Abstract: Generation of a first prediction model is caused based on first training data, where the first prediction model enables determining whether an exploit to be developed for software vulnerabilities will be used in an attack. For each training instance in the first training data, the first prediction model is used to generate a score. Each training instance is added to second training data if the score is greater than a threshold value. The second training data is a subset of the first training data. Generation of a second prediction model is caused based on the second training data, where the second prediction model enables determining whether an exploit to be developed for software vulnerabilities will be used in an attack.

Abstract: Generation of a first prediction model is caused based on first training data, wherein the first prediction model enables determining whether an exploit to be developed for software vulnerabilities will be used in an attack. For each training instance in the first training data, the first prediction model is used to generate a scored. Each training instance is added to second training data if the score is greater than a threshold value. The second training data is a subset of the first training data. Generation of a second prediction model is caused based on the second training data, wherein the second prediction model enables determining whether an exploit to be developed for software vulnerabilities will be used in an attack.

Abstract: Generation of a first prediction model is caused based on first training data, where the first prediction model enables determining whether an exploit to be developed for software vulnerabilities will be used in an attack. For each training instance in the first training data, the first prediction model is used to generate a score. Each training instance is added to second training data if the score is greater than a threshold value. The second training data is a subset of the first training data. Generation of a second prediction model is caused based on the second training data, where the second prediction model enables determining whether an exploit to be developed for software vulnerabilities will be used in an attack.

Abstract: Generation of a first prediction model is caused based on first training data, where the first prediction model enables determining whether an exploit to be developed for software vulnerabilities will be used in an attack. For each training instance in the first training data, the first prediction model is used to generate a score. Each training instance is added to second training data if the score is greater than a threshold value. The second training data is a subset of the first training data. Generation of a second prediction model is caused based on the second training data, where the second prediction model enables determining whether an exploit to be developed for software vulnerabilities will be used in an attack.

Abstract: The subject disclosure pertains to secure and anonymous data storage and access. More particularly, encryption methods and mechanisms are provided in conjunction with one or more blobs, identities, and guards to implement one or more layers of indirect encryption. Generation of these components can be accomplished without including or pointing to any personally identifiable information about a user. Accordingly, a user can store sensitive data securely and anonymously on a server or like storage system. Such data can also be roamed, recovered, and synchronized securely from a plurality of computers at least because the data is centrally located.

Abstract: The claimed subject matter provides a system and/or a method that facilitates generating and displaying a graphical item. An interface component can facilitate receipt of data related to the graphical item associated with an operating system. An enhancement component can leverage a browser to generate the graphical item with an opaque portion and at least one of a translucent portion and a transparent portion.

Abstract: A method to allocate memory, in response to application requests, for a compact data structure having location data and a trailer section is provided. The trailer section of the compact data structure is checked to determine an offset for listings and indices representing the location data. Upon determining the offset, the listings and indices are loaded into memory and responses to the application requests are generated by utilizing the listings and indices stored in the memory.

Abstract: A web accelerator reduces web latency experienced when retrieving and displaying content. The web accelerator includes an interceptor component, a resolver component, a predictor component and a tracer component. The interceptor component captures web requests. The web requests are tracked by the tracer component, which logs the web requests to generate a statistical model that reflects web browsing activity. The predictor component utilizes the statistical model to predict subsequent web requests, and the resolver component resolves hostnames specified in the subsequent web requests and pre-loads content specified in the subsequent web requests when there is a strong likelihood that a user is interested in the content specified in the subsequent web requests.

Abstract: A schema-based service for Internet access to per-user services data, wherein access to data is based on each user's identity. The service includes a schema that defines rules and a structure for each user's data, and also includes methods that provide access to the data in a defined way. The services schema thus corresponds to a logical document containing the data for each user. The user manipulates (e.g., reads or writes) data in the logical document by data access requests through defined methods. In one implementation, the services schemas are arranged as XML documents, and the services provide methods that control access to the data based on the requesting user's identification, defined role and scope for that role. In this way, data can be accessed by its owner, and shared to an extent determined by the owner.

Abstract: A method and system for dynamically configuring a server computer is provided. A global configuration file is utilized to configure a server computer on a per request basis. When a request is received at a server computer embodying aspects of the present invention, the server computer dynamically configures itself utilizing the contents of a global configuration file. The global configuration file contains configuration settings that may or may not be utilized by the server computer in configuring itself. To determine if particular configuration settings should be utilized by the server computer in configuring itself, the server computer parses rules also contained in the global configuration file. If a rule is evaluated as true, configuration settings associated with the rule are used by the server computer when configuring itself. The server computer can then respond to the request utilizing its dynamic configuration.

Abstract: Microneedle devices with microneedles having a truncated tapered shape are disclosed. The microneedles of microneedle devices may also have a controlled aspect ratio. Microneedle delivery apparatus are disclosed that include drivers designed to deliver microneedles at velocities that may enhance perforation of the stratum corneum while limiting the sensation of pain experienced at the delivery site.