圾邮件还是非垃圾邮件。一些实施例还将输入目标字符串的无监督聚类执行为群集，其中群集的所有成员具有相似的频谱。

5. 发明申请

WO2021214092A2 MACHINE LEARNING SYSTEMS AND METHODS FOR REDUCING THE FALSE POSITIVE MALWARE DETECTION RATE 审中-公开
公开(公告)号：WO2021214092A2
公开(公告)日：2021-10-28
申请号：PCT/EP2021/060293
申请日：2021-04-21
申请人： BITDEFENDER IPR MANAGEMENT LTD
发明人： DICHIU, Daniel , DINCU, Andreea , BOTARLEANU, Robert-mihail , ZAMFIR, Sorina N. , BOSINCEANU, Elena A. , PREJBEANU, Razvan
IPC分类号： G06F21/57 , G06F21/55 , H04L29/06 , G06F21/552 , G06F21/56 , G06F21/577 , G06F2221/033 , G06F3/0604 , G06F3/065 , G06F3/0673 , G06N3/08 , H04L63/1425
摘要： In some embodiments, a behavior classifier comprises a set of neural networks trained to determine whether a monitored software entity is malicious according to a sequence of computing events caused by the execution of the respective entity. When the behavior classifier indicates that the entity is malicious, some embodiments execute a memory classifier comprising another set of neural networks trained to determine whether the monitored entity is malicious according to a memory snapshot of the monitored entity. Applying the classifiers in sequence may substantially reduce the false positive detection rate, while reducing computational costs.

6. 发明申请

WO2020120427A1 SYSTEMS AND METHODS FOR BEHAVIORAL THREAT DETECTIION 审中-公开
公开(公告)号：WO2020120427A1
公开(公告)日：2020-06-18
申请号：PCT/EP2019/084310
申请日：2019-12-10
申请人： BITDEFENDER IPR MANAGEMENT LTD
发明人： DICHIU, Daniel , NICULAE, Stefan , BOSINCEANU, Elena A. , ZAMFIR, Sorina N. , DINCU, Andreea , APOSTOAE, Andrei A.
IPC分类号： G06F21/55 , H04L29/06
摘要： In some embodiments, a behavioral computer security system protects clients and networks against threats such as malicious software and intrusion. A set of client profiles is constructed according to a training corpus of events occurring on clients, wherein each client profile represents a subset of protected machines, and each client profile is indicative of a normal or baseline pattern of using the machines assigned to the client respective profile. A client profile may group together machines having a similar event statistic. Following training, events detected on a client are selectively analyzed against a client profile associated with the respective client, to detect anomalous behavior. In some embodiments, individual events are analyzed in the context of other events, using a multi-dimensional event embedding space.

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