HOMOGLYPH ATTACK DETECTION
    1.
    发明申请

    公开(公告)号:US20240414199A1

    公开(公告)日:2024-12-12

    申请号:US18813106

    申请日:2024-08-23

    Abstract: The described technology is generally directed towards homoglyph attack detection. A homoglyph attack detection service can create images of customer's protected domain names. A convolutional neural network can generate feature vectors based on the images. The feature vectors can be stored in a similarity search data store. Newly observed domain names can be compared to the customer's protected domain names, by also generating feature vectors for the newly observed domain names and conducting approximate nearest neighbor searches. Search results can be further evaluated by comparing protected domain names to newly observed domain names using a siamese neural network which applies a similarity threshold. Newly observed domain names that meet or exceed the similarity threshold can be flagged for further action.

    Homoglyph attack detection
    3.
    发明授权

    公开(公告)号:US12095813B2

    公开(公告)日:2024-09-17

    申请号:US17380677

    申请日:2021-07-20

    Abstract: The described technology is generally directed towards homoglyph attack detection. A homoglyph attack detection service can create images of customer's protected domain names. A convolutional neural network can generate feature vectors based on the images. The feature vectors can be stored in a similarity search data store. Newly observed domain names can be compared to the customer's protected domain names, by also generating feature vectors for the newly observed domain names and conducting approximate nearest neighbor searches. Search results can be further evaluated by comparing protected domain names to newly observed domain names using a siamese neural network which applies a similarity threshold. Newly observed domain names that meet or exceed the similarity threshold can be flagged for further action.

    HOMOGLYPH ATTACK DETECTION
    4.
    发明申请

    公开(公告)号:US20230028490A1

    公开(公告)日:2023-01-26

    申请号:US17380677

    申请日:2021-07-20

    Abstract: The described technology is generally directed towards homoglyph attack detection. A homoglyph attack detection service can create images of customer's protected domain names. A convolutional neural network can generate feature vectors based on the images. The feature vectors can be stored in a similarity search data store. Newly observed domain names can be compared to the customer's protected domain names, by also generating feature vectors for the newly observed domain names and conducting approximate nearest neighbor searches. Search results can be further evaluated by comparing protected domain names to newly observed domain names using a siamese neural network which applies a similarity threshold. Newly observed domain names that meet or exceed the similarity threshold can be flagged for further action.

    TIMING CONTENT PRESENTATION BASED ON PREDICTED RECIPIENT MENTAL STATE

    公开(公告)号:US20210194985A1

    公开(公告)日:2021-06-24

    申请号:US16723382

    申请日:2019-12-20

    Abstract: Content presentation is timed based on an individual's predicted mental state. In one example, a method performed by a processing system includes extracting a feature set from data that is collected by at least one sensor, where the sensor is monitoring an individual, the feature set comprises at least one feature of the individual, and the feature set excludes features extracted from images of the individual, predicting a current mental state of the individual, where the current mental state is predicted by providing the feature set as input to a machine learning model, sending media content to an endpoint device of the individual when the current mental state indicates that the individual is likely to be receptive to receiving the media content, and postponing sending media content to the endpoint device when the current mental state indicates that the individual is unlikely to be receptive to receiving the media content.

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