1050 results about "Behavioral analytics" patented technology

An approach is provided for supporting network security. A dataflow destined for an end user network is received. The dataflow is sampled according to a predetermined sampling rate. Flow information is generated from the sampled dataflow. The flow information is forwarded to a collector device for remote behavioral analysis to determine a behavioral profile indicative of a Denial of Service (DoS) attack (e.g., distributed Denial of Service (DDOS) attack) of the end user network.

The present invention is a method and system for automatically analyzing a category in a plurality of the categories in a physical space based on the visual characterization, such as behavior analysis or segmentation, of the persons with regard to the category. The present invention captures a plurality of input images of the persons in the category by a plurality of means for capturing images. The present invention processes the plurality of input images in order to understand the shopping behavior of the persons with the sub-categories of the category and analyzes the level of engagement and decision process at the sub-category level. The processes are based on a novel usage of a plurality of computer vision technologies to analyze the visual characterization of the persons from the plurality of input images. The physical space may be a retail space, and the persons may be customers in the retail space.

The invention discloses an information pushing system of a WiFi (wireless fidelity) terminal and an implementation method thereof. The system comprises a WiFi signal collector, a WiFi signal processing module, a WiFi indoor positioning module, a customer activity analyzing and data mining module, a user personality file database, an advertisement information storage database, an advertisement putting and matching engine and a WiFi logging portal module. The system is suitable for all terminals with the WiFi function, such as mobile phones, PADs (personal access device) and PCs (personal computer), and different software platforms, such as Andriod, wP, iOS, Windows, MAC OS and Linux, the WiFi terminals do not need any software modification and updating, and the applicable range is wide. The possible hobby of a consumer is judged through data analysis and mining, and the real-time and on-site precise marketing is realized for target users, so on one hand, the experience of the user consuming in business places is improved, and on the other hand, the commercial value of sellers and factories is improved.

Transaction-based behavioral profiling, whereby the entity to be profiled is represented by a stream of transactions, is required in a variety of data mining and predictive modeling applications. An approach is described for assessing inconsistency in the activity of an entity, as a way of detecting fraud and abuse, using service-code information available on each transaction. Inconsistency is based on the concept that certain service-codes naturally co-occur more than do others. An assessment is made of activity consistency looking at the overall activity of an individual entity, as well as looking at the interaction of entities. Several approaches for measuring consistency are provided, including one inspired by latent semantic analysis as used in text analysis. While the description is in the context of fraud detection in healthcare, the techniques are relevant to application in other industries and for purposes other than fraud detection.

A computer system is configured to administer a psychological profiling test to a participant in a driver education program, or receive such profile from another source; to determine the participant's psychological profile. The system then selects a driver education program for the participant based on the profile. The system also selects a method of delivering the curriculum to the participant based on the profile. The system further selects a method of testing the participant's comprehension and retention of the curriculum material, also based on the profile. The system delivers the selected curriculum to the participant using the selected delivery method, verifies attendance or participation, and tests the participant's comprehension and retention of the curriculum material using the selected testing method.

A system for inferring intent of visitors to a Website has a visitor-tracking application executing from a digital medium coupled to a server hosting the Website, the server connected to a repository adapted to store data about visitor behavior, and an inference engine for processing the data to infer the intent of visitors. Visitor behavior relative to links is tracked, and intent of a visitor is inferred from one or both, or a combination of analysis of the behavior and deducing meaning for anchor text of links selected.

The present invention generally relates to financial data processing, and in particular it relates to credit scoring, consumer profiling, consumer behavior analysis and modeling. More specifically, it relates to risk modeling using the inputs of credit bureau data, size of wallet data, and, optionally, internal data.

Various embodiments provide systems and methods for preventing or detecting data leakage. For example, systems and methods may prevent or detect data leakage by profiling the behavior of computer users, computer programs, or computer systems. Systems and methods may use a behavior model in monitoring or verifying computer activity executed by a particular computer user, group of computer users, computer program, group of computer programs, computer system, or group of computer systems, and detect or prevent the computer activity when such computer activity deviates from standard behavior. Depending on the embodiment, standard behavior may be established on past computer activity executed by the computer user, or past computer activity executed by a group of computer users.

A computer system models human memory by deriving associations between objects, events, and the context of the computer user or users. These associations can be dynamically generated, changing depending on the behavior of the user and context. Examples of areas in which this system can be used include time management (e.g., a calendar that presents time-based groupings of objects), people management (e.g., use analysis of user communications to rank importance of people to the user, groupings, and associations between people/groups and other objects such as documents, email), and general computer management (e.g., use analysis of user behavior to identify important objects and objects that are related to a current focus and context of the computer user).

In embodiments, methods and systems for electronically capturing consumer location data for consumer behavior analysis may be provided. The location data may be gathered for one or more consumers from any suitable source. In some cases, the location data may be gathered using electronic devices associated with consumers, such as mobile phones. The gathered data may be analyzed to determine behavior patterns or other characteristics of the one or more consumers. Further, inferences or predictions about consumers may be derived based on the characteristics. The inferences and predictions may be the basis of consumer analytics supplied to a business or other entity.

The present invention generally relates to financial data processing, and in particular it relates to credit scoring, consumer profiling, consumer behavior analysis and modeling. More specifically, it relates to risk modeling using the inputs of credit bureau data, size of wallet data, and, optionally, internal data.

The present invention generally relates to financial data processing, and in particular it relates to credit scoring, consumer profiling, consumer behavior analysis and modeling. More specifically, it relates to risk modeling using the inputs of credit bureau data, size of wallet data, and, optionally, internal data.

The present invention generally relates to financial data processing, and in particular it relates to credit scoring, consumer profiling, consumer behavior analysis and modeling. More specifically, it relates to risk modeling using the inputs of credit bureau data, size of wallet data, and, optionally, internal data.

The present invention generally relates to financial data processing, and in particular it relates to credit scoring, consumer profiling, consumer behavior analysis and modeling. More specifically, it relates to risk modeling using the inputs of credit bureau data, size of wallet data, and, optionally, internal data.

In embodiments, methods and systems for consumer behavior analysis using electronically-captured consumer location data may be provided. The location data may be gathered for one or more consumers. The gathered data may be analyzed to determine behavior patterns or other characteristics of the one or more consumers. Further, inferences or predictions about consumers may be derived based on the characteristics. The inferences and predictions may be the basis of consumer analytics supplied to a business or other entity.

The present invention generally relates to financial data processing, and in particular it relates to credit scoring, consumer profiling, consumer behavior analysis and modeling. More specifically, it relates to risk modeling using the inputs of credit bureau data, size of wallet data, and, optionally, internal data.

New and improved techniques for a behavior analysis based DNS tunneling detection and classification framework for network security are disclosed. In some embodiments, a platform implementing an analytics framework for DNS security is provided for facilitating DNS tunneling detection. For example, an online platform can implement an analytics framework for DNS security based on passive DNS traffic analysis.

The present invention generally relates to financial data processing, and in particular it relates to credit scoring, consumer profiling, consumer behavior analysis and modeling. More specifically, it relates to risk modeling using the inputs of credit bureau data, size of wallet data, and, optionally, internal data.