There is a system for controlling access to an electronic device. This system can comprise at least one server having at least one microprocessor. There can be at least one remote device having at least one microprocessor, and at least one GPS location device, wherein the one remote device is configured to communicate a location of the at least one remote device. This remote device further comprises any one of at least one transceiver configured to communicate wirelessly, at least one biometric reader configured to read a biometric of a user and/or at least one hardware reader configured to read an identification piece. Thus, the electronic device is selectively unlocked via either an internal lock or via the server authenticating a location of the remote device, a Wifi signal of the remote device, a biometric reading of the remote device and a reading of the hardware reader of the remote device.

A two-step authentication system and method includes a location address and a non-visual identifier at the location address that is identified and verified via an electronic device. The electronic device may be a scan device at the location address that includes a unique identifier or may also be a GPS location at the address. The system uses one or more electronic devices to capture and verify the address for the delivery of a parcel along with the non-visual identifier assigned to the address location. Communication is provided to a user upon deliver.

Adapting specifications of an artificial intelligence (AI) ecosystem are adapted, using a computer, based on an existing AI ecosystem of a user. A login is received, at the computer having a remote-based account of a user, to a new AI ecosystem. Specifications are determined from an existing AI ecosystem of the user, and the specifications include preferences and historical data related to the existing AI ecosystem based on usage of existing machines. Adaptive functionality is derived, using the computer, for new machines in the new AI ecosystem. The adaptive functionality is based on the specifications including the preferences and the historical data for the existing AI ecosystem. The specifications including the adaptive functionality is applied to the new machines of the new AI ecosystem.

Aspects of the disclosure relate to a system that provides enhanced security of information transmitted by connected devices. The system may be used to request resources from members of a donee's virtual group. Donated funds or line of credit may be loaded to the donee's digital wallet with no link to any of the donee's personal accounts. The request for resources may utilize secure correspondence between the donee and the prospective donors. The secure correspondence may be locked and prevented from being forwarded or captured via a screenshot to ensure confidentiality. If an attempt is made to forward or copy the secure correspondence, the secure correspondence may be deleted. Donated funds/line of credit may be allocated for specific use, and may not be owned by the donee until used.

An object is to lower the ratio of the number of users of an authentication service to the number of users of an application which uses the authentication service. A state of a first application is obtained by executing a second application. Whether to perform authentication processing is determined according to the state of the first application by executing the second application. Moreover, an instruction to perform the authentication processing is issued by executing the first application or the second application in a case where it is determined that the authentication processing is to be performed.

Predictive modeling using statistical evaluation combined with federated learning is described to enable incident map creation while preserving anonymity and achieving fine granularity. Machine-learned models (116) are trained to infer when persons associated with individual user devices (102) do or do not have a condition. The models (116) are deployed to the user devices (102) and return generalized location data and aggregated statistics about inferences made by the models. A remote system collects the aggregated statistics (120) and builds an incidence map (122-1, 122-2) identifying hotspots and coldspots for the condition. The incidence map identifies affected regions, with fine granularity down to a neighborhood or street level. The subregion-level information is regularly updated as new inferences, and new aggregated statistics, are made. Hence, the incidence map (122-1, 122-2) is current and highly detailed.

The encrypted data analysis device includes a sorting unit that sorts by [Time Information] and then sorts by [User ID] an encrypted data set group including a plurality of encrypted data sets, each of the plurality of encrypted data sets including a [Location ID], the [User ID], and the [Time Information], an encoding unit that generates a [Flow], and encoding the [Location ID] extracted, and an equal sign determination unit that determines whether a [User ID] and another [User ID] adjacent to each other are equal, and when not equal, replaces a corresponding [Flow] with a [predetermined value that represents invalid].

A new generation “smart card” creates a severable invisible “bond” between the cardholder and the smart card itself where this trusted bond relationship is used to enhance and simplify the authentication process during the use. This new smart card is initiated and connected to a specific user using biometric information added to the card and the user using biometric information connects via a trusted bond with the card by pairing the biometric information which can be severed in one of multiple ways. The trusted bond with the smart card can be broken in one of multiple ways including disconnection from a network, distancing from the user, impact accelerometers, outside parameters, etc. The multi-function smart card also uses this established trusted bond with the user to simplify the authentication of the user for use of the card in encrypted computer network, ground security, or other retail and payment function.

State-of-the-art techniques hardly attempt to address controlled resource access problem in context of Basic Emergent Users (BEUs). Embodiments of the present disclosure provide a method and system for Proof of Work (POW) based protection of resources. The method includes using the POW for work done by BEUs in physical world and mapping it to digital world to generate crypto currency in terms of credit score, wherein an end user is eligible or authorized to use a resource of an entity to get a desired service if accumulated credit score is above a credit threshold. Gaining points to improve the credit score is challenging as it is based on percentage of compliance achieved by the BEU through actual work in accordance with a compliance protocol. Further, the method includes authenticating the authorized user based on a set of questions with increasing difficulty, derived based on a culture graph.

Systems herein allow a digital assistant to make requests to applications, such as third-party applications, that access data in an enterprise mobility management (“EMM”) system. The digital assistant can link to a portal application and receive a token that identifies a user. A remote application on a user device can establish a session with the portal application as part of a single sign on (“SSO”). The session can identify the same user. The portal application can then link the digital assistant to the remote application. When the digital assistant makes a request to the portal application, a notification can be pushed to the remote application. The user can confirm the request, establishing an authorized session during which time the digital assistant can make additional requests to the portal application. The portal application can service the requests by accessing third-party applications available through the portal application and authorized for access by the SSO.