System and method for securing, perfecting and accelerating biometric identification via holographic environmental data

Abstract

An electronic platform/system and method that uses electronic data to protect itself by realizing where an individual's device is and where it is being accessed from. As the internet expands into the physical world, with every device being IP enabled and addressable, the geographic proximity, network proximity, proximity to the access point of the internet, the authentication, encryption and presentation and flow of data can be linked to an increasingly addressable and measurable physical reality, a moment in time and a proximity to other data and objects using the system and method. The data itself is IP accessible in the form of IP addressable storage devices, and subject to the same techniques. Geographic, chronological and addressable interrelationship of the data as it is packetized and distributed, and the devices as they communicate, form a fabric. In total, a holographic layer of authorization, encryption, and distribution of data can be created by spanning the fabric of IP addressable objects and data. As the number of types of these devices proliferate, it becomes geometrically more complex to replicate the local fabric. A unique encryption key, access method, authentication method, and data distribution framework is disclosed. This unique key can further be utilized to subset biometric identification such that the number of biometric signatures to be compared may be minimized, potentially down to one, thereby geometrically speeding up biometric identification while perfecting its security.

What is claimed is: 
     
         1 . A software-based method for identifying an electronic network access point associated with an electronic device of an individual where the electronic device is attempting to store or access data, comprising the steps:
 (a) identifying one or more physical electronic devices associated with the electronic device of the individual that are communicating on a network access point;   (b) forming a holographic map of interconnected data between the individual's electronic device and the one or more electronic devices identified in step (a); and   (c) identifying a unique location within a physical world, an IoT or Internet based on the holographic map formed in step (b).   
     
     
         2 . The software-based method of  claim 1  wherein the identifying in step (a) is accomplished by identifying conversations between the individual's electronic device and the one or more electronic devices sniffed across the network access point. 
     
     
         3 . The software-based method of  claim 1 , further comprising the step of using the holographic map as part of an identity authentication process for the individual. 
     
     
         4 . The software-based method of  claim 3  wherein the identity authentication process also includes one or more of the following protections: biometrics, physical protections and manually entered passwords. 
     
     
         5 . The software-based method of  claim 1  further comprising the step of leveraging the holographic map for encryption to form a basis of unique digital keys. 
     
     
         6 . The software-based method of  claim 1  wherein the unique location identified in step (c) represents a specific location in time and space that cannot be replicated without having all of the one or more physical electronic devices placed and communicating in an exact geometry as when identified in step (a). 
     
     
         7 . The software-based method of  claim 1  further comprising the step of determining by the electronic system how many times each of the physical electronic devices identified in step (a) has been previously electronically seen by the electronic system in connection with the individual. 
     
     
         8 . The software-based method of  claim 7  for electronic devices previously seen on multiple occasions by the electronic system; electronically attributing the previously seen electronic devices as electronic devices closely associated with the individual by the electronic system. 
     
     
         9 . A software-based method for earlier gathering of electronic data pertaining to a particular individual to be used for identifying or authenticating the individual for a transaction or other electronic activity in order to decrease the processing time required for identifying or authenticating the individual in connection with the transaction or other activity, comprising the steps of:
 (a) receiving electronic data from Internet of Things (“IoT”) devices associated with an individual via an application programming interface of an electronic system;   (b) determining by the electronic system whether any of the IoT devices have previously communicated with or sent electronic data to the electronic system in connection with the particular individual; and   (c) where the electronic system determines in step (b) that one or more IoT devices has previously communicated or sent electronic data in connection with the particular individual, automatically electronically prefetching previously saved biometric history data for the individual such that the previously saved biometric history data is available earlier for use in connection with electronically identifying or authenticating the individual by the electronic system for the transaction or other activity.   
     
     
         10 . The software-based method of  claim 9  wherein step (b) comprises comparing the received IoT device data to previously saved electronic data for electronic devices previously seen by the electronic system for the individual for use in predicting future actions by the individual. 
     
     
         11 . The software-based method of  claim 9  further comprising the steps of determining how many times any IoT device associated with the individual from step (a) had been previously electronically seen by the electronic seen and determining a total score based on how many IoT devices were associated with the individual in step (a) and how many times the IoT devices were previously seen by the electronic system. 
     
     
         12 . The software-based method of  claim 11  further comprising the steps of parsing the number of IoT devices associated with the individual and the number of previous electronic seens by the electronic system of the IoT devices by a learning neural network. 
     
     
         13 . The software-based method of  claim 12  further comprising the step of determining an authentication or identification confidence level for the individual by the electronic system based on the IoT device data. 
     
     
         14 . . The software-based method of  claim 9  further comprising the step of using the IoT data and prefetched biometric data to reduce a number of profiles that the electronic system has to search or compare for authenticating or identifying the individual for the transaction or other activity 
     
     
         15 . A software-based method for earlier gathering of electronic data pertaining to a particular individual to be used for identifying or authenticating the individual for a transaction or other activity in order to decrease the processing time required for identifying or authenticating the individual, comprising the steps of:
 (a) receiving electronic data from Internet of Things (“IoT”) devices associated with an individual for use by an electronic system;   (b) electronically saving the electronic data and any biometric data for the individual;   (c) based on prior conduct of the individual known to the electronic system obtained from the electronic data saved in step (b), determining by the electronic system an anticipated future point in time that the individual will be at a physical or virtual location; and   (d) automatically electronically prefetching the biometric data saved in step (b) prior to the anticipated future point in time such that the biometric data is already gathered or retrieved for use in electronically identifying or authenticating the user at the physical or virtual location in connection with a transaction or other activity involving the individual.   
     
     
         16 . The software-based method of  claim 15  further comprising the step of using the electronic data and prefetched biometric data to reduce a number of profiles that the electronic system has to search or compare for authenticating or identifying the individual for the transaction or other activity. 
     
     
         17 . The software-based method of  claim 15  further comprising the steps of determining by the electronic system whether any of the IoT devices have previously communicated with or sent electronic data to the electronic system in connection with the particular individual and using any data or information of prior communication between any of the IoT devices and the electronic system in connection with the determinations made in step (c). 
     
     
         18 . The software-based method of  claim 15  wherein step (c) comprises comparing saved history for IoT devices associated with the individual and returning a confidence metric. 
     
     
         19 . The software-based method of  claim 15  further comprising the step of comparing current received biometric data for an individual at the physical or virtual location with the biometric data prefetched in step (d).