WO2015085393A1 - Système et procédé pour évaluer un historique de transactions - Google Patents

Système et procédé pour évaluer un historique de transactions Download PDF

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Publication number
WO2015085393A1
WO2015085393A1 PCT/CA2013/050967 CA2013050967W WO2015085393A1 WO 2015085393 A1 WO2015085393 A1 WO 2015085393A1 CA 2013050967 W CA2013050967 W CA 2013050967W WO 2015085393 A1 WO2015085393 A1 WO 2015085393A1
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WIPO (PCT)
Prior art keywords
rating
peer
digital currency
account
transaction
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PCT/CA2013/050967
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English (en)
Inventor
Li Jun TANG
Jia Hao TANG
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Tang li jun
Tang Jia Hao
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Application filed by Tang li jun, Tang Jia Hao filed Critical Tang li jun
Priority to CA2933407A priority Critical patent/CA2933407A1/fr
Priority to PCT/CA2013/050967 priority patent/WO2015085393A1/fr
Publication of WO2015085393A1 publication Critical patent/WO2015085393A1/fr

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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q20/00—Payment architectures, schemes or protocols
    • G06Q20/04—Payment circuits
    • G06Q20/06—Private payment circuits, e.g. involving electronic currency used among participants of a common payment scheme
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q20/00—Payment architectures, schemes or protocols
    • G06Q20/22—Payment schemes or models
    • G06Q20/223—Payment schemes or models based on the use of peer-to-peer networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q20/00—Payment architectures, schemes or protocols
    • G06Q20/38—Payment protocols; Details thereof
    • G06Q20/389—Keeping log of transactions for guaranteeing non-repudiation of a transaction
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q20/00—Payment architectures, schemes or protocols
    • G06Q20/38—Payment protocols; Details thereof
    • G06Q20/40—Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
    • G06Q20/401—Transaction verification
    • G06Q20/4016—Transaction verification involving fraud or risk level assessment in transaction processing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/02—Banking, e.g. interest calculation or account maintenance

Definitions

  • the present invention relates to generating a rating of a transaction history in electronic commerce, and more specifically rating a transaction history of a digital currency.
  • a digital currency is electronic money that acts as alternative currency.
  • digital currencies are not produced by government-endorsed central banks nor necessarily backed by national currency.
  • Digital currencies are typically used in transactions with all goods and services and are not limited to electronic media such as Internet distribution of movies and games.
  • Mainstream monetary transactions are typically based on trust. Identification of each party in a two party transaction is a significant part of building trust. Digital currencies such as Bitcoin and Bitcoin based currencies use proof-of-work, as well as proof-of-stake for PPcoin, as validators instead of traditional mechanisms for establishing trust. Moreover, with digital currencies such as Bitcoin, transactions are often carried out in anonymity without any exchange of identification other than a user's account identifier. Thus, digital currency transactions are susceptible to identity fraud or scams.
  • a rating system for rating a transaction history of a digital currency comprising:
  • a storage system for storing transaction information of the digital currency
  • an interface for receiving an identifier of at least one account associated with the digital currency and a request for rating the transaction history of the at least one account;
  • a processor communicative with the storage system and the interface;
  • the processor identifying transactions of the at least one account from the transaction information stored in the storage system and assessing the amount, date, and destination of the identified transactions to generate a rating for the at least one account.
  • a computer-implemented method for rating a transaction history of a digital currency comprising:
  • a computer readable medium embodying a computer program for rating a transaction history of a digital currency, comprising:
  • a rating system for rating a transaction history of a peer-to-peer digital currency comprising:
  • a storage system for storing transaction information of the peer-to-peer digital currency
  • an interface for receiving an identifier of at least one account associated with the peer- to-peer digital currency and a request for rating the transaction history of the at least one account
  • a processor communicative with the storage system and the interface
  • the processor identifying transactions of the at least one account from the transaction information stored in the storage system and assessing the destination of the identified transactions to generate a rating for the at least one account.
  • a computer-implemented method for rating a transaction history of a peer-to-peer digital currency comprising:
  • a computer readable medium embodying a computer program for rating a transaction history of a peer-to-peer digital currency, comprising:
  • computer readable code for storing transaction information of the peer-to-peer digital currency in a storage system; computer readable code for receiving over a network via an interface an identifier of at least one account associated with the peer-to peer digital currency and a request for rating the transaction history of the at least one account;
  • Figure 1 shows a block diagram describing a flow example of a user interaction with a transaction history rating system
  • Figure 2 shows a block diagram describing a flow example of the transaction history rating system processing the user request shown in Figure 1 ;
  • Figure 3 shows a block diagram describing a flow example of a user interaction with a transaction history rating system for Bitcoin transactions
  • Figure 4 shows a block diagram describing a flow example of the Bitcoin transaction history rating system processing the user request shown in Figure 3;
  • Figure 5 shows a block diagram describing a flow example of the Bitcoin transaction history rating system generating a reference value
  • Figure 6 shows a block diagram describing a flow example of the Bitcoin transaction history rating system generating a score characterizing the transaction history of a specified account
  • Figure 7 shows a block diagram describing a flow example of the Bitcoin transaction history rating system generating an averaged score characterizing the transaction history of a specified account
  • Figure 8 shows a block diagram describing a flow example of the Bitcoin transaction history rating system generating a projected score characterizing the transaction history of a specified account
  • Figure 9 shows a block diagram describing a flow example of an aggressive projection for generating the projected score shown in Figure 8
  • Figure 10 shows a block diagram describing a flow example of a conservative projection for generating the projected score shown in Figure 8;
  • Figure 11 shows a block diagram describing an alternative flow example, to that shown in Figure 5, of the Bitcoin transaction history rating system generating a reference value;
  • Figure 12 shows a block diagram describing an alternative flow example, to that shown in Figure 6, of the Bitcoin transaction history rating system generating a score characterizing the transaction history of a specified account.
  • Figure 13 is a system map showing an implementation of the rating system
  • Figure 14 is a system map showing an alternative implementation of the rating system.
  • Figure 1 shows a flow diagram describing an example of a user inputing an account identifier and requesting a score for the account identifier within the system.
  • the user may perform the steps shown in Figure 1 using an application installed on a personal computing device or using a website interface for an online application connected to a server computer.
  • the application installed on a personal computing device may be used offline with local processor and memory or may be used online in connection with a server computer and database.
  • the steps are described in the context of an application installed on the user's personal computing device with an online connection to a server computer.
  • an end-user interface application software previously installed on the computing device will start (110) and initiate a networked communication with a server computer of the system.
  • the server computer will typically require login information (120) that may be provided by the application software in the form of a stored electronic data packet such as an electronic cookie.
  • login information 120
  • the user is prompted to manually enter the login information (122) such as a login name and password.
  • the user can access a list (130), for example as a pull down menu, of predetermined score types.
  • the system may provide the user with a brief description of each score type.
  • the user selects a desired score type (140) and inputs an identifier for a digital currency account (150).
  • the server computer calculates the score for the specified account.
  • the user receives the requested score (160).
  • FIG. 2 shows a flow diagram describing an example of processing steps performed by the server computer to generate the requested score.
  • the server computer receives (210) the selected score type and the specified account identifier from the user's computing device.
  • the server computer accesses the transaction history of the digital currency (220) and based on the account identifier information provided by the user (150) the server computer can filter the transaction history of the digital currency to analyze the transactions of the specified account (230).
  • the server computer analyzes the transactions of the specified account with reference to one or more relevant parameters such as transaction amount (232), transaction frequency (234), account age (236), or transaction destination (238).
  • the one or more relevant parameters may be any single or combination of quantifiable factors that can define a digital currency transaction.
  • the server computer executes algorithm(s) based on the one or more relevant parameters to calculate a score (240).
  • the score is sent to the user's computing device (250) and received by the application software, displayed to the user and optionally stored in memory.
  • Figure 3 shows a flow diagram providing an example of the steps similar to those shown in Figures 1 and 2 applied to generation of a score for a Bitcoin digital currency account.
  • a user wishing to obtain a score for a Bitcoin account inputs information containing a unique identifier of the account, typically a Bitcoin address or a hash of the address (310).
  • the user may choose a type of score (312) selecting from options (314) such as Current, Projected, Average, or Projected Average.
  • the user may choose an output format (316) selecting from options (318) such as XML, plain text or CSV.
  • the information containing the unique identifier, the choice of score type and the choice of output format is submitted to a processor for score calculation.
  • the processor calculates the requested score with predetermined algorithms corresponding to the chosen score type (322, 326) and by accessing the transaction history database or Blockchain of the Bitcoin (324) or a database derived from the Blockchain information (328). The calculated score is returned to the user's personal computing device and displayed to the user.
  • Figure 4 shows a flow diagram providing an example of steps of a calculation (322).
  • Calculation (322) is initiated by receipt of a request for a score calculation (340) with the request comprising information relating to an account identifier, and optionally a score type and an output format (342).
  • the received information and more particularly the account identifier information may be validated, for example by checksum analysis, to ensure that it is in an appropriate form (344) with an invalid format resulting in an error message returned to the user (346) and a valid format proceeding to access Blockchain information stored in a local memory (348).
  • the locally stored Blockchain information is assessed (350), and if it is up to date the processor selects an algorithm (354) corresponding to the score type specified in the request (342) and executes the selected algorithm (356, 357, 358 or 359). If the Blockchain information is not up to date a networked connection is initiated to update the Blockchain information (352) and to calculate reference values relating to the total, average or mean of an accumulated value of transactions in the Blockchain. The reference values are used to normalize scores to facilitate comparison of scores for different accounts at different time points.
  • Figure 5 shows a flow diagram providing an example of steps to update the Blockchain information and reference values (352).
  • a networked connection to a realtime Bitcoin Blockchain database is initiated and compared to a record of the last updated Blockchain transaction (370) to determine a starting point and size of the update.
  • the update can involve updating a Bitcoin Blockchain database stored in local memory as well as parameter weight factors database also stored in a local memory and used for calculating scores.
  • a reference value Cm is updated (374) in view of updated Blockchain transactions. Calculation of the reference value Cm comprises three components: a total transaction amount, a negative weighting penalizing longer intervals (ie., lower frequency), and a negative weighting penalizing greater account age.
  • the reference value Cm can be updated in iterative fashion (378) by considering each subsequent updated transaction until the current transaction is reached (376) resulting in an updated Cm reference value.
  • Figure 6 shows a flow diagram providing an example of steps to calculate a Bitcoin account score extending (356) from the steps shown in Figure 4.
  • the Blockchain and weight factor databases (372), updated as shown in Figure 5, are accessed for transaction information relevant to the specified account identifier for which a score has been requested as shown in Figure 3 (310).
  • Value Cid an accumulated value of all the transactions of Bitcoin transfers carried out by the specified account, is then calculated (390).
  • calculation of value Cid comprises three components (390): a total transaction amount, a negative weighting penalizing longer intervals (ie., lower frequency), and a negative weighting penalizing greater account age.
  • the Bitcoin account score is then calculated as a comparison, more specifically a ratio, of the value Cid over the reference value Cm to yield the score Sid (394) which is then sent (396) and displayed to the user to complete the user's request (320).
  • id identifier of a digital currency account may also be identification number of a report, also is the address in Bitcoin
  • Cid Accumulated value of transactions associated with id Cid Accumulated value of transactions associated with id.
  • FIG. 7 shows a flow diagram providing an example of steps to calculate a system index score extending (357) from the steps shown in Figure 4.
  • the score index Id is calculated (400) as a comparison, or more specifically a ratio of a Cm value at a specified date to a Cm value at a prior reference date, designated Co.
  • the index score can then be returned (402) and displayed to the user.
  • the index score is useful for assessing overall or top level trends of the system between two or more dates.
  • the Index score may reflect overall expansion or contraction of the system between a queried date and a reference date.
  • the index score may be used for month-over-month or year-over-year comparisons.
  • Figure 8 shows a flow diagram providing an example of steps to calculate a projected
  • Bitcoin account score extending (358) from the steps shown in Figure 4.
  • the Blockchain and weight factor databases (372), updated as shown in Figure 5, are accessed for transaction information relevant to the specified account identifier for which a score has been requested as shown in Figure 3 (310).
  • Value Cdp a projected accumulated value of all the transactions of Bitcoin transfers carried out by the specified account, is then calculated (410).
  • the value Cdp is for projected day dp.
  • a projected reference value Cp is also calculated (414).
  • Cp is the projected average value considering all accounts/addresses of Bitcoin as predicted for projected day dp.
  • the Bitcoin account score is then calculated as a comparison, more specifically a ratio, of the projected account value Cdp over the projected reference value Cp to yield the projected score Sdp (416) for projected day dp which is then sent (418) and displayed to the user to complete the user's request (320).
  • fp is a predictive function that is applied to a data set comprising a plurality of existing Cid values and their corresponding dates.
  • the predictive function may be applied independent of the parameters considered to obtain the data set of Cid values.
  • Many different predictive algorithms may be applied including Lagrange interpoloation, polynomial regression, trigonometric functions, complex number functions, exponential functions, logarithmic functions and the like.
  • Figures 9 and 10 show alternative calculations or predictive algorithms for obtaining the projected score shown in Figure 8, an aggressive projection (420) in Figure 9 based on a Lagrange interpolation and a conservative projection (450) in Figure 10 based on a polynomial regression.
  • Figure 9 provides a Lagrange interpolation for fp shown in Figure 8.
  • Data sets for a plurality of corresponding Cid and di data points can be obtained (422) and treated with a Lagrange interpolation to obtain a Cdp value (424) and a Cp value (426).
  • the Lagrange expression comprises the requested projected date - d, the date of transaction i - di, and all dates for which Cid has been calculated that are not equal to di - dj .
  • the Cdp value is obtained for the projected date - d.
  • the projected reference value Cp for the projected date d is obtained by summing all Cdp values for all Bitcoin addresses for the projected date d divided by the number of total addresses.
  • the projected score is then calculated as a comparison, more specifically a ratio, of the Cdp value over the Cp value to yield the projected score Sdp (428) for the projected date d which is then sent (430) and displayed to the user.
  • Figure 10 provides a polynomial regression for fp shown in Figure 8.
  • a polynomial regression can be expressed in matrix form and solved using a least squares method.
  • Data sets for a plurality of corresponding Cid and di data points can be obtained (452) and treated with a polynomial regression to obtain a Cdp value (456) and a Cp value (458) for the projected date d.
  • the projected score is then calculated as a comparison, more specifically a ratio, of the Cdp value over the Cp value to yield the projected score Sdp (460) for the projected date d which is then sent (462) and displayed to the user.
  • Figure 11 shows a flow diagram providing an alternative example, to that shown in Figure 5, of steps to update the Blockchain information and reference values (352).
  • Figure 11 differs from Figure 5 by assessing an additional parameter of transaction destination information.
  • a networked connection to a realtime Bitcoin Blockchain database is initiated and compared to a record of the last updated Blockchain transaction to determine a starting point and size of the update and access relevant information for calculation of reference values (470).
  • the update can involve updating a Bitcoin Blockchain database stored in local memory as well as parameter weight factors database also stored in a local memory and used for calculating scores (372).
  • a reference value Cmk(id,idd) for each unique account/destination pair is updated (474) in view of updated Blockchain transactions.
  • Calculation of the reference value Cmk(id,idd) comprises three components: a total transaction amount, a negative weighting penalizing longer intervals (ie., lower frequency), and a negative weighting penalizing greater account age.
  • the reference value Cmk(id,idd) can be updated in iterative fashion (478) for each unique account/destination pair by considering each subsequent updated transaction until the current transaction is reached (476) resulting in an updated Cmk(id,idd) reference value.
  • a factor k(id,idd) is then calculated based on the number of repeated transactions for each unique account/destination pair (480).
  • Figure 12 shows a flow diagram providing an alternative example, to that shown in Figure 6, of steps to calculate a Bitcoin account score extending (356) from the steps shown in Figure 4.
  • Figure 12 differs from Figure 6 by assessing an additional parameter of transaction destination information.
  • the Blockchain and weight factor databases (372), updated as shown in Figure 11, are accessed for transaction information (570) relevant to the specified account identifier for which a score has been requested as shown in Figure 3 (310).
  • Ck(id,idd) characterizing accumulated transactions for each unique destination for Bitcoin transfers from the specified account is calculated (574) in view of updated Blockchain transaction information.
  • Calculation of Ck(id,idd) comprises three components: a total transaction amount, a negative weighting penalizing longer intervals (ie., lower frequency), and a negative weighting penalizing greater account age.
  • Ck(id,idd) can be calculated in iterative fashion (578) for each unique destination from the specified account by considering each subsequent transaction until the current transaction is reached (576). A factor k(id,idd) is then calculated based on the number of repeated transactions for each unique destination for Bitcoin transfer from the specified account (580).
  • the alternative calculation of value Cid shown in Figure 12 comprises five components: a total transaction amount, a negative weighting penalizing longer intervals (ie., lower frequency), a negative weighting penalizing greater account age, a positive summation rewarding greater numbers of unique destinations, and a factor that penalizes multiple transactions to the same destination.
  • the Bitcoin account score Sid may then be calculated as shown in Figure 6, as a comparison, more specifically a ratio, of the value Cid over the reference value Cm to yield the score Sid (394) which is then sent (396) and displayed to the user to complete the user's request (320). From Figures 1 1 and 12:
  • nidd total number of transactions with same destination address from source id
  • Figure 13 shows a system map describing an example of an internet cloud (620) based implementation of the system (600) for generating ratings in respect of Bitcoin transaction histories, where functions for analyzing transaction histories and generating scores are carried out by server computers (602) operably linked to data storage systems (604) that are isolated from the cloud (620) by an electronic interface device (606).
  • the electronic interface device has processing power, optionally including a firewall, to receive via the internet (620) requests from client computing devices for a score relating to an account identifier and then to return a score for the account identifier back to the client computing device.
  • the electronic interface device (606) shields the server computers (602) and data storage systems (604) from direct interaction with the Internet or from direct communication with client computers.
  • the electronic interface device Upon receiving a request from a client computing device the electronic interface device (606) logs the request, optionally performing a validation check of the request, and then sends a request for a score including account identifier information to the server computers (602). Once a score is generated, the server computers (602) return the score to the electronic interface device for subsequent return to the client computing device.
  • Bitcoin transaction histories termed Blockchain are publically available from many sources including Bitcoin electronic exchanges and connection of server computers (602) with the Bitcoin system (610), may be established either directly or through an electronic interface device at any desired frequency to ensure that the transaction history information stored within data storage system (604) is up to date.
  • the computer architecture shown in Figure 13 may be simplified or elaborated depending upon the desired application.
  • the system comprises a plurality of users (630) each with at least one computing device.
  • User computing devices (630) through either a web browser or a locally installed application communicate over a network (620) with the scoring system (600).
  • the scoring system (600) may be independent and shielded from the Bitcoin system or may be embedded in the Bitcoin system.
  • the scoring system (600) may be hosted on a single server with a processor operably linked to a memory.
  • Memory may include volatile memory such as various RAM types, and non-volatile such as ROM, magnetic storage systems, optical storage systems and the like.
  • Figure 14 shows a system map describing another example of an implementation (700) of the system.
  • User computing devices 710 including smartphones, tablets, laptops, desktops and the like may communicate through web browsers or locally installed applications with a digital currency system comprising a component for conducting transactions (730) and a component for recording each transaction and its related information (732).
  • the user computing devices 710 may also communicate through web browsers or locally installed applications with a system for rating transactional histories of the digital currency.
  • Corporate entity computers (712) such as financial institutions, commodity and currency exchanges, transaction processors and the like may also communicate with the digital currency system and/or the rating system through an application programming interface (API).
  • API application programming interface
  • the user computing devices (710) will communicate with the rating system through a network (720) such as the Internet, while corporate computers (712) may have a more direct electronic linkage.
  • the rating system receives requests for ratings including an account identifier over the network (720) through website applications (740) hosted on a load balanced web server farm (742).
  • Corporate computers (712) may send requests directly to the web server farm (742) based on an API.
  • the web server farm is communicative with load balanced transaction history servers (750) and score calculation servers (752) which are in turn communicative with a load balanced database server farm (760, 762, 764, 766, 768, 770) which maintain, update, and access records from a data storage system (660).
  • the transaction history servers (750) are communicative with the score calculation servers (752).
  • the transaction history servers (750) or the web servers (742) may be communicative with a publically accessible or privately held electronic record or data base of the transaction histories of the digital currency.
  • the rating system described herein provides users with a rating, score, ranking and the like to be able to assess the activity of a targeted account of a digital currency.
  • a proof-of-work concept as a validator of a transaction.
  • Proof-of-work inherently requires time to lapse after a transfer of currency.
  • proof-of-work is difficult to understand for most users.
  • the rating system can provide a score characterizing a queried account's transaction activity in advance of agreeing to a transaction. Thus, it may complement existing validators such as proof-of-work or proof-of-stake to provide confidence or trust in a digital currency system.
  • the rating system may be used by users that are expecting to enter into a transaction using a digital currency or by corporate entities such as financial institutions or transaction processors that may be tasked with monitoring a digital currency system.
  • a user before agreeing to a transaction in a digital currency, a user can obtain the account address or identifier of the opposing party. The user can then input the account identifier in a data entry box in a web application and send a request over the internet for a rating corresponding to the account identifier. The request is received and a rating is calculated and returned to be displayed to the user through the web application.
  • the rating may be presented in any manner of ways including numerical score, star rating, percentile ranking, 2D graphs, distribution curves, and the like.
  • the user can assess the risk of the potential transaction in view of the rating.
  • the rating reflects the ability of the account to fulfill a transaction of the digital currency at a current date or a target projected date queried by the user.
  • the system is typically used for rating a transaction history of a digital currency.
  • the transaction history of the digital currency may be publically accessible or privately held.
  • the Bitcoin transaction history is publically accessible, while a significant portion of the transaction history of Amazon's digital currency, Amazon coins, is privately held.
  • the system may be used in conjunction with any digital currency and may function independently of a digital currency or may be embedded within the digital currency computing infrastructure.
  • peer-to-peer digital currency is a decentralized currency managed by peer-to-peer networked computing technology (P2P), without a central authority. Consistent with P2P technology, the networked distributed computing application architecture partitions tasks or workloads among peers or nodes. Functions of currency issuance, transaction processing and verification are carried out collectively by the network, without a central supervisor or agency to oversee operations.
  • P2P peer-to-peer networked computing technology
  • the system typically requires a memory, an interface and a processor.
  • the types and arrangements of memory, interface and processor may be varied according to implementations.
  • the interface may include a software interface such as a web application that launces a web browser and internet connection on an end-user computing device.
  • the interface may also include a physical electronic device configured to receive requests or queries from an end-user.
  • the rating system can represent a rating in any convenient graphical or text format.
  • the rating system may generate a numerical score that characterizes the transaction history of an account of a digital currency.
  • the numerical score may represent a total value for the accumulated transactions of the account, per day average, a per transaction average, a per destination average, or any other convenient representation.
  • the numerical score may be compared to a reference value to normalize the numerical score.
  • the reference value may characterize the total accumulated transaction information of the digital currency.
  • the reference value may be represented as a total, average, mean or modal (most frequently observed) value or any other convenient representation characterizing the accumulated transaction information of the digital currency.
  • the rating system will typically assess at least one of the parameters of amount, date and destination of transactions that make up the transaction history of an account of the digital currency. More typically, the rating system will assess at least two of the parameters of amount, date and destination. For example, assessing amounts alone is a measure of currency volume. Assessing dates alone can provide a rating based on frequency and/or age of transactions. Assessing destination identifiers alone can provide a rating based on numbers of unique destinations and/or repetition of the same destination. Thus, each parameter of amount, date, and destination taken alone may be able to provide a useful rating, but taken together with at least two of the three, or all three, co-operate to provide an increasingly robust rating.
  • the parameters of amount, date, and destination, or parameters derived therefrom may be negatively or positively correlated with a rating depending on the rating scheme and the algorithms for generating a rating. Correlations may encompass linear relationships as well as non-linear relationships. A correlation may be considered for any two or more variables that depart from independence.
  • amount is positively correlated with the rating such that an increase in amount is correlated with an increase in rating.
  • An increase amount may be rewarded as it reflects currency volume and provides precedent for a transaction level.
  • Transaction frequency may be derived from transaction dates, for example by calculating intervals between each transaction, with transaction frequency typically being positively correlated with rating, such that an increase in transaction frequency is correlated with an increase in the rating.
  • the rating system may be configured to reward increase frequency as higher successful active density means more creditable contributions.
  • Age of transactions or age of the account can also be derived from transaction dates, with age typically being negatively correlated with the rating, such that a decrease in transaction age is correlated with an increase in the rating.
  • the rating system may be configured to penalize an increase in age as a contribution erodes by time or aging, with more recent activity providing a better indicator.
  • the number of unique transaction destinations may be derived from transaction destination information with unique transaction destinations typically being positively correlated with the rating, such that an increase in the number of unique transaction destinations is correlated with an increase in the rating.
  • the rating system may be configured to reward an increase in unique destinations to reward diversity as more unique destinations means more diverse activities to different receivers and increased exposure to detection of fraudulent activity.
  • the number of repeated transactions to the same destination may be derived from the transaction destination information with the number of repeated transactions to the same destination being negatively correlated with the rating such that a decrease in repeated transactions to the same destination is correlated with an increase in the rating.
  • the rating system may be configured to penalize increase in repeated transaction to the same destination to promote diversity and to limit contributions from potential cheat or fake transactions for the purpose of gaming the rating system to increase a rating by simply shuttling currency back and forth between accounts. Destinations are typically derived from the transaction information by extracting destination account identifiers.
  • the components of the system may be administered by a single organization or a plurality of partnering organizations.
  • the tracking and validation of transaction histories of a digital currency may be administered by an organization at arm's length from the organization administering the rest of the system.
  • Such an arm's length organization may be a financial institution, accounting firm or payment transaction processor.
  • the system may accommodate any type of end-user computing device or client computing device provided the computing device can be networked to the system and is configured to display website interfaces and/or graphical interface elements for performing the various functions of the system such as inputting an account identifier, displaying a rating or updating a transaction history database that may be locally stored in the computing device.
  • the computing device may be a desktop, laptop, notebook, tablet, personal digital assistant (PDA), PDA phone or smartphone, gaming console, portable media player, and the like.
  • PDA personal digital assistant
  • the computing device may be implemented using any appropriate combination of hardware and/or software configured for wired and/or wireless communication over the network.
  • the server computer may be any combination of hardware and software components used to store, process and/or provide scores or ratings for transactions from one or more accounts using a digital currency, and monitoring and analyzing such transactions.
  • the server computer components such as storage systems, processors, interface devices, input/output ports, bus connections, switches, routers, gateways and the like may be geographically centralized or distributed.
  • the server computer may be a single server computer or any combination of multiple physical and/or virtual servers including for example, a web server, a transaction server, an application server, a bus server, an integration server, a user profile server, an algorithm server, a weighting factor server, a log server, an accounting server and the like.
  • Any conventional computer architecture may be used to implement the system including for example a memory, a mass storage device, a processor (CPU), a Read-Only Memory (ROM), and a Random-Access Memory (RAM) generally connected to a system bus of data-processing apparatus.
  • Memory can be implemented as a ROM, RAM, a combination thereof, or simply a general memory unit.
  • Software modules in the form of routines and/or subroutines for carrying out features of the rating system can be stored within memory and then retrieved and processed via processor to perform a particular task or function.
  • one or more of the flow diagrams shown in Figures 1-12 may be encoded as a program component, stored as executable instructions within memory and then retrieved and processed via a processor.
  • a user input device such as a keyboard, mouse, or another pointing device, can be connected to PCI (Peripheral Component Interconnect) bus.
  • PCI Peripheral Component Interconnect
  • the software will typically provide an environment that represents programs, files, options, and so forth by means of graphically displayed icons, menus, and dialog boxes on a computer monitor screen.
  • a data-process apparatus can include CPU, ROM, and RAM, which are also coupled to a PCI (Peripheral Component Interconnect) local bus of data-processing apparatus through PCI Host Bridge.
  • PCI Host Bridge can provide a low latency path through which processor may directly access PCI devices mapped anywhere within bus memory and/or input/output (I/O) address spaces.
  • PCI Host Bridge can also provide a high bandwidth path for allowing PCI devices to directly access RAM.
  • a communications adapter, a small computer system interface (SCSI), and an expansion bus-bridge may also be attached to PCI local bus.
  • the communications adapter can be utilized for connecting data-processing apparatus to a network.
  • SCSI can be utilized to control a high-speed SCSI disk drive.
  • An expansion bus-bridge such as a PCI-to-ISA bus bridge, may be utilized for coupling ISA bus to PCI local bus.
  • PCI local bus can be connected to a monitor, which functions as a display (e.g., a video monitor) for displaying data and information for an operator and also for interactively displaying a graphical user interface.
  • a database can contain information on a variety of matters such as data relating to digital currency transactions, transfers, or conversions.
  • a database may contain user profiles, user preferences, transaction history, score history, and/or history of prior score requests.
  • a user profile may include, but is not limited to, a user identifier such as login name, a password, contact information, mailing information, billing information, saved product searches, and/or user preferences for use in searching database and/or displaying product searches.
  • the network may be a single network or a combination of multiple networks.
  • the network may include the internet and/or one or more intranets, landline networks, wireless networks, and/or other appropriate types of communication networks.
  • the network may comprise a wireless telecommunications network (e.g., cellular phone network) adapted to communicate with other communication networks, such as the Internet.
  • the network will comprise a computer network that makes use of a TCP/IP protocol (including protocols based on TCP/IP protocol, such as HTTP, HTTPS or FTP).
  • the system may be adapted to follow any computer communication standard including Extensible Markup Language (XML), Comma-Separated Values (CSV), Hypertext Transfer Protocol (HTTP), Java Message Service (JMS), Simple Object Access Protocol (SOAP), Representational State Transfer (REST), Lightweight Directory Access Protocol (LDAP), Simple Mail Transfer Protocol (SMTP) and the like.
  • XML Extensible Markup Language
  • CSV Common-Separated Values
  • HTTP Hypertext Transfer Protocol
  • JMS Java Message Service
  • SOAP Simple Object Access Protocol
  • REST Representational State Transfer
  • LDAP Lightweight Directory Access Protocol
  • SMTP Simple Mail Transfer Protocol
  • the system may represent a score graphically or by images and may accordingly accommodate any type of still or moving image file including JPEG, PNG, GIF, PDF, RAW, BMP, TIFF, MP3, WAV, WMV, MOV, MPEG, AVI, FLV, WebM, 3 GPP, SVI and the like.
  • the system may guide or prompt user attempts to input account identifiers and request various score types by any convenient form of user interface element including, for example, a window, a tab, a text box, a button, a hyperlink, a drop down list, a list box, a check box, a radio button box, a cycle button, a datagrid or any combination thereof.
  • user interface elements may provide a graphic label such as any type of symbol or icon, a text label or any combination thereof. Any desired spatial pattern or timing pattern of appearance of user interface elements may be accommodated by the system.
  • the system described herein and each variant, modification or combination thereof may also be implemented as a method or code on a computer readable medium (i.e. a substrate).
  • the computer readable medium is a tangible data storage device that can store data, which can thereafter, be read by a computer system. Examples of a computer readable medium include read-only memory, random-access memory, CD-ROMs, magnetic tape, optical data storage devices and the like.
  • the computer readable medium may be geographically localized or may be distributed over a network coupled computer system so that the computer readable code is stored and executed in a distributed fashion.

Abstract

La présente invention concerne un système d'évaluation pour évaluer un historique de transactions d'une devise numérique, comprenant : un système de mémoire pour mémoriser des informations de transaction de la devise numérique ; une interface pour recevoir un identificateur d'au moins un compte associé à la devise numérique et une requête pour évaluer l'historique de transactions dudit compte ; un processeur en communication avec le système de mémoire et l'interface ; le processeur identifiant des transactions dudit compte à partir des informations de transaction mémorisées dans le système de mémoire et évaluant la destination des transactions identifiées pour générer une évaluation pour ledit compte. Le système d'évaluation peut en outre évaluer le montant et l'âge des transactions identifiées. Le système d'évaluation peut être utile, par exemple, pour des devises numériques entre homologues, telles que Bitcoin. La présente invention concerne également des procédés pour évaluer un historique de transactions d'une devise numérique et des supports lisibles par ordinateur pour fournir ces derniers.
PCT/CA2013/050967 2013-12-13 2013-12-13 Système et procédé pour évaluer un historique de transactions WO2015085393A1 (fr)

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