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1. 发明申请

WO2023278070A1 AUTOMATIC LABELING OF TEXT DATA 审中-公开
公开(公告)号：WO2023278070A1
公开(公告)日：2023-01-05
申请号：PCT/US2022/030464
申请日：2022-05-23
申请人： MICROSOFT TECHNOLOGY LICENSING, LLC
发明人： SEWAK, Mohit , POLURI, Ravi Kiran Reddy , BLUM, William , CHAN, Pak On , LI, Weisheng , ACHARYA, Sharada Shirish , RUDNICK, Christian , BETSER, Michael Abraham , DRINIC, Milenko , LIU, Sihong
IPC分类号： G06F16/33 , G06F16/35 , G06F16/3344 , G06F16/3346
摘要： The technology described herein determines whether a candidate text is in a requested class by using a generative model that may not be trained on the requested class. The present technology may use of a model trained primarily in an unsupervised mode, without requiring a large number of manual user-input examples of a label class. The may produce a semantically rich positive example of label text from a candidate text and label. Likewise, the technology may produce from the candidate text and the label a semantically rich negative example of label text. The labeling service makes use of a generative model to produce a generative result, which estimates the likelihood that the label properly applies to the candidate text. In another aspect, the technology is directed toward a method for obtaining a semantically rich example that is similar to a candidate text.

2. 发明申请

WO2021087496A1 CAMPAIGN INTELLIGENCE AND VISUALIZATION FOR COMBATING CYBERATTACKS 审中-公开
公开(公告)号：WO2021087496A1
公开(公告)日：2021-05-06
申请号：PCT/US2020/058757
申请日：2020-11-03
申请人： MICROSOFT TECHNOLOGY LICENSING, LLC
发明人： COSTEA, Mihai , BETSER, Michael Abraham , POLURI, Ravi Kiran Reddy , DING, Hua , LI, Weisheng , PAMPATI, Phanindra , YOST, David Nicholas
IPC分类号： G06F21/55 , G06F21/56
摘要： Methods, systems, and computer storage media for providing a multi-attribute cluster-identifier that supports identifying malicious activity in computing environments. An instance of an activity having an attribute set can be assessed. The attribute set of the instance of the activity is analyzed to determine whether the instance of the activity is a malicious activity. The attribute set of the instance of the activity is compared to a plurality of multi-attribute cluster-identifiers of previous instances of the activity, such that, a determination that the instance of the activity is a malicious activity is made when the attribute set of the instance of the activity corresponds to an identified multi-attribute cluster-identifier. The identified multi-attribute cluster-identifier has a risk score and an attribute set that indicate a likelihood that the instance of the activity is a malicious activity. A visualization that identifies the instance of the activity as a malicious activity is generated.

3. 发明申请

WO2017003974A1 USER-FEEDBACK-BASED TENANT-LEVEL MESSAGE FILTERING 审中-公开
标题翻译：基于用户反馈的优先级消息过滤
公开(公告)号：WO2017003974A1
公开(公告)日：2017-01-05
申请号：PCT/US2016/039696
申请日：2016-06-28
申请人： MICROSOFT TECHNOLOGY LICENSING, LLC
发明人： GUNASEKARA, Atapattuge D. Samith , TAIMANA, Bruce , GOUREVITCH, Gregory , POLURI, Ravi Kiran Reddy , RANGARAJAN, Krishnan , PATRO, Una Sai Prasad
IPC分类号： G06Q10/10
CPC分类号： H04L51/12 , G06Q10/107
摘要： Embodiments maintain filtering criteria for classifying electronic messages in a multi-tenant environment, including maintaining global filtering criteria for all tenants, as well as tenant-level filtering criteria for each tenant. For each tenant, feedback regarding a messaging campaign is identified. When the messaging campaign has not been categorized, and the feedback signals the messaging campaign as undesirable, the tenant-level filtering criteria for the tenant is updated to signal the messaging campaign as undesirable. When the messaging campaign has previously been categorized as undesirable, and the feedback signals the messaging campaign as desirable, the tenant-level filtering criteria for the tenant is updated to signal the messaging campaign as desirable. A reputation score for each tenant is also calculated. The global filtering criteria is updated to signal desirability of the messaging campaign when a threshold number of tenants, each having a threshold reputation score, reach a consensus regarding desirability of the messaging campaign.
摘要翻译：实施例维护用于在多租户环境中分类电子消息的过滤标准，包括维护所有租户的全局过滤标准，以及每个租户的租户级别过滤标准。对于每个租户，确定有关消息传递活动的反馈。当消息传递活动尚未分类，并且反馈将消息传送信号指示为不期望时，租户的租户级别过滤标准被更新，以将消息传送广告信号指示为不期望的。当消息传播活动以前被分类为不期望的，并且反馈将消息传送信号指示为期望时，租户的租户级别过滤标准被更新，以将消息传送信号指示为期望的。还计算每个租户的声誉评分。当全球过滤标准被更新以表示消息传递活动的可取性，当阈值数量的租户（每个具有阈值信誉评分）达成关于消息传递活动的可取性的共识时。

4. 发明公开

EP4290808A2 CAMPAIGN INTELLIGENCE AND VISUALIZATION FOR COMBATING CYBERATTACKS 审中-公开
公开(公告)号：EP4290808A2
公开(公告)日：2023-12-13
申请号：EP23206708.2
申请日：2020-11-03
申请人： Microsoft Technology Licensing, LLC
发明人： COSTEA, Mihai , BETSER, Michael Abraham , POLURI, Ravi Kiran Reddy , DING, Hua , LI, Weisheng , PAMPATI, Phanindra , YOST, David Nicholas
IPC分类号： H04L9/40
摘要： Methods, systems, and computer storage media for providing a multi-attribute cluster-identifier that supports identifying malicious activity in computing environments. An instance of an activity having an attribute set can be assessed. The attribute set of the instance of the activity is analyzed to determine whether the instance of the activity is a malicious activity. The attribute set of the instance of the activity is compared to a plurality of multi-attribute cluster-identifiers of previous instances of the activity, such that, a determination that the instance of the activity is a malicious activity is made when the attribute set of the instance of the activity corresponds to an identified multi-attribute cluster-identifier. The identified multi-attribute cluster-identifier has a risk score and an attribute set that indicate a likelihood that the instance of the activity is a malicious activity. A visualization that identifies the instance of the activity as a malicious activity is generated.

5. 发明公开

EP4290808A3 CAMPAIGN INTELLIGENCE AND VISUALIZATION FOR COMBATING CYBERATTACKS 审中-公开
公开(公告)号：EP4290808A3
公开(公告)日：2024-02-21
申请号：EP23206708.2
申请日：2020-11-03
申请人： Microsoft Technology Licensing, LLC
发明人： COSTEA, Mihai , BETSER, Michael Abraham , POLURI, Ravi Kiran Reddy , DING, Hua , LI, Weisheng , PAMPATI, Phanindra , YOST, David Nicholas
IPC分类号： G06F21/55 , G06F21/56 , H04L41/22 , H04L51/212 , H04L9/40
摘要： Methods, systems, and computer storage media for providing a multi-attribute cluster-identifier that supports identifying malicious activity in computing environments. An instance of an activity having an attribute set can be assessed. The attribute set of the instance of the activity is analyzed to determine whether the instance of the activity is a malicious activity. The attribute set of the instance of the activity is compared to a plurality of multi-attribute cluster-identifiers of previous instances of the activity, such that, a determination that the instance of the activity is a malicious activity is made when the attribute set of the instance of the activity corresponds to an identified multi-attribute cluster-identifier. The identified multi-attribute cluster-identifier has a risk score and an attribute set that indicate a likelihood that the instance of the activity is a malicious activity. A visualization that identifies the instance of the activity as a malicious activity is generated.

6. 发明公开

EP4052156A1 CAMPAIGN INTELLIGENCE AND VISUALIZATION FOR COMBATING CYBERATTACKS 审中-公开
公开(公告)号：EP4052156A1
公开(公告)日：2022-09-07
申请号：EP20816697.5
申请日：2020-11-03
申请人： Microsoft Technology Licensing, LLC
发明人： COSTEA, Mihai , BETSER, Michael Abraham , POLURI, Ravi Kiran Reddy , DING, Hua , LI, Weisheng , PAMPATI, Phanindra , YOST, David Nicholas
IPC分类号： G06F21/55 , G06F21/56

7. 发明公开

EP4364000A1 AUTOMATIC LABELING OF TEXT DATA 审中-公开
公开(公告)号：EP4364000A1
公开(公告)日：2024-05-08
申请号：EP22732737.6
申请日：2022-05-23
申请人： Microsoft Technology Licensing, LLC
发明人： SEWAK, Mohit , POLURI, Ravi Kiran Reddy , BLUM, William , CHAN, Pak On , LI, Weisheng , ACHARYA, Sharada Shirish , RUDNICK, Christian , BETSER, Michael Abraham , DRINIC, Milenko , LIU, Sihong
IPC分类号： G06F16/33 , G06F16/35
CPC分类号： G06F16/35 , G06F16/3344 , G06F16/3346 , G06F40/30

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