Abstract: A computer security method for analyzing data sets for remediating security incidents in a cloud-based response system. Logs of data are retrieved from a computer network. The logs of data are parsed and filtered into the data sets. The logs of data are filtered by creating an event timeline of the computer network by identifying events from the data sets. An event timeline of the computer network is analyzed from the data sets to identify whether data from the logs of data is accessed by an unauthorized computing system. Based on a result of the identification of whether data from the logs of data is accessed by an unauthorized computing system, a set of suggested tasks, wherein each suggested task of the set of suggested tasks represents techniques for isolating a host connected to the computer network if the data has been compromised.

Abstract: Placing an event into a particular cluster can allow various inferences about the event. A new payment transaction that looks similar to a previously identified cluster of mostly fraudulent payment transactions, for example, may be higher risk. The present disclosure includes structural data improvements to the way that online clustering of events (which may include web events and not just payment transactions) occurs. A new event can be classified into a particular segment very quickly using feature table searching, which can allow for better decision making when a short timeframe is required (e.g. transaction processing, online advertising, etc.).

Abstract: There are provided systems and methods for a dynamic value appended to cookie data for fraud detection and step-up authentication. A service provider, such as an electronic transaction processor for digital transactions, may utilize computer cookies for authentication and/or login for a user account. In order to further secure cookies from being compromised and used by malicious parties for fraudulent account access, the service provider may add or append a dynamic value that changes at each subsequent login to the computer cookie. The dynamic value may be used so that if a computer cookie is misappropriated, only one device may use the cookie once without the cookie updating and invalidating the cookie with another device or application on the device. Thereafter, when a login is requested, the dynamic value is matched to an expected value by the service provider when determining whether to authenticate the device.

Abstract: An intracranial access device includes a housing having an operator-facing side and a patient-facing side and an opening therethrough extending from the operator-facing side to the patient-facing side. The device further includes at least one fastener configured to secure the device to a cranium of a patient. The device further includes a drill mounted to a surface of the housing and a cauterizer. The device may further include a number of sensors arranged on the patient-facing side of the housing and configured to identify a hemorrhage location.

Abstract: A device may include a processor configured to obtain a time series of documents; determine query scores for particular documents of the time series of documents based on a set of query terms; and determine time scores for the particular documents based on timestamps associated with the particular documents. The processor may be further configured to compute document relevancy scores for the particular documents based on a combination of the query scores and the time scores for the particular documents; order the particular documents based on the computed relevancy scores; and generate a document summary by applying a document summarizer applied to the ordered particular documents.

Abstract: Methods and apparatus for automatically preparing food for consumption in which preparation comprises dispensing, manipulation, heating, and other operations using a wide variety of ingredients. The methods and apparatus described use ingredients efficiently and maintain their quality, while avoiding contact between ingredients and apparatus to minimize the risk of system contamination.

Abstract: A computer system receives a goal for an environment, wherein the environment corresponds to at least one webpage. The computer system receives one or more classifiers corresponding to the environment, wherein the one or more classifiers provide information corresponding to a current webpage and information corresponding to one or more previous actions taken by a web crawler. The computer system identifies a recommended next action based on the one or more classifiers. The computer system transmits the recommended next action to the web crawler to cause the web crawler to perform the recommended next action.

Abstract: A device may include a processor configured to obtain a time series of documents; determine query scores for particular documents of the time series of documents based on a set of query terms; and determine time scores for the particular documents based on timestamps associated with the particular documents. The processor may be further configured to compute document relevancy scores for the particular documents based on a combination of the query scores and the time scores for the particular documents; order the particular documents based on the computed relevancy scores; and generate a document summary by applying a document summarizer applied to the ordered particular documents.

Abstract: Methods and systems are provided for calibrating a medical imaging system. In one example, a method includes identifying a calibration vector to be updated based on an artifact in an image acquired with the medical imaging system, determining calibration data to be obtained with the medical imaging system based on the calibration vector, obtaining the calibration data with the medical imaging system, and updating the calibration vector based on the calibration data.

Abstract: Indexing application actions for voice-based execution is provided. An indexer of a device receives, from an application executed by the device, an indication of an action and a deep link corresponding to the action declared by the application via an application programming interface. The indexer accesses an index stored in the memory of the device that is accessible to a plurality of applications. The indexer inputs, into a location in the index, the action and the deep link with a cryptographic token that prevents access to the deep link by unauthorized applications. A digital assistant of the device receives a voice query detected by a microphone and parses the voice query to determine the action. The digital assistant identifies in the index the deep link corresponding to the action. The digital assistant invokes, with the cryptographic token, the deep link to cause the application to perform the action.

Abstract: Methods and apparatus for automatically preparing food for consumption in which preparation comprises dispensing, manipulation, heating, and other operations using a wide variety of ingredients. The methods and apparatus described use ingredients efficiently and maintain their quality, while avoiding contact between ingredients and apparatus to minimize the risk of system contamination.

Abstract: A method is provided that includes accessing, by a server provider server of a service provider, a database storing associations between network addresses and locations. Additionally, the method includes determining a subset of the database corresponding to a first network address, each association included in the subset corresponding to an association between the first network address and a respective location. The method also includes in response to determining that the subset of the database satisfies one or more clustering criteria, calculating a representative location corresponding to the first network address, and storing an association between the first network address and the representative location in a second database.

Abstract: Placing an event into a particular cluster can allow various inferences about the event. A new payment transaction that looks similar to a previously identified cluster of mostly fraudulent payment transactions, for example, may be higher risk. The present disclosure includes structural data improvements to the way that online clustering of events (which may include web events and not just payment transactions) occurs. A new event can be classified into a particular segment very quickly using feature table searching, which can allow for better decision making when a short timeframe is required (e.g. transaction processing, online advertising, etc.).

Abstract: A computer system receives a goal for an environment, wherein the environment corresponds to at least one webpage. The computer system receives one or more classifiers corresponding to the environment, wherein the one or more classifiers provide information corresponding to a current webpage and information corresponding to one or more previous actions taken by a web crawler. The computer system identifies a recommended next action based on the one or more classifiers. The computer system transmits the recommended next action to the web crawler to cause the web crawler to perform the recommended next action.

Abstract: There are provided systems and methods for a dynamic value appended to cookie data for fraud detection and step-up authentication. A service provider, such as an electronic transaction processor for digital transactions, may utilize computer cookies for authentication and/or login for a user account. In order to further secure cookies from being compromised and used by malicious parties for fraudulent account access, the service provider may add or append a dynamic value that changes at each subsequent login to the computer cookie. The dynamic value may be used so that if a computer cookie is misappropriated, only one device may use the cookie once without the cookie updating and invalidating the cookie with another device or application on the device. Thereafter, when a login is requested, the dynamic value is matched to an expected value by the service provider when determining whether to authenticate the device.

Abstract: Placing an event into a particular cluster can allow various inferences about the event. A new payment transaction that looks similar to a previously identified cluster of mostly fraudulent payment transactions, for example, may be higher risk. The present disclosure includes structural data improvements to the way that online clustering of events (which may include web events and not just payment transactions) occurs. A new event can be classified into a particular segment very quickly using feature table searching, which can allow for better decision making when a short timeframe is required (e.g. transaction processing, online advertising, etc.).

Abstract: Machine learning techniques are used in combination with graph data structures to perform automated classification of accounts. Graphs may be constructed using a seed node and then expanded outward to second-degree nodes and third-degree nodes that are connected to a seed user account node via direct interaction between the accounts. Characterization information regarding the interaction between accounts can be stored in the graph (e.g., quantity of interactions, types of interactions) as well as other metrics and metadata. A classifier, using random forest or another technique, may be trained using a number of different graphs that can then be used to reach a determination as to whether a user account falls into one particular category or another. These techniques can identify accounts that may be violating terms of service, committing a security violation, and/or performing illegal actions in a way that is not ascertainable from human analysis.