Detailed Action
Claims 1-4, and 6-20 are pending and are examined.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
Claims 1, 8, 13, and 15 are currently amended.
Claim 5 is cancelled.
Response to Remarks
35 U.S.C. § 102 and § 103
Remark 1: Applicant argues that Li lacks any smart-contract-specific fraudulent training cluster, while Vijayan merely generates a single smart-contract security score from factors such as indicator factors, complaints, source code analysis, and abuse evidence. Applicant further argues that Jakobsson only updates machine-learning parameters or wallet/user activity models, not a cluster that adds a new transaction-labeled fraudulent smart-contract data point.
Response to Remark 1: Examiner respectfully disagrees, as the currently cited references (e.g. Li, Vijayan, Jakobsson, and Krishnamoorthy) teach the amended claim language that the applicant noted in their remarks, as shown at least in paragraphs 381-382, and 358 of Vijayan, and as further outlined in paragraphs 25-28 of this action. Li teaches a blockchain risk-scoring framework, including ‘data comprising a contract based transaction executable on the blockchain storage system’, comparing new data to ‘past data in a memory’, communicating the measure of risk, and ‘adding the data to a memory in the analysis system’. Vijayan supplies the smart contract specific training/labeling context because wallets ‘report outcomes of transactions’, the scoring component computes a ‘score for the smart contract’, and the system weighs abuse logs, complaints that ‘the smart contract drained their account without delivering the digital asset; m and AI/ML associations with ‘previously malevolent smart contracts’.
Moreover, the claim limitation “wherein at least a portion of the data points in the cluster of data points is labeled as a training smart contract linked with a corresponding requested electronic transaction” is non-functional descriptive material not functionally involved in a step/function recited. Any associated step/function would be performed the same regardless of the descriptive material since the step/function does not explicitly interact therewith. Limitations that are not functionally interrelated with the useful acts, structure, or properties of the claimed invention carry little or no patentable weight. Thus, this descriptive material will not distinguish the claimed invention from the prior art in terms of patentability. See In re Ngai, 70 USPQ2d 1862 (CAFC 2004); In re Gulack, 703 F.2d 1381, 1385, 217 USPQ 401, 404 (Fed. Cir. 1983); In re Lowry, 32 F.3d 1579, 32 USPQ2d 1031 (Fed. Cir. 1994). Accordingly, this contention is unpersuasive.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-4, and 6-20 are rejected under 35 U.S.C. 103 as being unpatentable over Li et al. (US Pub. 2021/0042421 Al) (hereinafter “Li”) in view of Jakobsson et al. (US20230006976A1) (hereinafter “Jakobsson”) in view of Vijayan et al. (US20230325814A1) (hereinafter “Vijayan”) and Krishnamoorthy et al. (US20200042723A1) (hereinafter “Krishnamoorthy”).
As per Claim 1, 8, and 15, Li teaches:
“A method comprising: training, by a server, a computer model to identify a risk score for a requested electronic transaction corresponding to an interaction with a smart contract to conduct the requested electronic transaction, the smart contract corresponding to a blockchain, wherein the computer model is trained based on one or more characteristics associated with a plurality of training smart contracts corresponding to the blockchain; the one or more characteristics including a cluster of data points, (“A target model template may be pulled from a database of model templates, segmented by types or requests, jurisdictions, user data and other attributes.” (Para. 0027); “Using the new data, the blockchain 105, using an algorithm, delivers a customized score and saves it to the blockchain 105. The score may be on a scale and the scale may be set according to the user. For example, some users may want a number on a 100 point scale while other users may desire a simple letter grade and other users may desire a text categorical variable.” (Para. 0053); “In some embodiments, the ratings may be refined over time. Machine learning may be used to analyze past ratings in view of the actual results. Machine learning may be used to review a training group of past risk rating data and determine risk ratings moving forward. FIG. 5 may illustrate sample artificial intelligence (AI) training data according to one or more embodiments. As an example and not a limitation, an artificial intelligence system may trained by analyzing a set of training data 605. The training data may be broken into sets, such as set A 610, set B 615, set C 620 and set D 625. As illustrated in FIG. 6A, one set may be using as a testing set (say set D 625) and the remaining sets may be used as training set (set A 610, set B 615 and set C 620). The artificial intelligence system may analyze the training set (set A 610, set B 615 and set C 620) and use the testing set (set D 625) to test the model create from the training data. Then the data sets may shift as illustrated in FIG. 6B, where the test data set may be added to the training data sets (say set A 610, set B 615 and set D 625) and one of the training data sets that have not been used to test before (say set C 620) may be used as the test data set. The analysis of the training data (set A 610, set B 615 and set D 625) may occur again with the new testing set (set C 620) being used to test the model and the model may be refined. The rotation of data sets may occur repeatedly until all the data sets have been used as the test data sets. The model then may be considered complete and the model may then be used on additional data sets.” (Para. 0056).
detecting, by the server. . ., the interaction by the . . . with the smart contract corresponding to the blockchain”: (See “an action may be determined based on the risk score. In some cases, the risk score may be over a threshold and events may begin automatically. For example, if the risk score is over a threshold for a particular project, the project may be automatically rejected and the method may end at block 455.” Para. 0057; “The analysis element may include computer executable code for receiving data added to the blockchain and for determining a risk score for the data added to the blockchain based on an analysis of the data representing the contract on the blockchain.” Para. 0078).
responsive to detecting the interaction, executing, by the server, the computer model to identify risk score for the requested electronic transaction corresponding to the interaction with the smart contract (“The analysis element may include computer executable code for receiving data added to the blockchain and for determining a risk score for the data added to the blockchain based on an analysis of the data representing the contract on the blockchain.” Para. 0078; “Machine learning may be used to review a training group of past risk rating data and determine risk ratings moving forward . . . an artificial intelligence system may trained by analyzing a set of training data 605. The training data may be broken into sets, such as set A 610, set B 615, set C 620 and set D 625. As illustrated in FIG. 6A, one set may be using as a testing set (say set D 625) and the remaining sets may be used as training set (set A 610, set B 615 and set C 620). The artificial intelligence system may analyze the training set (set A 610, set B 615 and set C 620) and use the testing set ( set D 625) to test the model create from the training data. Then the data sets may shift as illustrated in FIG. 6B, where the test data set may be added to the training data sets (say set A 610, set B 615 and set D 625) and one of the training data sets that have not been used to test before (say set C 620) may be used as the test data set. The analysis of the training data (set A 610, set B 615 and set D 625) may occur again with the new testing set (set C 620) being used to test the model and the model may be refined.” Para. 0056; “The base line score may be determined and a secure form of the final model may be included in the blockchain 105 for this contract.” Para. 0052; “Logically, the score is modified anytime a new partner joins in. A partner may be a contributor (employee) or an investor. The potential data may include: Partner's reputation based on prior transactions. Partner's ego net (who are they connected with) reputation. This score may dynamically reflect the riskiness of the endeavor for the potential loan-issuing partner. Potential partners can initially review the calculated new score based on their interaction to make a decision about joining. If they proceed with joining, the new score will be saved to a blockchain at block 470. If the score is unacceptable, the method may end at block 455”. Para. 0059 - 0063).
determining, by the server, that the risk score for the requested electronic transaction satisfies a threshold indicating that the requested electronic transaction is fraudulent; and (“Investors may be presented the risk rating and the investors may then decide whether to invest or to withdraw from a project.” (Para. 0064); “In response to the risk score 850 being over a threshold, members of blockchain may be alerted of the risk score 850. In addition, the risk score 850 may be communicated to parties looking to join the blockchain. In some embodiments, if the risk score 850 is over a threshold, the contract may be terminated from executing on the blockchain storage system.” (Para. 0071); “FIG. 7 may illustrate a sample blockchain platform. A user 101 may login to the user database 705, which may entail submitting some identification 707 to be authorized using data from the user database 705. The identification 707 may take on many forms such as an ID and password to biometric identification to second channel confirmations to encrypted key exchanges.” (Para. 0069).
responsive to the risk score satisfying the threshold, causing, by the server, at least one graphical element of a graphical user interface associated with the decentralized digital wallet to provide an indication of a risk associated with the requested electronic transaction. (“user interface may be used to create the initial blockchain for the project at hand. A user interface may be available for the relevant parties”. Para. 0090; “In response to the risk score being over a threshold, members of blockchain may be alerted of the risk score. In addition, the risk score may be communicated to parties looking to join the blockchain.” Para. 0088.)
. . ..
Li does not disclose:
“the one or more characteristics including a cluster of data points that associate at least one fraudulent smart contract of the one or more smart contracts with a corresponding requested electronic transaction.” (claim 1).
However, as per Claim 1, Vijayan in the analogous art of securing blockchain transactions in smart contract-based environments, teaches:
“. . . the one or more characteristics including a cluster of data points that associate at least one fraudulent smart contract of the one or more smart contracts with a corresponding requested electronic transaction. . .”. (See “The smart contract (2310) may be retrieved by an indicator provider (2320) and analyzed using an analysis function (2325) producing an indicator (2330) comprising a plurality of indicator vectors (2332, 2334, 2335).”, Para. 0339); “The first wallet (2540) and/or the second wallet (2541) may subsequently report outcomes of transactions, as indicated by arrow 2590 and arrow 2595 respectively, back to a scoring component (2550)”, Para. 0350); “a buyer of an NFT may publicly complain on a marketplace platform that the smart contract drained their account without delivering the digital asset.”, Para. 0354))
It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the method of Li, which determines a risk score for blockchain data by comparing new data against new data against past data stored in an analysis-system memory and using that stored corpus as a training group for ML-based risk ratings, with the technique of Vijayan, which analyzes an individual smart contract to generate an indicator comprising multiple indicator vectors and then augments that indicator with transaction-level outcomes, abuse logs, and buyer complaints to score the contract, to include representing the one or more characteristics used for Li’s risk scoring as a cluster of data points that associates at least one fraudulent smart contract with the corresponding requested electronic transactions that produced evidence of abuse. Therefore, the incentives of improving smart-contract-level fraud detection by reusing Vijayan’s multi-feature, compliant and outcome driven scoring representation inside Li’s existing blockchain risk engine provided a reason to make an adaptation, and invention resulted from application of the prior knowledge in a predictable manner.
Li does not disclose:
“wherein at least a portion of the data points in the cluster of data points is labeled as fraudulent training smart contract linked with a corresponding requested electronic transaction.” (claim 1).
However, as per Claim 1, Vijayan in the analogous art of securing blockchain transactions in smart contract-based environments, teaches:
“wherein at least a portion of the data points in the cluster of data points is labeled as fraudulent training smart contract linked with a corresponding requested electronic transaction” (“The wallet provider and/or third party entity may also compile a database over time that includes records of known risky smart contracts which may be examined during testing for possible malicious interactions during execution of the smart contract.” (Para. 0382); “The wallet may use test techniques such as fuzz testing, Monte Carlo simulations, and/or a machine learning algorithm to spot check possible outcomes from interacting with the smart contract and/or submitting a proposed transaction. Through these means the wallet may discover potentially undesirable outcomes and may inform the user accordingly.” (Para. 0381); “scores can be based on statistical methods taking as input previously computed security scores and observations relating to the behavior of the smart contract, e.g., whether it was malicious or not, buggy or not, representing human-facing descriptions or not.” (Para. 0358))
It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the method of Li with the technique of Vijayan to include labeling at least a portion of the data points in the cluster as fraudulent training smart contracts linked with corresponding requested electronic transactions. Therefore, the incentives of improving blockchain transaction risk scoring with known malicious smart-contract examples provided a reason to make an adaptation, and the invention resulted from application of the prior knowledge in a predictable manner.
Li does not disclose:
“in response to providing the indication of the risk, updating, by the server, the cluster of data points to include the requested electronic transaction associated with the smart contract as a data point that corresponds to the decentralized digital wallet.” (claim 1).
However, as per Claim 1, Jakobsson in the analogous art of securing blockchain transactions in token-based environments, teaches:
“. . . in response to providing the indication of the risk, updating, by the server, the cluster of data points to include the requested electronic transaction associated with the smart contract as a data point that corresponds to the decentralized digital wallet. . .”. (See “may additionally employ a model trained, refined, or updated to reflect the activities of the owning wallet and/or user.”. Para. 0419); “the fact that the human owner of the source wallet has flagged a transaction as fraudulent may be used as a further input into a neural network.”. Para. 0326); “determine the safety of a given pending transaction, e.g., based on information about recent trends in payment requests by other wallets.”. Para. 0418).
It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the method of Li, determining and communicating a risk score for blockchain transaction data and then adding that same data back into an analysis-system memory, with the technique of Jakobsson, training and updating wallet-specific machine learning to reflect wallet activities and using transactions identified as suspicious or fraudulent as further inputs, to include updating a cluster of data points after providing an indication of risk by inserting the requested electronic transaction associated with a smart contract as a new data point corresponding to the decentralized digital wallet. Therefore, the incentives of maintaining an adaptive, wallet-aware fraud model that continuously learns each scored smart-interaction provided a reason to make an adaptation, and the invention resulted from application of the prior knowledge in a predictable manner.
Li does not disclose:
“that is communicatively coupled with a decentralized digital wallet.” (claim 1).
However, as per Claim 1, Jakobsson in the analogous art of securing blockchain transactions in token-based environments, teaches:
“. . .that is communicatively coupled with a decentralized digital wallet. . .”. (See “digital wallets”) can enable users to obtain NFTs that prove purchase of rights to access a particular piece of media content on one platform and use the NFT to gain access to the purchased content on another platform. The consumption of such content may be governed by content classification directed to visual user interface systems.”. Para. 0130; “the digital wallet may securely store rich media NFTs and/or other tokens. Additionally, in some embodiments, the digital wallet may display user interface through which user instructions concerning data access permissions can be received.”. Para. 0193.)
It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the method of Li with the technique of Osborn to include a digital wallet in a blockchain system. Therefore, the incentives of providing increased system accessibility for the user provided a reason to make an adaptation, and the invention resulted from application of the prior knowledge in a predictable manner.
Li does not disclose:
“. . . and causing, by the server, the . . . to perform a secondary authentication via a notification provided on the at least one graphical element of the graphical user interface.” (claim 1).
However, as per Claim 1, Krishnamoothy in the analogous art of blockchain transactions, teaches:
“. . . and causing, by the server, the . . . to perform a secondary authentication via a notification provided on the at least one graphical element of the graphical user interface. . .”. (See “Policy manager 130, upon receipt of the risk score associated with a user 105, compares the risk score with a policy threshold score or policy score range, previously set. . . An “attention required” state (identified with a “7” within a circle) indicates that the determined risk score for the user 105 is ambiguous (i.e., neither too high nor too low), and that a further security measure(s) may be applied to the user 105's attempt to access the protected digital resources. The further security measure(s) may include triggering a re-authentication process 140, such as, for example, step-up authentication or multi-factor authentication, for user 105 by authentication server(s) 120.”. (Para. 0019); “If the user authentication server 120 receives an “attention required” indication (ATTENTION REQUIRED—block 545), then user authentication server 120 initiates an extra security measure (block 570)(FIG. 5C). In one implementation, the extra security measure may include a “touch ID” or “push to verify” process by which risk assessment platform 100 initiates a pop-up window or message at the user 105's device 110 that requests the user 105 to push a button on the device 110 to verify receipt of the message. In this “touch ID” process, pushing of the button upon the user 105's device may, in itself, be used as a verification of the identity of user 105. In other implementations, when the button is pushed by the user 105 (e.g., with a particular finger) upon the device 110, a biometric scan of the user 105's fingerprint may be taken via a touch screen of the device 110. The scanned fingerprint may then be used for verification of the identity of the user 105 such as by comparison with a previously stored biometric scan of the user 105's fingerprint.” (Para. 0046); “FIGS. 8A and 8B depict an example of a “touch ID” process performed at a device 110. As shown in FIG. 8A, a pop-up window 810 is displayed via a touch screen display 800 of device 110 in response to a request from risk assessment platform 100. Upon selection of the pop-up window 810 by the user 105 (e.g., touching the displayed window upon the touch screen display 800), a “touch ID” window 820 is displayed via touch screen display 800 of device 110, as further shown in FIG. 8B. The user 105, using a finger, may reject the “touch ID” request by touching the “reject” button 840, or may accept the “touch ID” request by touching, using a particular finger (e.g., the index finger), a touch region 830 of the “touch ID” window 820.” (Para. 0047).
It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the method of Li with the technique of Krishnamoothy to include a pop-up graphical notification prompting secondary authentication when a threshold is exceeded. Therefore, the incentives of providing increased user security provided a reason to make an adaptation, and the invention resulted from application of the prior knowledge in a predictable manner.
Regarding claim 1, The limitation “causing, by the server, the decentralized digital wallet to perform a secondary authentication via a notification provided on the at least one graphical element of the graphical user interface” is interpreted as the intended use of the “that causes” step, such that it has been considered but does not patentably distinguish the claims from the prior art because it fails to add any steps and is thereby regarded as intended use language. A recitation of the intended use of the claimed invention must result in additional steps. See Bristol-Myers Squibb Co. v. Ben Venue Laboratories, Inc., 246 F.3d 1368, 1375-76, 58 USPQ2d 1508, 1513 (Fed. Cir. 2001) (Where the language in a method claim states only a purpose and intended result, the expression does not result in a manipulative difference in the steps of the claim.) The recitation of the intended use of the claimed invention does not serve to differentiate the claim from the prior art. See MPEP 2103 I C. See also MPEP 2111.04(I) “However, the court noted that a "‘whereby clause in a method claim is not given weight when it simply expresses the intended result of a process step positively recited.’" Id. (quoting Minton v. Nat’l Ass’n of Securities Dealers, Inc., 336 F.3d 1373, 1381, 67 USPQ2d 1614, 1620 (Fed. Cir. 2003))”.
As per Claim 2, Li teaches:
“The method of claim 1, wherein causing the at least one graphical element to provide the indication of the risk corresponds to revising a visual attribute of the at least one graphical element.” (“user interface may be used to create the initial blockchain for the project at hand. A user interface may be available for the relevant parties”. Para. 0090; “the block 1 901 may also contain transaction data 940. Block 2 902 and block 3 903 may contain similar types of data with the information being specific to the transaction represented by each block 902, 903. In response to the risk score being over a threshold, members of blockchain may be alerted of the risk score. In addition, the risk score may be communicated to parties looking to join the blockchain. In some embodiments, if the risk score is over a threshold, the contract may be terminated from executing on the blockchain storage system.” Para. 0088; “The risk analysis function may execute and may store a risk score for the funding. Project 0 860 and Project 1 861 may withdraw funds from the investment blockchain and each project may have its own risk level. The risk levels of the projects may be analyzed by the risk analysis function and the updated risk score may be stored in block 1 on the blockchain 810. Project 2 862 with another risk score may return funds to the investment blockchain 810 which may be further analyzed by the risk analysis function. User 2 802 and User 3 803 may then add funds to the investment blockchain and the investment may be recorded in block 2 and 3 on the investment blockchain.” Para. 0071.)
As per Claim 3, Li teaches:
“The method of claim 1, wherein the at least one graphical element is displayed as a notification.” (“user interface may be used to create the initial blockchain for the project at hand. A user interface may be available for the relevant parties”. Para. 0090; “In response to the risk score being over a threshold, members of blockchain may be alerted of the risk score. In addition, the risk score may be communicated to parties looking to join the blockchain.” Para. 0088.)
As per Claim 4, Li teaches:
“The method of claim 3, wherein the . . . causes the requested electronic transaction to be processed in response to receiving a positive response to the notification. (“user interface may be used to create the initial blockchain for the project at hand.” Para. 0090; “an action may be determined based on the risk score. In some cases, the risk score may be over a threshold and events may begin automatically. For example, if the risk score is over a threshold for a particular project, the project may be automatically rejected and the method may end at block 455. In other examples, the score may be below a threshold and the project may proceed to block 460.”. Para. 0057.)
Li does not disclose:
“decentralized digital wallet.” (claim 4).
However, as per Claim 4, Osborn in the analogous art of blockchain transactions, teaches:
“. . . decentralized digital wallet. . .”. (See “the request can be generated by a wallet application 112 or other payment client executed by a client device 102. The wallet application 112 can generate and output a graphical interface that includes the confidence score and allows a user to make a more informed decision”. Para. 0018; “wallet application 112 can be configured to automatically allow the proposed transaction to proceed with the digital asset transfer to the destination blockchain address when the confidence score exceeds a predefined threshold.”. Para. 0053.)
It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the method of Li with the technique of Osborn to include a digital wallet in a blockchain system. Therefore, the incentives of providing system accessibility for the user provided a reason to make an adaptation, and the invention resulted from application of the prior knowledge in a predictable manner.
As per Claim 6, Li teaches:
“The method of claim 1, further comprising: generating, by the server, a score associated with the . . ., the score corresponding to a number of transactions associated with the decentralized digital wallet having a risk score that satisfies the threshold. (See Figure 6, “Machine learning may be used to review a training group of past risk rating data and determine risk ratings moving forward . . . an artificial intelligence system may trained by analyzing a set of training data 605. The training data may be broken into sets, such as set A 610, set B 615, set C 620 and set D 625. As illustrated in FIG. 6A, one set may be using as a testing set (say set D 625) and the remaining sets may be used as training set (set A 610, set B 615 and set C 620). The artificial intelligence system may analyze the training set (set A 610, set B 615 and set C 620) and use the testing set ( set D 625) to test the model create from the training data. Then the data sets may shift as illustrated in FIG. 6B, where the test data set may be added to the training data sets (say set A 610, set B 615 and set D 625) and one of the training data sets that have not been used to test before (say set C 620) may be used as the test data set. The analysis of the training data (set A 610, set B 615 and set D 625) may occur again with the new testing set (set C 620) being used to test the model and the model may be refined.” Para. 0056).
Li does not disclose:
“decentralized digital wallet.” (claim 6).
However, as per Claim 6, Osborn in the analogous art of blockchain transactions, teaches:
“. . . decentralized digital wallet. . .”. (See “the request can be generated by a wallet application 112 or other payment client executed by a client device 102. The wallet application 112 can generate and output a graphical interface that includes the confidence score and allows a user to make a more informed decision”. Para. 0018; “wallet application 112 can be configured to automatically allow the proposed transaction to proceed with the digital asset transfer to the destination blockchain address when the confidence score exceeds a predefined threshold.”. Para. 0053.)
It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the method of Li with the technique of Osborn to include a digital wallet in a blockchain system. Therefore, the incentives of providing system accessibility for the user provided a reason to make an adaptation, and the invention resulted from application of the prior knowledge in a predictable manner.
As Per Claim 7, Li teaches:
“The method of claim 1, wherein causing the at least one graphical element to provide the indication of the risk corresponds to inactivating the at least one graphical element, such that a user associated with the . . . can no longer interact with the at least one graphical element.” (“user interface may be used to create the initial blockchain for the project at hand. A user interface may be available for the relevant parties”. Para. 0090; See Figure 8, Element 863 ‘Project_3 (risk score D)’: “Exit the program because of the high risk score”; “The risk rating may then exceed a threshold for some users 805 and some users 805 may exit the investment blockchain which again may cause the risk score 850 to be updated. In response to the risk score 850 being over a threshold, members of blockchain may be alerted of the risk score 850.” Para. 0071; “an action may be determined based on the risk score. In some cases, the risk score may be over a threshold and events may begin automatically. For example, if the risk score is over a threshold for a particular project, the project may be automatically rejected and the method may end at block 455.” Para. 0057).
Li does not disclose:
“decentralized digital wallet.” (claim 7).
However, as per Claim 7, Osborn in the analogous art of blockchain transactions, teaches:
“. . . decentralized digital wallet. . .”. (See “the request can be generated by a wallet application 112 or other payment client executed by a client device 102. The wallet application 112 can generate and output a graphical interface that includes the confidence score and allows a user to make a more informed decision”. Para. 0018; “wallet application 112 can be configured to automatically allow the proposed transaction to proceed with the digital asset transfer to the destination blockchain address when the confidence score exceeds a predefined threshold.”. Para. 0053.)
It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the method of Li with the technique of Osborn to include a digital wallet in a blockchain system. Therefore, the incentives of providing system accessibility for the user provided a reason to make an adaptation, and the invention resulted from application of the prior knowledge in a predictable manner.
As per Claim 9, Li teaches:
“The system of claim 8, wherein causing the at least one graphical element to provide the indication of the risk corresponds to revising a visual attribute of the at least one graphical element.” (“user interface may be used to create the initial blockchain for the project at hand. A user interface may be available for the relevant parties”. Para. 0090; “the block 1 901 may also contain transaction data 940. Block 2 902 and block 3 903 may contain similar types of data with the information being specific to the transaction represented by each block 902, 903. In response to the risk score being over a threshold, members of blockchain may be alerted of the risk score. In addition, the risk score may be communicated to parties looking to join the blockchain. In some embodiments, if the risk score is over a threshold, the contract may be terminated from executing on the blockchain storage system.” Para. 0088; “The risk analysis function may execute and may store a risk score for the funding. Project 0 860 and Project 1 861 may withdraw funds from the investment blockchain and each project may have its own risk level. The risk levels of the projects may be analyzed by the risk analysis function and the updated risk score may be stored in block 1 on the blockchain 810. Project 2 862 with another risk score may return funds to the investment blockchain 810 which may be further analyzed by the risk analysis function. User 2 802 and User 3 803 may then add funds to the investment blockchain and the investment may be recorded in block 2 and 3 on the investment blockchain.” Para. 0071.)
As per Claim 10, Li teaches:
“The system of claim 8, wherein the at least one graphical element is displayed as a notification. (“user interface may be used to create the initial blockchain for the project at hand. A user interface may be available for the relevant parties”. Para. 0090; “In response to the risk score being over a threshold, members of blockchain may be alerted of the risk score. In addition, the risk score may be communicated to parties looking to join the blockchain.” Para. 0088.)
As per Claim 11, Li teaches:
“The system of claim 10, wherein the . . . causes the requested electronic transaction to be processed in response to receiving a positive response to the notification. (“user interface may be used to create the initial blockchain for the project at hand.” Para. 0090; “an action may be determined based on the risk score. In some cases, the risk score may be over a threshold and events may begin automatically. For example, if the risk score is over a threshold for a particular project, the project may be automatically rejected and the method may end at block 455. In other examples, the score may be below a threshold and the project may proceed to block 460.”. Para. 0057.)
Li does not disclose:
“decentralized digital wallet.” (claim 11).
However, as per Claim 11, Osborn in the analogous art of blockchain transactions, teaches:
“. . . decentralized digital wallet. . .”. (See “the request can be generated by a wallet application 112 or other payment client executed by a client device 102. The wallet application 112 can generate and output a graphical interface that includes the confidence score and allows a user to make a more informed decision”. Para. 0018; “wallet application 112 can be configured to automatically allow the proposed transaction to proceed with the digital asset transfer to the destination blockchain address when the confidence score exceeds a predefined threshold.”. Para. 0053.)
It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the method of Li with the technique of Osborn to include a digital wallet in a blockchain system. Therefore, the incentives of providing system accessibility for the user provided a reason to make an adaptation, and the invention resulted from application of the prior knowledge in a predictable manner.
As per Claim 12, Li teaches:
“The system of claim 8, wherein the instructions further cause the server to: initiate a new authentication method for the requested transaction.” (See Figure 4, “At block 435, indexes may be rebuilt. As the transaction and data related to the request may be updated, the indexes that represent the machine learning results may be rebuilt with the updated data. . . At block 440, sub-model may be rebuilt. Logically, if there is new data, such as new members to a transaction or new market conditions, the model should take in to account the new data. Thus, the sub-model may be re-built to take into account the new data and related analysis.” Para. 0049; See also Figure 8, “Project 0 860 and Project 1 861 may withdraw funds from the investment blockchain and each project may have its own risk level. The risk levels of the projects may be analyzed by the risk analysis function and the updated risk score may be stored in block 1 on the blockchain 810. Project 2 862 with another risk score may return funds to the investment blockchain 810 which may be further analyzed by the risk analysis function.” Para. 0071.)
As per Claim 13, Li teaches:
“The system of claim 8, wherein the instructions further cause the server to: generate a score associated with the . . ., the score corresponding to a number of transactions associated with the . . . having a risk score that satisfies the threshold. (See Figure 6, “Machine learning may be used to review a training group of past risk rating data and determine risk ratings moving forward . . . an artificial intelligence system may trained by analyzing a set of training data 605. The training data may be broken into sets, such as set A 610, set B 615, set C 620 and set D 625. As illustrated in FIG. 6A, one set may be using as a testing set (say set D 625) and the remaining sets may be used as training set (set A 610, set B 615 and set C 620). The artificial intelligence system may analyze the training set (set A 610, set B 615 and set C 620) and use the testing set ( set D 625) to test the model create from the training data. Then the data sets may shift as illustrated in FIG. 6B, where the test data set may be added to the training data sets (say set A 610, set B 615 and set D 625) and one of the training data sets that have not been used to test before (say set C 620) may be used as the test data set. The analysis of the training data (set A 610, set B 615 and set D 625) may occur again with the new testing set (set C 620) being used to test the model and the model may be refined.” Para. 0056).
Li does not disclose:
“decentralized digital wallet.” (claim 13).
However, as per Claim 13, Osborn in the analogous art of blockchain transactions, teaches:
“. . . decentralized digital wallet. . .”. (See “the request can be generated by a wallet application 112 or other payment client executed by a client device 102. The wallet application 112 can generate and output a graphical interface that includes the confidence score and allows a user to make a more informed decision”. Para. 0018; “wallet application 112 can be configured to automatically allow the proposed transaction to proceed with the digital asset transfer to the destination blockchain address when the confidence score exceeds a predefined threshold.”. Para. 0053.)
It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the method of Li with the technique of Osborn to include a digital wallet in a blockchain system. Therefore, the incentives of providing system accessibility for the user provided a reason to make an adaptation, and the invention resulted from application of the prior knowledge in a predictable manner.
As Per Claim 14, Li teaches:
“The system of claim 8, wherein causing the at least one graphical element to provide the indication of the risk corresponds to inactivating the at least one graphical element, such that a user associated with the . . . can no longer interact with the at least one graphical element.” (“user interface may be used to create the initial blockchain for the project at hand. A user interface may be available for the relevant parties”. Para. 0090; See Figure 8, Element 863 ‘Project_3 (risk score D)’: “Exit the program because of the high risk score”; “The risk rating may then exceed a threshold for some users 805 and some users 805 may exit the investment blockchain which again may cause the risk score 850 to be updated. In response to the risk score 850 being over a threshold, members of blockchain may be alerted of the risk score 850.” Para. 0071; “an action may be determined based on the risk score. In some cases, the risk score may be over a threshold and events may begin automatically. For example, if the risk score is over a threshold for a particular project, the project may be automatically rejected and the method may end at block 455.” Para. 0057).
Li does not disclose:
“decentralized digital wallet.” (claim 14).
However, as per Claim 14, Osborn in the analogous art of blockchain transactions, teaches:
“. . . decentralized digital wallet. . .”. (See “the request can be generated by a wallet application 112 or other payment client executed by a client device 102. The wallet application 112 can generate and output a graphical interface that includes the confidence score and allows a user to make a more informed decision”. Para. 0018; “wallet application 112 can be configured to automatically allow the proposed transaction to proceed with the digital asset transfer to the destination blockchain address when the confidence score exceeds a predefined threshold.”. Para. 0053.)
It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the method of Li with the technique of Osborn to include a digital wallet in a blockchain system. Therefore, the incentives of providing system accessibility for the user provided a reason to make an adaptation, and the invention resulted from application of the prior knowledge in a predictable manner.
As per Claim 16, Li teaches:
“The system of claim 15, wherein causing the at least one graphical element to provide the indication of the risk corresponds to revising a visual attribute of the at least one graphical element.” (“user interface may be used to create the initial blockchain for the project at hand. A user interface may be available for the relevant parties”. Para. 0090; “the block 1 901 may also contain transaction data 940. Block 2 902 and block 3 903 may contain similar types of data with the information being specific to the transaction represented by each block 902, 903. In response to the risk score being over a threshold, members of blockchain may be alerted of the risk score. In addition, the risk score may be communicated to parties looking to join the blockchain. In some embodiments, if the risk score is over a threshold, the contract may be terminated from executing on the blockchain storage system.” Para. 0088; “The risk analysis function may execute and may store a risk score for the funding. Project 0 860 and Project 1 861 may withdraw funds from the investment blockchain and each project may have its own risk level. The risk levels of the projects may be analyzed by the risk analysis function and the updated risk score may be stored in block 1 on the blockchain 810. Project 2 862 with another risk score may return funds to the investment blockchain 810 which may be further analyzed by the risk analysis function. User 2 802 and User 3 803 may then add funds to the investment blockchain and the investment may be recorded in block 2 and 3 on the investment blockchain.” Para. 0071.)
As per Claim 17, Li teaches:
“The system of claim 15, wherein the at least one graphical element is displayed as notification.” (“user interface may be used to create the initial blockchain for the project at hand. A user interface may be available for the relevant parties”. Para. 0090; “In response to the risk score being over a threshold, members of blockchain may be alerted of the risk score. In addition, the risk score may be communicated to parties looking to join the blockchain.” Para. 0088.)
As per Claim 18, Li teaches:
“The system of claim 17, wherein the . . . causes the requested electronic transaction to be processed in response to receiving a positive response to the notification.” (“user interface may be used to create the initial blockchain for the project at hand.” Para. 0090; “an action may be determined based on the risk score. In some cases, the risk score may be over a threshold and events may begin automatically. For example, if the risk score is over a threshold for a particular project, the project may be automatically rejected and the method may end at block 455. In other examples, the score may be below a threshold and the project may proceed to block 460.”. Para. 0057.)
Li does not disclose:
“decentralized digital wallet.” (claim 18).
However, as per Claim 18, Osborn in the analogous art of blockchain transactions, teaches:
“. . . decentralized digital wallet. . .”. (See “the request can be generated by a wallet application 112 or other payment client executed by a client device 102. The wallet application 112 can generate and output a graphical interface that includes the confidence score and allows a user to make a more informed decision”. Para. 0018; “wallet application 112 can be configured to automatically allow the proposed transaction to proceed with the digital asset transfer to the destination blockchain address when the confidence score exceeds a predefined threshold.”. Para. 0053.)
It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the method of Li with the technique of Osborn to include a digital wallet in a blockchain system. Therefore, the incentives of providing system accessibility for the user provided a reason to make an adaptation, and the invention resulted from application of the prior knowledge in a predictable manner.
As per Claim 19, Li teaches:
“The system of claim 15, wherein the server is further configured to: initiate a new authentication method for the requested transaction.” (See Figure 4, “At block 435, indexes may be rebuilt. As the transaction and data related to the request may be updated, the indexes that represent the machine learning results may be rebuilt with the updated data. . . At block 440, sub-model may be rebuilt. Logically, if there is new data, such as new members to a transaction or new market conditions, the model should take in to account the new data. Thus, the sub-model may be re-built to take into account the new data and related analysis.” Para. 0049; See also Figure 8, “Project 0 860 and Project 1 861 may withdraw funds from the investment blockchain and each project may have its own risk level. The risk levels of the projects may be analyzed by the risk analysis function and the updated risk score may be stored in block 1 on the blockchain 810. Project 2 862 with another risk score may return funds to the investment blockchain 810 which may be further analyzed by the risk analysis function.” Para. 0071.)
As per Claim 20, Li teaches:
“The system of claim 15, wherein the server is further configured to: generate a score associated with the . . ., the score corresponding to a number of transactions associated with the decentralized digital wallet having a risk score that satisfies the threshold. (See Figure 6, “Machine learning may be used to review a training group of past risk rating data and determine risk ratings moving forward . . . an artificial intelligence system may trained by analyzing a set of training data 605. The training data may be broken into sets, such as set A 610, set B 615, set C 620 and set D 625. As illustrated in FIG. 6A, one set may be using as a testing set (say set D 625) and the remaining sets may be used as training set (set A 610, set B 615 and set C 620). The artificial intelligence system may analyze the training set (set A 610, set B 615 and set C 620) and use the testing set ( set D 625) to test the model create from the training data. Then the data sets may shift as illustrated in FIG. 6B, where the test data set may be added to the training data sets (say set A 610, set B 615 and set D 625) and one of the training data sets that have not been used to test before (say set C 620) may be used as the test data set. The analysis of the training data (set A 610, set B 615 and set D 625) may occur again with the new testing set (set C 620) being used to test the model and the model may be refined.” Para. 0056).
Li does not disclose:
“decentralized digital wallet.” (claim 20).
However, as per Claim 20, Osborn in the analogous art of blockchain transactions, teaches:
“. . . decentralized digital wallet. . .”. (See “the request can be generated by a wallet application 112 or other payment client executed by a client device 102. The wallet application 112 can generate and output a graphical interface that includes the confidence score and allows a user to make a more informed decision”. Para. 0018; “wallet application 112 can be configured to automatically allow the proposed transaction to proceed with the digital asset transfer to the destination blockchain address when the confidence score exceeds a predefined threshold.”. Para. 0053.)
It would have been obvious to one of ordinary skill in the art before the effective filing date to combine the method of Li with the technique of Osborn to include a digital wallet in a blockchain system. Therefore, the incentives of providing system accessibility for the user provided a reason to make an adaptation, and the invention resulted from application of the prior knowledge in a predictable manner.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Justin A. Jimenez whose telephone number is (571)270-3080. The examiner can normally be reached on 8:30 AM - 5:00 PM.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, John W. Hayes can be reached on 571-272-6708. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/Justin Jimenez/
Patent Examiner, Art Unit 3697
/ARI SHAHABI/Primary Examiner, Art Unit 3697
Prosecution Insights