Automatic Learning Multi-Modal Fraud Prevention (LMFP) System
First Claim
1. A computerized method for generating a new signature of a user to prevent user impersonation, comprising a computer processor steps of,a. fetching a signal from a non-volatile memory of at least one portion of at least one previously generated user'"'"'s signature;
- b. generating at least one challenge sequence based on the signal to create a new signature;
c. presenting the generated challenge sequence to the user;
d. collecting the user'"'"'s challenge response to the generated challenge sequence; and
,e. computing a quality factor which represents a degree of correlation between any portion of the user'"'"'s challenge response and any portion of the generated challenge sequence;
f. generating a new signature based on any portion of user'"'"'s challenge response and any portion of the previously generated signature and any portion of collectable information from user'"'"'s device memory; and
,g. storing at least one of, the new signature, the quality factor, the trust factor and/or the transaction quality factor in a non-volatile memory or communicating it to a computer program.
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Accused Products
Abstract
A computerized learning multi-modal fraud prevention system and method for generating a data signature of a user, such as one engaged in electronic commerce, to prevent fraudulent activities by machines and persons imitating the user. Steps comprise: fetching a signal of a user'"'"'s signature stored in memory; generating at least one challenge sequence based on the signal to create a second signature; presenting the generated challenge sequence to the user; collecting the user'"'"'s challenge response to the generated challenge sequence; computing a quality factor between the user'"'"'s challenge response and the generated challenge sequence; computing a transaction quality factor and content quality factor and reporting an impostor or re-challenging if the quality factor is below a threshold. Lastly, generating a new signature based on any portion of a user'"'"'s challenge response and/or any portion of the previously generated signature and/or any portion of collectable information from the user'"'"'s device memory.
111 Citations
24 Claims
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1. A computerized method for generating a new signature of a user to prevent user impersonation, comprising a computer processor steps of,
a. fetching a signal from a non-volatile memory of at least one portion of at least one previously generated user'"'"'s signature; -
b. generating at least one challenge sequence based on the signal to create a new signature; c. presenting the generated challenge sequence to the user; d. collecting the user'"'"'s challenge response to the generated challenge sequence; and
,e. computing a quality factor which represents a degree of correlation between any portion of the user'"'"'s challenge response and any portion of the generated challenge sequence; f. generating a new signature based on any portion of user'"'"'s challenge response and any portion of the previously generated signature and any portion of collectable information from user'"'"'s device memory; and
,g. storing at least one of, the new signature, the quality factor, the trust factor and/or the transaction quality factor in a non-volatile memory or communicating it to a computer program. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A networked based computing system for detecting fraudulent machine or human impersonation of a user, comprising:
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a) a system computer comprising at least one processor and at least one memory device operably connected to one another, and a plurality of computer-executable instructions stored on the memory device that when executed by the processor, cause the processor to; i. fetch a signal from a non-volatile memory of at least one portion of at least one previously generated user'"'"'s signature; ii. generate at least one challenge sequence based on the signal to create a new signature; iii. present the generated challenge sequence to the user; iv. collect the user'"'"'s challenge response to the generated challenge sequence; v. compute a quality factor which represents a degree of correlation between any portion of the user'"'"'s challenge response and any portion of the generated challenge sequence; vi. generate a new signature based on any portion of the user'"'"'s challenge response and any portion of the previously generated signature and any portion of collectable information from the user'"'"'s device memory; vii. store at least one of, the new signature, the quality factor, the trust factor, and the transaction quality factor in memory or communicating it to a computer program; and
,b) a connection between the system computer and one or more external applications. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20)
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21. A networked based computing system for detecting fraudulent machine or human impersonation of a user, comprising:
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a) a system computer comprising at least one processor and at least one memory device operably connected to one another, and a plurality of computer-executable instructions stored on the memory device that when executed by the processor, cause the processor to; i. fetch signals from memory of at least one portion of any of the following;
a previously generated user'"'"'s signature, a previously generated challenge sequence, a user'"'"'s identifying information, a user'"'"'s related information, a user'"'"'s device identifying information, a user'"'"'s device location, a user'"'"'s device parameters, a user'"'"'s challenge response, a quality factor, a trust factor, a transaction quality factor, a content quality factor, a whitelist, a blacklist, an advertisement, a content object, a user'"'"'s behavior information;ii. generate at least one new signature on, or adjacent to, every user interaction, and/or an external application interaction, and/or a predefined schedule or trigger event based on the signals; iii. store the new signature in memory or communicate it to a computer program; and
,b) a connection between the system computer and one or more external applications. - View Dependent Claims (22, 23, 24)
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Specification