13 results about "Watch list" patented technology

The present disclosure relates to a system to proactively detect in real time one or more threats in crowded areas. The present disclosure presents a proactive system for real-time threat detection in crowded areas. Utilizing a network of imaging sensors and advanced machine learning algorithms, the system identifies suspicious individuals, objects, and behavioral patterns within a predefined area. The system detects potential threats such as individuals on watch lists, suspicious objects like unattended bags, and abnormal behaviors indicative of security risks, by continuously monitoring and analyzing images and video feeds. Upon detection, the system promptly notifies authorities, providing detailed information on threat location, suspected individuals, and behavioral analysis. Privacy-preserving measures, including encryption of facial recognition data, ensure compliance with privacy regulations. The present disclosure offers a scalable, efficient, and automated solution to enhance security measures, reduce response times, and safeguard public safety in dynamic urban environments.

Systems and methods discussed herein relate to a system for detecting and preventing fraudulent transactions through collecting requests for website access, stored-card trades and sales, and transactions using physical or electronically issued credit, debit, stored-value, and other cards. The fraud detection system not only flags individual transactions, but is also configured to dynamically track and update banned / watch lists associated with request artifacts and cards in order to catch and prevent individual actors as well as BOTs, at least by adjusting the thresholds used to evaluate risk scores and what is placed on the banned / watch lists based upon requests received as well as information from financial institutions, merchants, government agencies, and watchdog groups. The system is also configured to provide information to those groups.

In some embodiments, an electronic device displays a representation of a plurality of sets of channels along a first axis in a user interface, and in response to receiving a selection of the set, displays a representation of channels associated with the selected plurality of sets of channels along the first axis. In some embodiments, an electronic device displays a user interface for viewing subscribed and unsubscribed channels and for subscribing to unsubscribed channels. In some embodiments, an electronic device displays a navigation bar for navigating between live content, watch list content, on-demand content, channels, and search content. In some embodiments, an electronic device displays an array-based content guide.

One or more identifications of one or more newly observed domains are received. The one or more newly observed domains are store in a newly observed domain watch list for a specified watch interval. One or more automatic analyses are periodically performed to determine whether any newly observed domain stored in the newly observed domain watch list for the specified watch interval is determined to be suspicious or malicious.

The present disclosure relates to a system to proactively detect in real time one or more threats in crowded areas. The present disclosure presents a proactive system for real-time threat detection in crowded areas. Utilizing a network of imaging sensors and advanced machine learning algorithms, the system identifies suspicious individuals, objects, and behavioral patterns within a predefined area. The system detects potential threats such as individuals on watch lists, suspicious objects like unattended bags, and abnormal behaviors indicative of security risks, by continuously monitoring and analyzing images and video feeds. Upon detection, the system promptly notifies authorities, providing detailed information on threat location, suspected individuals, and behavioral analysis. Privacy-preserving measures, including encryption of facial recognition data, ensure compliance with privacy regulations. The present disclosure offers a scalable, efficient, and automated solution to enhance security measures, reduce response times, and safeguard public safety in dynamic urban environments.

The present disclosure relates to a system to proactively detect in real time one or more threats in crowded areas. The present disclosure presents a proactive system for real-time threat detection in crowded areas. Utilizing a network of imaging sensors and advanced machine learning algorithms, the system identifies suspicious individuals, objects, and behavioral patterns within a predefined area. The system detects potential threats such as individuals on watch lists, suspicious objects like unattended bags, and abnormal behaviors indicative of security risks, by continuously monitoring and analyzing images and video feeds. Upon detection, the system promptly notifies authorities, providing detailed information on threat location, suspected individuals, and behavioral analysis. Privacy-preserving measures, including encryption of facial recognition data, ensure compliance with privacy regulations. The present disclosure offers a scalable, efficient, and automated solution to enhance security measures, reduce response times, and safeguard public safety in dynamic urban environments.

In some embodiments, an electronic device displays a representation of a plurality of sets of channels along a first axis in a user interface, and in response to receiving a selection of the set, displays a representation of channels associated with the selected plurality of sets of channels along the first axis. In some embodiments, an electronic device displays a user interface for viewing subscribed and unsubscribed channels and for subscribing to unsubscribed channels. In some embodiments, an electronic device displays a navigation bar for navigating between live content, watch list content, on-demand content, channels, and search content. In some embodiments, an electronic device displays an array-based content guide.

Disclosed are techniques for identifying users within an enterprise who pose heightened security risks to the enterprise. A method can include receiving, by a computing system, information about users in the enterprise, grouping the users into groups based on at least one grouping feature and the user information, the at least one grouping feature including, for each of the users, behavior, activity, role, department, region, role-based risk score, event-based risk score, and / or composite risk score, identifying, for each group, normalized behavior of users in the group, generating, for each user in each group, a composite risk score based on deviation of the user's activity from the normalized behavior of the group, identifying, for each group, a subset of users in the group to be added to a watch list, and adding the subset of users to the watch list.

The systems described herein provide a system for presenting affordances for applications installable on electronic devices. In response to selection of one or more of the affordances, a content affordance of content provided by a corresponding application is provided.

The application discloses a low-power-consumption circuit applied to an electronic duty roster and an implementation method thereof. The circuit comprises at least a control unit, a switching unit and a display unit. The control unit is connected with the switching unit. The switching unit is connected with the display unit. The switching unit comprises a switching module, a sampling module and a charging module. The switching module is connected with the sampling module. The switching module is connected with the charging module. The sampling module is connected with the charging module in parallel. The application changes the current of the sampling module by changing the high and low levels, realizes the target output of the sampling module, reduces the power consumption of the circuit, and protects the components in the circuit, improves the service life of the product, and reduces resource waste when the high and low levels are dynamically changed. The application can be applied to the technical field of electronic circuits.

The present invention discloses a method for detecting abnormal electricity consumption behavior applicable to a new energy distribution network. Based on historical data of user stations, feature extraction is performed to obtain a sample set of a network for screening suspicious electricity consumption behavior. Three-layer deep learning screening networks are respectively constructed according to the coupling degree of data in a training set, and training of the suspicious behavior screening network is completed based on the sample set. The historical abnormal data is used as a sample set for false alarm identification, and an abnormal false alarm identification model is established. Data in an electricity collection system is input into a suspicious behavior screening network after feature extraction, and when the output abnormal state value exceeds a threshold, the user data is transmitted to an abnormal false alarm identification model. The abnormal false alarm identification model identifies whether there is an abnormal false alarm in the suspicious electricity consumption behavior of the user according to the characteristics of the electricity consumption data, and if so, the user is included in a monitoring list. The method is executed again for users in the monitoring list, and if the output abnormal state value still exceeds the threshold, it is determined that the user has abnormal electricity consumption behavior.

Systems and methods are provided for automatically creating and using a watch list using generative artificial intelligence. The systems and methods can include determining variants for a watch list of entities that are not allowed access to a senders computing system, and determining a similarity between the variants and the watch list to, e.g., determine which variants to add to the watch list. The systems and methods can include updating the watch list and transmitting back to the sender computers.

Methods and systems describe providing for dynamic syncing of aggregated media from streaming services. For each of a number of streaming services associated with a user, the system: receives a watch list of the user for the streaming service; based on the watch list, determines a playback bookmark for each of a subset of media provided via the streaming service; matches the playback bookmarks for the subset of media to analogous media within the aggregate streaming platform; assigns the playback bookmarks for the analogous media to a user profile associated with the user, such that a user may initiate playback of analogous media within the streaming service starting from the playback bookmark for that analogous media; and updates a content queue based on the analogous media with assigned playback bookmarks.