Microsoft Technology Licensing, LLC

Other

Ramin L Halviatti

Michael I Hyman

Frank G Sanborn

Ahmed M Azmy Hassan

Sunil Pai

Pavan Gopal Bandla

LiLei Cui

Christopher Michael Jeffords

Noah Bergman

Srikanth Bolisetty

Ayala Miller

James Matthew Atkins

Kaymie Sato-Hayashi-Kagawa Shiozawa

Ramin Zabih

Jessica Michelle Satnick

Ravi Kumar Lingamallu

Ahmed Awad-idris

Amritaputra Bhattacharya

Access to secured items in a computing system is requested instead of being persistent. Access requests may be granted on a just-in-time basis. Anomalous access requests are detected using machine learning models based on historic patterns. Models utilizing conditional probability or collaborative filtering also facilitate the creation of human-understandable explanations of threat assessments. Individual machine learning models are based on historic data of users, peers, cohorts, services, or resources. Models may be weighted, and then aggregated in a subsystem to produce an access request risk score. Scoring principles and conditions utilized in the scoring subsystem may include probabilities, distribution entropies, and data item counts. A feedback loop allows incremental refinement of the subsystem. Anomalous requests that would be automatically approved under a policy may instead face human review, and low threat requests that would have been delayed by human review may instead be approved automatically.

Anomaly-based mitigation of access request risk

A method of supporting all raster-based image manipulations described in vector-based terms. The present invention has the benefits of providing clean transformation that vector-based manipulations yields, and providing a broad selection of all image transformation operations that raster-based manipulations yields. In one aspect of the invention a vector-defined shape is drawn on top of a raster-based image by replacing the contents of the vector image with the bits from the raster image. In another aspect of the present invention, a copy of the portion of the raster image that overlaps with the vector-defined portion is made, the transformation operation is performed on the copy, and then the portion of the raster image is replaced with the transformed copy. In yet another aspect of the present invention, a filter, such as a transformation operation, is attached to a textual vector instruction, the bits defined by the textual vector instruction are replaced with the corresponding bits in a raster image, and the transformation is applied. In still another aspect of the present invention, a browser receives a HTML page, in which the HTML page identifies a custom plug-in extension method to the browser, a background image, a vector shape, and a raster manipulation, the browser communicates the information in the HTML page to the custom plug-in extension component, and the component uses an input buffer, and an output buffer coupled to the browser to perform the raster manipulation on the vector shape and background image.

System and method for providing vector editing of bitmap images

A method of supporting all raster-based image manipulations described in vector-based terms. The present invention has the benefits of providing clean transformation that vector-based manipulations yields, and providing a broad selection of all image transformation operations that raster-based manipulations yield. In one aspect of the invention a vector-defined shape is drawn on top of a raster-based image by replacing the contents of the vector image with the bits from the raster image. In another aspect of the present invention, a copy of the portion of the raster image that overlaps with the vector-defined portion is made, the transformation operation is performed on the copy, and then the portion of the raster image is replaced with the transformed copy. In yet another aspect of the present invention, a filter, such as a transformation operation, is attached to a textual vector instruction, the bits defined by the textual vector instruction are replaced with the corresponding bits in a raster image, and the transformation is applied. In still another aspect of the present invention, a browser receives a HTML page, in which the HTML page identifies a custom plug-in extension method to the browser, a background image, a vector shape, and a raster manipulation, the browser communicates the information in the HTML page to the custom plug-in extension component, and the component uses an input buffer, and an output buffer coupled to the browser to perform the raster manipulation on the vector shape and background image.

An invention for quantitatively analyzing bitmap images using computer vision is disclosed. In one embodiment, these bitmap images correspond to the rendered screens of two applications based on a same data source file. An optional preprocessing step filters non-important information for analyzing purposes such as the background, replaces each image with a blank image of the same size, and modifies non-visible attributes of a screen so their structure can be recovered during the computer vision processing. After a series of rendered screens of each application are captured, these bitmap images are interpreted using computer vision techniques to produce machine-readable visual attributes of the rendered screens. Corresponding attributes from each of the two applications are then compared to generate a set of differences, where those differences within a predefined set of deliberate design differences are ignored. These attributes and differences are then processed to derive a set of grades reflecting the similarities between the rendered screens of the two applications. In determining these grades, a set of user-definable thresholds are used to overlook small variances inherent in the rendering by the different applications.

Method and apparatus for analyzing computer screens

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Kirkland, WA, United States of America

Ramin L Halviatti