Carnegie Mellon University

Wombat Security Technologies, Inc.

Proofpoint, Inc.

Jason I Hong

Norman Sadeh-Koniecpol

Kurt Wescoe

Jason Brubaker

Justin Cranshaw

Raz Schwartz

Trevor Tyler Hawthorn

Nathan Miller

Haojian Jin

Swarun Kumar Suresh Kumar

Jeff Losapio

Jingxian Wang

Eiji Hayashi

Zhijian Yang

Various embodiments assess security risks of users in computing networks. In some embodiments, an interaction item is sent to an end user electronic device. When the end user interacts with the interaction item, the system collects feedback data that includes information about the user's interaction with the interaction item, as well as technical information about the electronic device. The feedback is compared to a plurality of security risk scoring metrics. Based on this comparison, a security risk score for the user with respect to a computing network.

Assessing security risks of users in a computing network

Provided is a system and method for heating an item in a microwave oven. The method includes capturing, with at least one electromagnetic field sensor, at least one electromagnetic field measurement of a microwave chamber, each electromagnetic field measurement of the at least one electromagnetic field measurement corresponding to a region in the microwave chamber, generating an electromagnetic field map of the microwave chamber based on the at least one electromagnetic field measurement, capturing, with at least one sensor, a plurality of thermal measurements of the item being heated in the microwave chamber, each thermal measurement of the plurality of thermal measurements corresponding to a region on the item, and controlling at least one of a position of the item and the electromagnetic field while the item is being heated in the microwave chamber based on the electromagnetic field map and the plurality of thermal measurements.

System and method for heating an item in a microwave oven

Computer-based systems and methods for discovering neighborhood clusters in a geographic region, where the clusters have a mix of venues and are determined based on venue check-in data. The mix of venues for the clusters may be based on the social similarity between pairs of venues; or emblematic of certain neighborhood typologies; or emblematic of temporal check-in pattern types; or combinations thereof. The neighborhood clusters that are so discovered through venue-check in data could be used for many commercial and civic purposes.

Discovering neighborhood clusters and uses therefor

Provided is a system, method, and apparatus for tracking a body. The method includes communicating at least one activation signal to each RF transponder of a first array and a second array, receiving a plurality of response signals from the first array and the second array, the plurality of response signals comprising a response signal for each RF transponder of the first array and the second array, determining a difference in distances between the antenna and each RF transponder of the first array and each transponder of the second array based at least partially on at least one corresponding response signal of the plurality of response signals, and determining a relative location of the first portion of the body and the second portion of the body.

System and method for tracking a body

A method, system, and computer program product is provided for tracking the shape of a surface. The method includes generating a first plurality of surface models based on the surface, each surface model associated with surface parameter values and representing a different shape, determining an estimated position of the plurality of RF transponders on each surface model of the first plurality of surface models, communicating at least one activation signal to the plurality of RF transponders arranged on the surface, the surface comprising an unknown shape, receiving a plurality of response signals from at least a subset of the plurality of RF transponders, determining radio environment parameters for each surface model of the first plurality of surface models, and determining at least one selected surface model of the first plurality of surface models.

System and method for tracking a shape

A system assesses the susceptibility of an electronic device user to a cybersecurity threat by sensing a user action with respect to the electronic device. The system maps the sensed data to a training needs model to determine whether the sensed data corresponds to a pattern associated with a threat scenario in the training needs model. When the system determines that the sensed data corresponds to a pattern associated with a threat scenario in the training needs model, identify a cybersecurity threat scenario for which the user is at risk, and use the training needs model to estimate susceptibility of the user to the cybersecurity threat scenario.

Context-aware cybersecurity training systems, apparatuses, and methods

A system for automatic authentication of a user to allow access to websites and physical devices which provides tiered levels of security and defines an API protocol for exchange of authentication credentials.

Unified authentication management system

A system assesses the susceptibility of an electronic device user to a cybersecurity threat by identifying information relating to the user of an electronic device, selecting a mock attack, and causing the mock attack to be deployed to the user so that the user receives the mock attack in the user's regular context of use of the electronic device. When a sensor detects a user action that the user has interacted with the electronic device in response to the mock attack, the system will record the sensed user action and use the sensed user action to determine the susceptibility of the user to a cybersecurity threat. In some embodiments, the lack of user action in response to a mock attack also may be used to determine the user's susceptibility to a cybersecurity threat.

Mock attack cybersecurity training system and methods

A training system senses a user action that may expose the user to a threat, such as a cybersecurity threat. The user action may be in response to a mock attack delivered via a messaging service, a wireless communication service, a fake malware application or another device, service, system or mechanism. The system selects a training action from a collection of available training actions and causes the training action to be delivered to the user.

Growing community of inventors

Pittsburgh, PA, United States of America

Jason I Hong