Microsoft Technology Licensing, LLC

Benjamin Livshits

David Alexander Molnar

Jiahe Helen Wang

Jeffrey Van Gogh

Emre Mehmet Kiciman

Benjamin Zorn

Kenneth D Ray

Henricus Johannes Maria Meijer

Eyal Ofek

Darko Kirovski

Todd Douglas Mytkowicz

Danny Van Velzen

Margus Veanes

Vijay Gajjala

Patrice Godefroid

Gennady Medvinsky

Alexander Nikolavich Moshchuk

Christian Seifert

Prateek Saxena

Matthew Fredrikson

Loris D'Antoni

Brian C Beckman

Douglas Christopher Burger

Michael C Fanning

Weidong Cui

Nachiappan Nagappan

Jesper B Lind

Lior Shapira

Tadayoshi Kohno

Cedric Fournet

Dragos A Manolescu

Franziska Roesner

Ran Gal

Jaeyeon Jung

Chen Ding

Alexander Moshchuk

Christopher M H Faucon

Abhishek Prateek

Timothy Scott Saponas

Charles M Curtsinger

Blair MacIntyre

Andrew Joseph Davidson

David Simmons

Alan M Dunn

Nikhil Swamy

Lucas S Figueiredo

Krishnaprasad Vikram

Robert A Cochran

John Vilk

Suman Jana

Georgios Kastrinis

Magnus Madsen

Clemens Kolbitsch

Arjun Guha

William G J Halfond

William Gj Halfond

Benjamin Stock

Bryan Sullivan

Matthew Thornhill Hall

Blair Macintyre

Various technologies described herein pertain to automation of crowd-sourced polling. At least one query can be received. The at least one query includes a request. A poll can be automatically generated based upon the at least one query, where the poll corresponds to the request. The poll can be submitted to a crowdsourcing backend, where instances of the poll are administered on the crowdsourcing backend. Moreover, crowd-sourced responses to the instances of the poll can be retrieved from the crowdsourcing backend. The crowd-sourced responses to the instances of the poll can respectively include crowd-sourced responses to the request. The crowd-sourced responses to the request can be converted to a random variable. An operation can be performed upon the random variable. The operation can include one or more of a statistical analysis (e.g., hypothesis testing), bias correction, an arithmetic operation, expected value computation, standard deviation computation, etc.

Automation of crowd-sourced polling

A 'Poll Optimizer' provides automated techniques for performing various combinations of both static and runtime optimizations for crowd-sourced queries including, but not limited to, crowd-sourced opinion-based polls. These optimizations have been observed to improve poll performance by reducing factors such as completion times, monetary costs, and error rates of polls. In various implementations, the Poll Optimizer receives an input query representing a crowd-sourced poll that is formatted as a multi-layer structure (e.g., LINQ-based queries natively supported by .NET languages, JQL-based queries supported by JAVA, etc.). The Poll optimizer then iteratively reduces the multi-layer structure of the input query to construct a reformulated query. This reformulated query is then matched to an optimized execution process selected from a plurality of predefined execution processes. Finally, the reformulated query and matching optimized execution process are provided as an optimized version of the crowd-sourced poll for execution via a computer-based crowd-sourcing backend.

Optimizing efficiency and cost of crowd-sourced polling

An exemplary method includes providing an application that includes client-side code and server-side code, instrumenting the client-side code and the server-side code to generate timestamps, distributing the instrumented client-side code and the instrumented server-side code and monitoring timestamps generated during execution of the application. In such a method, where timestamps generated by the client-side code and timestamps generated by the server-side code occur along a common timeline, a developer can monitor performance of the distributed application. Other exemplary methods, systems, etc., are also disclosed.

Data-driven profiling for distributed applications

Disclosed herein are systems and methods for detecting script code malware and generating signatures. A plurality of script code samples are received and transformed into a plurality of tokenized samples. The tokenized samples are based on syntactical elements of the plurality of script code samples. One or more clusters of samples are determined based on similarities in different ones of the plurality of tokenized samples, and known malicious code having a threshold similarity to a representative sample of the cluster of samples is identified. Based on the identifying, the cluster of samples is identified as malicious. Based at least on respective ones of the plurality of tokenized samples associated with the cluster of samples, a generalized code signature usable to identify the script code samples in the cluster of samples is generated.

Code labeling based on tokenized code samples

The claimed subject matter includes techniques for processing gestures. An example method includes receiving a gesture from an application. The gesture includes one or more primitives from a language that is domain-specific to gestures. The method also further includes receiving skeletal data from a motion detection system. The method also includes comparing the skeletal data with the gesture from the application in a runtime module. The method also further includes sending a gesture event to the application.

Gesture processing using a domain-specific gesture language

A processing system for distributed multi-tier applications is provided. The system includes a server component that executes a replica of a client-side application, where a client component executes the client-side application. The client component captures events from the client-side application and transmits the events to the replica to validate the computational integrity security of the application.

Automatically securing distributed applications

An automatic context-sensitive sanitization technique detects errors due to the mismatch of a sanitizer sequence with a browser parsing context. A pre-deployment analyzer automatically detects violating paths that contain a sanitizer sequence that is inconsistent with a browsing context associated with outputting an untrusted input. The pre-deployment analyzer determines a correct sanitizer sequence which is stored in a sanitization cache. During the runtime execution of the web application, a path detector tracks execution of the web application in relation to the violating paths. The correct sanitizer sequence can be applied when the runtime execution follows a violating path.

Automatic context-sensitive sanitization

The subject disclosure is directed towards crowd-based approach to boosting the correctness of a computer program. Results from candidate programs obtained from a first crowd and which may be blended with one another into synthesized programs are sent to a second crowd for evaluation. Based upon the results, a training set evolves and programs are filtered based upon fitness. The process of blending and fitness evaluation with an evolved training set may be iteratively repeated to find a most fit program.

Program boosting including using crowdsourcing for correctness

A security engine may be selected from a plurality of security engines to apply one or more security mechanisms to a section of source code of an application. In some cases, the section of source code may be identified by one or more security mechanism identifiers included in the source code. The security engine may generate machine-readable code that corresponds to the section of source code for which the one or more security mechanisms are to be applied. The machine-readable code may be executed on a plurality of computing devices. In one implementation, applying the security mechanisms to the section of source code may include producing zero-knowledge proofs of knowledge for the section of source code.

Cryptographic mechanisms to provide information privacy and integrity

An 'AR Privacy API' provides an API that allows applications and web browsers to use various content rendering abstractions to protect user privacy in a wide range of web-based immersive augmented reality (AR) scenarios. The AR Privacy API extends the traditional concept of 'web pages' to immersive &#x201c;web rooms&#x201d; wherein any desired combination of existing or new 2D and 3D content is rendered within a user's room or other space. Advantageously, the AR Privacy API and associated rendering abstractions are useable by a wide variety of applications and web content for enhancing the user's room or other space with web-based immersive AR content. Further, the AR Privacy API is implemented using any existing or new web page coding platform, including, but not limited to HTML, XML, CSS, JavaScript, etc., thereby enabling existing web content and coding techniques to be smoothly integrated into a wide range of web room AR scenarios.

Protecting privacy in web-based immersive augmented reality

A profiling service may determine, local to a device, user profile attributes associated with a device user based on interaction of the device user with the device, based on device-local monitoring of device user interactions with the device, and may store the user profile attributes in a memory. The profiling service may be configured as an augmentation to a device operating system of the device. A profile exposure component may manage exposure of information associated with the user profile attributes to applications operating locally on the device, without exposure to the applications or to third parties of information determined as sensitive to the device user.

Combining personalization and privacy locally on devices

A 'code splitting tool' provides various techniques for automatically analyzing and rewriting existing browser-based applications to introduce dynamic code loading into those applications thereby improving perceived application responsiveness. Structural elements of application code (including functions, classes, etc.) are broken into small 'stubs' with corresponding bodies. Rewritten applications then initially transfer only the portion of the code (including some combination of stubs and bodies) to the client as necessary for initial application execution. Additional stubs and/or bodies are then transferred either on-demand at runtime or in the background. Automated code rewriting proceeds without requiring any application-specific knowledge or changes to existing code prior to code rewriting. Further, the code splitting tool can tailor code rewriting to specific computing devices (computers, PDA's, cell phones, etc.), specific network conditions, and/or specific users, through an automated training process that creates clusters that control code downloads to optimize perceived application responsiveness.

Automated code splitting and pre-fetching for improving responsiveness of browser-based applications

Functionality is described herein by which plural environment-sensing applications capture information from an environment in a fine-grained and least-privileged manner. By doing so, the functionality reduces the risk that private information that appears within the environment will be released to unauthorized parties. Among other aspects, the functionality provides an error correction mechanism for reducing the incidence of false positives in the detection of objects, an offloading technique for delegating computationally intensive recognition tasks to a remote computing framework, and a visualization module by which a user may inspect the access rights to be granted (or already granted) to each application.

Managing access by applications to perceptual information

Various embodiments are disclosed that relate to the automated identification of one or more computer program functions for potentially placing on a remote computing device in a split-computational computing environment. For example, one disclosed embodiment provides, on a computing device, a method of determining a factorable portion of code to locate remotely from other portions of the code of a program to hinder unauthorized use and/or distribution of the program. The method includes, on a computing device, receiving an input of a representation of the code of the program, performing analysis on the representation of the code, the analysis comprising one or more of static analysis and dynamic analysis, and based upon the analysis of the code, outputting a list of one or more functions determined from the analysis to be candidates for locating remotely.

Identifying factorable code

The subject disclosure is directed towards automated, static analysis-based program code processing that detects unprotected resource accesses by applications, that is, those that do not provide proper opt-in consent dialogs (prompts). In one aspect, consent prompt code is automatically inserted into the program code to protect such unprotected access points. Also described are program representation graph construction and processing, a dominator node-based approach to determine placement points for inserting consent prompt code, and a backward search-based approach for inserting consent prompt code.

Automatic mediation of resource access in mobile applications

Growing community of inventors

Kirkland, WA, United States of America

Benjamin Livshits