# US 2021/0243596 A1 · Shared Anonymized Databases of Telecommunications-Derived Behavioral Data > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2021/0243596 A1 - Document ID: US20210243596A1 - Status: Published application - Kind: A1 - Application number: 16/330,749 - Filed: 2018-12-19 - Published: 2021-08-05 - Earliest claimed: 2018-10-26 - Assignees: Eureka Analytics Pte Ltd - Applicants: Eureka Analytics Pte Ltd - Inventors: Aloysius LIM; Ying LI - Web page: https://patentgrep.com/patent/US20210243596A1 ## CPC - H04W 12/02: Protecting privacy or anonymity, e.g. protecting personally identifiable information [PII] - H04W 24/08: Testing, {supervising or monitoring} using real traffic - G06F 11/3438: {monitoring of user actions (tracking the activity of the user H04L67/535)} - G06F 16/22: Indexing; Data structures therefor; Storage structures - G06F 16/2379: {Updates performed during online database operations; commit processing} - G06F 16/24558: {Binary matching operations} - G06F 16/2462: {Approximate or statistical queries} - G06F 16/955: using information identifiers, e.g. uniform resource locators [URL] - G06F 18/22: Matching criteria, e.g. proximity measures - G06F 18/24137: {Distances to cluster centroïds} - G06F 21/6245: {Protecting personal data, e.g. for financial or medical purposes} - G06F 21/6254: {by anonymising data, e.g. decorrelating personal data from the owner's identification} - H04W 8/02: Processing of mobility data, e.g. registration information at HLR [Home Location Register] or VLR [Visitor Location Register]; Transfer of mobility data, e.g. between HLR, VLR or external networks - H04W 8/18: Processing of user or subscriber data, e.g. subscribed services, user preferences or user profiles; Transfer of user or subscriber data - H04W 8/20: Transfer of user or subscriber data - H04W 12/69: Identity-dependent - H04W 24/10: Scheduling measurement reports {; Arrangements for measurement reports} - G06F 16/245: Query processing - G06F 16/2458: Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries - G06F 21/60: Protecting data - H04L 2463/121: Timestamp - H04W 16/22: Traffic simulation tools or models - H04W: WIRELESS COMMUNICATION NETWORKS (broadcast communication H04H; communication systems using wireless links for non-selective communication, e.g. wireless extensions H04M1/72) - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M) ## Abstract Telecommunications data may be summarized into mathematical statistics that may not correlate with conventional semantic attributes. Such statistics may be difficult to observe without access to the telecommunications data, and therefore may be much less susceptible to social engineering attacks or other privacy-related vulnerabilities. The mathematical statistics may represent first, second, or higher order behavior-related observations relating to subscribers physical movements, engagement of applications and web browsing on a mobile device, as well as usage and billing of a mobile device. The statistics may not correlate to semantic identifiers for subscribers, and therefore may be difficult to observe and therefore identify specific subscribers whose statistical summaries may be known. ## Claims ### Claim at position 1 1-4. (canceled) ### Claim 5 A system comprising: at least one computer processor; said at least one computer processor configured to perform a method comprising: receiving a first set of mathematically descriptive statistics of subscribers, said first set of mathematically descriptive statistics being semantic-free and being calculated from a first telecommunications network; receiving a second set of mathematically descriptive statistics of subscribers, said second set of mathematically descriptive statistics being semantic-free and being calculated from a second telecommunications network; aggregating said first set of mathematically descriptive statistics of subscribers and a said second set of mathematically descriptive statistics of subscribers into an aggregated database; receiving a query request; processing said query request against said aggregated database to generate a query response, said query response comprising data derived from said aggregated database; and transmitting said query response; said first set of mathematically descriptive statistics of subscribers having a first set of anonymized subscriber identifiers, and said second set of mathematically descriptive statistics of subscribers having a second set of anonymized subscriber identifiers receiving a third set of mathematically descriptive statistics of subscribers, said third set of mathematically descriptive statistics of subscribers having non-anonymized subscriber identifiers; identifying a first subscriber within said third set of mathematically descriptive statistics of subscribers, said first subscriber being identified with a first non-anonymized subscriber identifier; searching said aggregated database to identify a second record within said aggregated database having a match with said first subscriber; and associating said first non-anonymized subscriber identifier with said second record. ### Claim 6 A system comprising: at least one computer processor; said at least one computer processor configured to perform a method comprising: receiving a first set of mathematically descriptive statistics of subscribers, said first set of mathematically descriptive statistics being semantic-free and being calculated from a first telecommunications network; receiving a second set of mathematically descriptive statistics of subscribers, said second set of mathematically descriptive statistics being semantic-free and being calculated from a second telecommunications network; aggregating said first set of mathematically descriptive statistics of subscribers and a said second set of mathematically descriptive statistics of subscribers into an aggregated database; receiving a query request; processing said query request against said aggregated database to generate a query response, said query response comprising data derived from said aggregated database; and transmitting said query response; said first set of mathematically descriptive statistics of subscribers having a first set of anonymized subscriber identifiers, and said second set of mathematically descriptive statistics of subscribers having a second set of anonymized subscriber identifiers; receiving a first anonymized subscriber identifier, said first anonymized subscriber identifier being opt-out for participation in said aggregated database; and removing at least one record associated with said first anonymized subscriber identifier from said aggregated database. ### Claim 7 A system comprising: at least one computer processor; said at least one computer processor configured to perform a method comprising: receiving a first set of mathematically descriptive statistics of subscribers, said first set of mathematically descriptive statistics being semantic-free and being calculated from a first telecommunications network; receiving a second set of mathematically descriptive statistics of subscribers, said second set of mathematically descriptive statistics being semantic-free and being calculated from a second telecommunications network; aggregating said first set of mathematically descriptive statistics of subscribers and a said second set of mathematically descriptive statistics of subscribers into an aggregated database; receiving a query request; processing said query request against said aggregated database to generate a query response, said query response comprising data derived from said aggregated database; and transmitting said query response; said first set of mathematically descriptive statistics of subscribers having a first set of anonymized subscriber identifiers, and said second set of mathematically descriptive statistics of subscribers having a second set of anonymized subscriber identifiers; said response comprising a third set of anonymized identifiers, said method further comprising: receiving a fourth set of anonymized identifiers, said fourth set of anonymized identifiers being a subset of said third set of anonymized identifiers; and transmitting at least a first portion of said fourth set of anonymized identifiers to said first telecommunications network. ### Claim 8 (depends on 7) The system of claim 7, said method further comprising: transmitting a first set of subscriber contact instructions, said first portion of said fourth set of anonymized identifiers corresponding with said first set of anonymized subscriber identifiers to said first telecommunications network. ### Claim at position 6 9-10. (canceled) ### Claim 11 A system comprising: at least one computer processor; said at least one computer processor configured to perform a method comprising: receiving a first set of mathematically descriptive statistics of subscribers, said first set of mathematically descriptive statistics being semantic-free and being calculated from a first telecommunications network; receiving a second set of mathematically descriptive statistics of subscribers, said second set of mathematically descriptive statistics being semantic-free and being calculated from a second telecommunications network; aggregating said first set of mathematically descriptive statistics of subscribers and a said second set of mathematically descriptive statistics of subscribers into an aggregated database; receiving a query request; processing said query request against said aggregated database to generate a query response, said query response comprising data derived from said aggregated database; and transmitting said query response; said first set of mathematically descriptive statistics of subscribers having a first set of anonymized subscriber identifiers, and said second set of mathematically descriptive statistics of subscribers having a second set of anonymized subscriber identifiers; comparing said first set of mathematically descriptive statistics with said second set of mathematically descriptive statistics to identify a first subscriber in said first set of mathematically descriptive statistics having a similarity to a second subscriber in said second set of mathematically descriptive statistics; and labeling said first subscriber and said second subscriber as the same subscriber when said similarity is in excess of a predefined threshold. ### Claim 12 (depends on 11) The system of claim 11, said method further comprising: said predefined threshold being a statistical confidence greater than 99.9%. ### Claim at position 9 13-16. (canceled) ### Claim 17 A method performed on at least one computer processor, said method comprising: receiving a first set of mathematically descriptive statistics of subscribers, said first set of mathematically descriptive statistics being semantic-free and being calculated from a first telecommunications network; receiving a second set of mathematically descriptive statistics of subscribers, said second set of mathematically descriptive statistics being semantic-free and being calculated from a second telecommunications network; aggregating said first set of mathematically descriptive statistics of subscribers and a said second set of mathematically descriptive statistics of subscribers into an aggregated database; receiving a query request; processing said query request against said aggregated database to generate a query response, said query response comprising data derived from said aggregated database; and transmitting said query response; identifying a first subscriber within said third set of mathematically descriptive statistics of subscribers, said first subscriber being identified with a first non-anonymized subscriber identifier; searching said aggregated database to identify a second record within said aggregated database having a match with said first subscriber; and associating said first non-anonymized subscriber identifier with said second record. ### Claim 18 A method performed on at least one computer processor, said method comprising: receiving a first set of mathematically descriptive statistics of subscribers, said first set of mathematically descriptive statistics being semantic-free and being calculated from a first telecommunications network; receiving a second set of mathematically descriptive statistics of subscribers, said second set of mathematically descriptive statistics being semantic-free and being calculated from a second telecommunications network; aggregating said first set of mathematically descriptive statistics of subscribers and a said second set of mathematically descriptive statistics of subscribers into an aggregated database; receiving a query request; processing said query request against said aggregated database to generate a query response, said query response comprising data derived from said aggregated database; and transmitting said query response; receiving a first anonymized subscriber identifier, said first anonymized subscriber identifier being opt-out for participation in said aggregated database; and removing at least one record associated with said first anonymized subscriber identifier from said aggregated database. ### Claim 19 A method performed on at least one computer processor, said method comprising: receiving a first set of mathematically descriptive statistics of subscribers, said first set of mathematically descriptive statistics being semantic-free and being calculated from a first telecommunications network; receiving a second set of mathematically descriptive statistics of subscribers, said second set of mathematically descriptive statistics being semantic-free and being calculated from a second telecommunications network; aggregating said first set of mathematically descriptive statistics of subscribers and a said second set of mathematically descriptive statistics of subscribers into an aggregated database; receiving a query request; processing said query request against said aggregated database to generate a query response, said query response comprising data derived from said aggregated database; and transmitting said query response; said response comprising a third set of anonymized identifiers: receiving a fourth set of anonymized identifiers, said fourth set of anonymized identifiers being a subset of said third set of anonymized identifiers; and transmitting at least a first portion of said fourth set of anonymized identifiers to said first telecommunications network. ### Claim 20 (depends on 19) The method of claim 19, said method further comprising: transmitting a first set of subscriber contact instructions, said first portion of said fourth set of anonymized identifiers corresponding with said first set of anonymized subscriber identifiers to said first telecommunications network. ### Claim at position 14 21-22. (canceled) ### Claim 23 A method performed on at least one computer processor, said method comprising: receiving a first set of mathematically descriptive statistics of subscribers, said first set of mathematically descriptive statistics being semantic-free and being calculated from a first telecommunications network; receiving a second set of mathematically descriptive statistics of subscribers, said second set of mathematically descriptive statistics being semantic-free and being calculated from a second telecommunications network; aggregating said first set of mathematically descriptive statistics of subscribers and a said second set of mathematically descriptive statistics of subscribers into an aggregated database; receiving a query request; processing said query request against said aggregated database to generate a query response, said query response comprising data derived from said aggregated database; and transmitting said query response; comparing said first set of mathematically descriptive statistics with said second set of mathematically descriptive statistics to identify a first subscriber in said first set of mathematically descriptive statistics having a similarity to a second subscriber in said second set of mathematically descriptive statistics; and labeling said first subscriber and said second subscriber as the same subscriber when said similarity is in excess of a predefined threshold. ### Claim 24 (depends on 23) The method of claim 23, said method further comprising: said predefined threshold being a statistical confidence greater than 99.9%.