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 .
Response to Amendment
The amendment filed on 12/15/2025 has been accepted and considered in this office action. Claims 1-15 have been amended. No claims have been cancelled. No new claims have been added.
Response to Arguments
Applicant’s arguments filed on 12/15/2025, with respect to the amended limitations of the independent claims have been fully considered and are persuasive. Therefore, the outstanding 103 rejection has been withdrawn.
However, upon further consideration, a new ground(s) of rejection is made in view of discovery of new prior art Andrade (US 20180240107 A1) in view of Tu (US 20220005022 A1) as set forth below.
With respect to 101 rejection, Applicant’s arguments have been fully considered but are not persuasive.
Applicant argues that the amended claims integrate any alleged idea into a practical application because the claim allegedly provide an improvement to the functioning of computers in the form of cybersecurity and securing smart contracts executed on blockchains.
The examiner acknowledges that the amended claim 1 now recites that the first transaction is a set of data which causes execution of code of a smart contract on a blockchain, that the first transaction is uploaded to the blockchain by a wallet, that the first and second transactions are signed by the wallet, that the smart contact is monitored on the blockchain via the wallet, and that the execution of the second transaction is triggered on the blockchain via the wallet. However, these amendments do not change the character of the claim as a whole. The claim remains directed to detecting an approval of a transaction, determining risk, and revoking/un-approving the transaction when the risk exceeds a threshold.
The additional limitations merely identify generic blockchain implementation details and use them as a tool to implement the business process. A blockchain transaction being data that causes smart contract code execution, a wallet uploading/signing transaction, and execution of a blockchain transaction via a wallet are conventional blockchain environment features recited at a high level of generality.
Applicant argues that the claim address open and potentially unlimited approvals in smart contracts, thereby securing the wallet against malicious attempts to exploit vulnerabilities in the smart contract. This argument is not persuasive because the claim does not recite a specific technological mechanism for securing the wallet or preventing exploitation of a smart contract vulnerability. Instead, the claim is directed towards the functional result of generating and executing a second transaction comprising un-approval when a risk factor exceeds a predetermined threshold. The claim does not recite how the risk factor is determined, how the smart contract is monitored, how the un-approval is technically implemented, or how the malicious exploitation is prevented.
Applicant’s reliance on the specification is not persuasive. Even if the specification discloses system improves protection of assets by approval revocations of smart contracts, the claim itself must reflect the alleged improvement. The amended claim does not recite a specific technical solution instead, the claim uses generic blockchain components as a tool to perform abstract process of monitoring approvals, evaluating risks, and revoking approval when the risk exceeds a threshold.
Thus, the amended limitations do not integrate the abstract idea into a practical application.
Therefore, Applicant’s argument is ultimately not persuasive. Hence, the 101 rejection is maintained.
Claim Interpretation
Applicant’s claims and specification is rife with mis-use of terminology and using terms against their generally accepted meaning by a person of ordinary skill in the art. Applicant’s assistance is requested in clarifying what the following terms mean so that the claims can actually be interpreted and the scope can be reliably determined:
“blockchain” – This term was never used in Nakamoto’s paper and, instead, the phrase “chain” of “blocks” was used. Indeed, the term ‘blockchain’, since Nakamoto’s paper (2008), has always referred to the actual records “chained” together by embedding a hash of all prior blocks. Of note, the “blockchain” is different than the “blockchain network”, which is generally used to refer to the computerized system of nodes and peers that implement and store the blockchain. However, applicant’s claim refers to both a ‘blockchain’ and ‘blockchain network’ in separate instances, but appears to use the term ‘blockchain’ in at least one instance in lieu of the term ‘blockchain network’ (“execution of the second transaction on the blockchain via the wallet”). In all instances of ‘blockchain’, it’s unclear if applicant is referring to the ‘blockchain network’ or the actual underlying blocks of data that are “chained” together.
“transaction” – The term ‘transaction’ generally means a completed agreement or exchange between two parties. Applicant’s claim now defines this abstract business concept as ‘data’ in the instance of a ‘first transaction’. However, the claim defines the ‘second transaction’ as an abstract business concept of “unapproval of the first transaction” but then says the ‘second transaction’ is “signed” which could only ever occur to a tangible representation of a transaction. Therefore, it appears the claim should recite the ‘second transaction’ comprises data indicative of un-approval.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “rule engine” in claims 3, 4, 5, 12, 13 and 14-.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Based on applicant’s specification, the “rule engine” are being interpreted as general purpose computing hardware and/or software implementing the functions claimed. Applicant is welcome to disprove this analysis with citation to their specification outlining the structure of the rule engine.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-17 are rejected under 35 U.S.C. 101 because the claimed invention, under the broadest reasonable interpretation, is directed to an abstract idea without significantly more.
Step 1: Statutory Category
Independent claim 1 is drawn to a method, claim 9 is drawn to a non-transitory computer readable medium (CRM) storing instructions to perform the method, and claim 10 is drawn to a system. Accordingly, each of these claim group falls under one of the four categories of statutory subject matter (process/method, machines/products/apparatus, manufactures, and compositions of matter).
Step 2A: Prong 1: Judicial Exception
Under the broadest reasonable interpretation (BRI), claims 1, 9 and 10 are directed to the abstract idea:
detecting an approval of a first transaction by at least one user node connected to the approval node over a blockchain network (Mental process, human-being (risk officer) reads an approvals list (paper report) to see which instructions have been pre-approved.);
wherein the first transaction is a set of data which causes execution of code of a smart contract on a blockchain (Mental process, A risk officer receives a written instruction that, according to the office’s manual, requires him to trigger a specific clause in a paper contract.)
wherein the first transaction is uploaded to the blockchain by a wallet (Organizing human activity, a risk officer takes a completed document and files it using a specific courier bag into a public record book.)
wherein the first transaction is signed by the wallet (Mental process, a risk officer reviews the document and confirms that the document is signed)
generating a second transaction comprising un-approval of the first transaction (Mental process, risk officer drafts a revocation memo (or fills out a form) to negate the prior approval);
wherein the second transaction is signed by the wallet (Mental process, a risk officer reviews the document and confirms that the document is signed)
monitoring the smart contract on the blockchain via the wallet in order to determine a risk factor (Mental process/organizing human activity, risk officer consults the policy manual and calculates a risk score by applying those rules to this situation);
and responsive to the risk factor exceeding a pre-determined risk level threshold, triggering an execution of the second transaction on the blockchain via the wallet (Organizing human activity/mental step leading to human action, risk officer compares the paper risk score to a threshold and issues a verbal/written order to staff to carry out the revocation).
The following are directed to additional elements:
Recitations of “blockchain network”, “smart contract”, “approval node”, “user node.” In claims 1, 9 and 10.
Recitation of “rule engine” in claims 3-5 and 12-14.
Recitation of “artificial intelligence (AI) module” and “training” in claims 6-8 and 15-17.
With respect to step 2A, prong 2, the additional elements fail to integrate the abstract idea into a practical application. The claims are not directed to, or limited to, a technical solution solving a technical problem. They fail to provide an improvement to a technology or the functioning of a computer. See MPEP 2106.04 (d)(1). Instead, the additional elements merely recite, at high level of generality, general purpose computing structure that are used as tools for implementing the abstract idea. The field of use limitations (“blockchain”, “smart contract”) and generic automation (“rule engine”, “AI model”) are instructions to apply the abstract idea in a particular environment. Thus, the examiner finds the additional elements are mere instructions to implement the judicial exception. See MPEP 2106.05 (a) (e) (f). As, such the examiner must conclude the invention is not integrated into a practical application.
With respect to step 2B, the claim fails to recite significantly more than the abstract idea itself. Similar to the analysis for step 2A, prong 2, the claims fail to provide improvement to a technology of the functioning of a computer. The claims only recite well-understood, routine, and conventional components and functions: generic processors, memory, storage media, generic receiving/detecting/monitoring/computing/triggering; and high level “rule engine/AI model” automation. Thus, examiner finds the additional elements are mere instructions to implement the judicial exception. See MPEP 2106.05(f).
Therefore, the examiner concludes claims 1, 9 and 10 are directed to an abstract idea without significantly more.
Regarding claims 2 and 11, these claims recite the following limitations that further recite an abstract idea:
determining the risk factor based on any one of: elapsed pre-defined time; and a size of the wallet exceeding a pre-defined threshold (Mental process, a human-being (risk officer) notes how long an approval has been open and checks the account size threshold on paper).
There are no new additional elements recited in these claims. Thus, the analysis for step 2A, prong 2 and step 2B is identical to that found within claims 1, 9 and 10 and is hereby incorporated by reference, even with an additional consideration for the claim as a whole.
Regarding claims 3 and 12, these claims recite the following limitations that further recite an abstract idea:
revoking the first transaction by a set of instruction (Mental process/organizing human activity, risk officer hands a junior clerk a paper checklist of rules and instruct the clerk to follow the rules and file a revocation form when the conditions are met).
Wherein the set of instruction comprises rule engine. There is an additional element (“rule engine”). It merely automates the human rule application; it does not improve computer functioning. Therefore, fails step 2A, prong 2 and step 2B for the reasons above.
Regarding claims 4 and 13, these claims recite the following limitations that further recite an abstract idea:
revoking, by the set of instruction, the first transaction responsive to detection of a deposit transaction subsequent to a swap transaction. (Mental process/organizing human activity, risk officer reads the ledger entries, recognizes that a deposit followed by a swap, and decides to revoke per policy).
Wherein the set of instruction comprises rule engine. There is an additional element (“rule engine”). It merely automates the human rule application; it does not improve computer functioning. Therefore, fails step 2A, prong 2 and step 2B for the reasons above.
Regarding claims 5 and 14, these claims recite the following limitations that further recite an abstract idea:
revoking, by the set of instruction, the first transaction responsive to detection of two transactions subsequent to two swap transactions. (Mental process/organizing human activity, risk officer reads the ledger entries, recognizes that two transactions subsequent to two swap transactions, and decides to revoke per policy).
Wherein the set of instruction comprises rule engine. There is an additional element (“rule engine”). It merely automates the human rule application; it does not improve computer functioning. Therefore, fails step 2A, prong 2 and step 2B for the reasons above.
Regarding claims 6 and 15, these claims recite the following limitations that further recite an abstract idea:
computing the risk factor using a decision model trained to compute the risk factor. (Mental process, risk officer uses scorecard previously developed from past cases (e.g., +3 points if approval is older than 30 days, +5 points if account size exceeds $X). The risk officer adds the points on paper to compute the risk score).
Wherein the decision model is artificial intelligence (AI) model. There is an additional element (“artificial intelligence (AI) model”). It merely automates the human rule application; it does not improve computer functioning. Therefore, fails step 2A, prong 2 and step 2B for the reasons above.
Regarding claims 7 and 16, these claims recite the following limitations that further recite an abstract idea:
training the decision model to compute the risk factor based on monitoring of the ledger connected with other ledgers. (Mental process/organizing human activity, a review committee meets monthly, reads recent paper ledger and updates the scorecard weights (e.g., increasing the points for loan-open approvals). Human policy-update process is the “training”).
Wherein the decision model is AI model. There is an additional element (“AI model”). It merely automates the human rule application; it does not improve computer functioning.
Wherein the ledger connected with other ledgers is blockchain network. There is an additional element (“blockchain network”). It merely automates the human rule application; it does not improve computer functioning. Therefore, fails step 2A, prong 2 and step 2B for the reasons above.
Regarding claims 8 and 17, these claims recite the following limitations that further recite an abstract idea:
training the decision module to compute the risk factor based on a combination of a duration of an approval being open and a size of the policy. (Mental process/organizing human activity, the committee builds a two-axis table on paper (rows: approval-open duration buckets; columns: contract-size bucket) and sets higher weights in cells where both are larger. Then they adopt the updated table as the new scorecard).
Wherein the decision module is AI model. There is an additional element (“AI model”). It merely automates the human rule application; it does not improve computer functioning.
Wherein the policy is smart contract. There is an additional element (“smart contract”). It merely automates the human rule application; it does not improve computer functioning. Therefore, fails step 2A, prong 2 and step 2B for the reasons above.
Specification
Applicant is reminded of the proper language and format for an abstract of the disclosure.
The abstract should be in narrative form and generally limited to a single paragraph on a separate sheet within the range of 50 to 150 words in length. The abstract should describe the disclosure sufficiently to assist readers in deciding whether there is a need for consulting the full patent text for details.
The language should be clear and concise and should not repeat information given in the title. It should avoid using phrases which can be implied, such as, “The disclosure concerns,” “The disclosure defined by this invention,” “The disclosure describes,” etc. In addition, the form and legal phraseology often used in patent claims, such as “means” and “said,” should be avoided.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
Claims 1-3, 9-12 are rejected under 35 U.S.C. 103 as being unpatentable over Andrade (US 20180240107 A1) in view of Tu (US 20220005022 A1).
Regarding Claim 1, Tu teaches:
detecting an approval of a transaction by a least one user node connected to the approval node over a blockchain network (Tu, para 21, discloses client device initiating a transaction associated with blockchain and cloud transaction manager identifying approval transaction);
wherein the first transaction is a set of data which causes execution of code of a smart contract on a blockchain, wherein the first transaction is uploaded to the blockchain by a wallet (Tu, para 39, discloses smart contracts listed as a transaction type that system manages; para 22 discloses the digital wallet is the source of upload/initiate transaction to blockchain);
wherein the first transaction is signed by the wallet (Tu, para 44 discloses the digital wallet uses the private key to authorize the transaction);
Tu does not explicitly teach; However, Andrade teaches:
generating a second transaction comprising un-approval of the first transaction (Andrade, para 410 discloses in the event of risk meeting a predetermined threshold, the transaction is stopped, delayed or reversed which inherently implies generating a subsequent transaction or equivalent action to negate the original transaction)
wherein the second transaction is signed by the wallet (Andrade, para 317, 367 discloses client wallet using client’s private key to sign transaction)
monitoring the smart contract on the blockchain via the wallet in order to determine a risk factor (Andrade, para 368-369, discloses monitoring transaction against a defined set of rules (e.g., laws and/or regulations and/or by CBEM users to regulate or limit transactions) for suspicious activities and determining risk score based on suspicious findings)
and responsive to the risk factor exceeding a pre-determined risk level threshold, triggering an execution of the second transaction on the blockchain via the wallet. (Andrade, para 410 discloses in the event of risk meeting a predetermined threshold, the transaction is stopped, delayed or reversed)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have modified the teaching of Andrade by incorporating Tu’s blockchain architecture in which a digital wallet initiates, signs, and submits transactions to a blockchain network using cryptographic keys and further uses approval-based transaction workflow. One would be motivated to make such modifications in Andrade’s system to improve security, prevent fraudulent or suspicious transactions, and enhance protection of digital assets, thereby improving the overall system reliability and security.
Regarding Claim 2, Andrade/Tu teaches the method of claim 1:
Andrade teaches:
determining the risk factor based on any one of: elapsed pre-defined time and a size of wallet exceeding a pre-defined threshold. (Andrade, para 369 discloses determining risk score based on monitoring transaction size $10,000 or above or amount unusually large for the account.)
Regarding Claim 3, Andrade/Tu teaches the method of claim 1:
Andrade teaches:
revoking the first transaction by a rule engine. (Andrade, para 410 discloses the system monitors transactions against a defined set of rules (e.g., laws and/or regulations and/or by CBEM users to regulate or limit transactions) to detect suspicious activity and the transaction can be reversed.)
Regarding Claim 9, Tu teaches:
detecting an approval of a transaction by a least one user node connected to the approval node over a blockchain network (Tu, para 21, discloses client device initiating a transaction associated with blockchain and cloud transaction manager identifying approval transaction);
wherein the first transaction is a set of data which causes execution of code of a smart contract on a blockchain, wherein the first transaction is uploaded to the blockchain by a wallet (Tu, para 39, discloses smart contracts listed as a transaction type that system manages; para 22 discloses the digital wallet is the source of upload/initiate transaction to blockchain);
wherein the first transaction is signed by the wallet (Tu, para 44 discloses the digital wallet uses the private key to authorize the transaction);
Tu does not explicitly teach; However, Andrade teaches:
generating a second transaction comprising un-approval of the first transaction (Andrade, para 410 discloses in the event of risk meeting a predetermined threshold, the transaction is stopped, delayed or reversed which inherently implies generating a subsequent transaction or equivalent action to negate the original transaction)
wherein the second transaction is signed by the wallet (Andrade, para 317, 367 discloses client wallet using client’s private key to sign transaction)
monitoring the smart contract on the blockchain via the wallet in order to determine a risk factor (Andrade, para 368-369, discloses monitoring transaction against a defined set of rules (e.g., laws and/or regulations and/or by CBEM users to regulate or limit transactions) for suspicious activities and determining risk score based on suspicious findings)
and responsive to the risk factor exceeding a pre-determined risk level threshold, triggering an execution of the second transaction on the blockchain via the wallet. (Andrade, para 410 discloses in the event of risk meeting a predetermined threshold, the transaction is stopped, delayed or reversed)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have modified the teaching of Andrade by incorporating Tu’s blockchain architecture in which a digital wallet initiates, signs, and submits transactions to a blockchain network using cryptographic keys and further uses approval-based transaction workflow. One would be motivated to make such modifications in Andrade’s system to improve security, prevent fraudulent or suspicious transactions, and enhance protection of digital assets, thereby improving the overall system reliability and security.
Regarding Claim 10, Tu teaches:
detect an approval of a transaction by a least one user node connected to the approval node over a blockchain network (Tu, para 21, discloses client device initiating a transaction associated with blockchain and cloud transaction manager identifying approval transaction);
wherein the first transaction is a set of data which causes execution of code of a smart contract on a blockchain, wherein the first transaction is uploaded to the blockchain by a wallet (Tu, para 39, discloses smart contracts listed as a transaction type that system manages; para 22 discloses the digital wallet is the source of upload/initiate transaction to blockchain);
wherein the first transaction is signed by the wallet (Tu, para 44 discloses the digital wallet uses the private key to authorize the transaction);
Tu does not explicitly teach; However, Andrade teaches:
generate a second transaction comprising un-approval of the first transaction (Andrade, para 410 discloses in the event of risk meeting a predetermined threshold, the transaction is stopped, delayed or reversed which inherently implies generating a subsequent transaction or equivalent action to negate the original transaction)
wherein the second transaction is signed by the wallet (Andrade, para 317, 367 discloses client wallet using client’s private key to sign transaction)
monitor the smart contract on the blockchain via the wallet in order to determine a risk factor (Andrade, para 368-369, discloses monitoring transaction against a defined set of rules (e.g., laws and/or regulations and/or by CBEM users to regulate or limit transactions) for suspicious activities and determining risk score based on suspicious findings)
and responsive to the risk factor exceeding a pre-determined risk level threshold, trigger an execution of the second transaction on the blockchain via the wallet. (Andrade, para 410 discloses in the event of risk meeting a predetermined threshold, the transaction is stopped, delayed or reversed)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have modified the teaching of Andrade by incorporating Tu’s blockchain architecture in which a digital wallet initiates, signs, and submits transactions to a blockchain network using cryptographic keys and further uses approval-based transaction workflow. One would be motivated to make such modifications in Andrade’s system to improve security, prevent fraudulent or suspicious transactions, and enhance protection of digital assets, thereby improving the overall system reliability and security.
Regarding Claim 11, Andrade/Tu teaches the system of claim 10:
Andrade teaches:
determine the risk factor based on any one of: elapsed pre-defined time and a size of wallet exceeding a pre-defined threshold. (Andrade, para 369 discloses determining risk score based on monitoring transaction size $10,000 or above or amount unusually large for the account.)
Regarding Claim 12, Andrade/Tu teaches the system of claim 10:
Andrade teaches:
revoke the first transaction by a rule engine. (Andrade, para 410 discloses the system monitors transactions against a defined set of rules (e.g., laws and/or regulations and/or by CBEM users to regulate or limit transactions) to detect suspicious activity and the transaction can be reversed.)
Claims 4- 7, 13-16 are rejected under 35 U.S.C. 103 as being unpatentable over Andrade (US 20180240107 A1) in view of Tu (US 20220005022 A1) in view of Fang (US 11436615 B2).
Regarding Claim 4, Andrade/Tu teaches the method of claim 3:
Andrade/Tu does not explicitly teach; However, Fang teaches:
Performing an action responsive to detection of a deposit transaction subsequent to a swap transaction. (Fang, Col 2, lines 60 -Col 3 lines 3; Col 6, lines 13-58, discloses a system that monitors or tracks blockchain user actions including withdraw 124, deposit 126, swap 128 and/or a transfer 130 of funds or cryptocurrency and uses a risk policy engine and a security control system and detects suspicious behavior based on past transactions to generate high risk score and based on the high risk score the system may block, freeze or suspend the transaction and/or the account that is performing the actions.)
Fang does not explicitly teach; However, Andrade teaches:
Wherein Performing an action comprises revoking, by the rule engine, the first transaction (Andrade, para 410 discloses the system monitors transactions against a defined set of rules (e.g., laws and/or regulations and/or by CBEM users to regulate or limit transactions) to detect suspicious activity and the transaction can be reversed.)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have modified the teaching of Andrade/Tu by incorporating Fang’s method monitoring blockchain activities including swaps, deposits, withdrawals, and transfers and detecting suspicious behavior based on past transaction to generate high risk score that triggers security actions like blocking, freezing or suspending transactions. One would be motivated to make such modifications in Andrade/Tu’s system to improve security by identifying risky transactions associated with a cryptocurrency exchange to block the transaction, as well as freeze or suspend the accounts.
Regarding Claim 5, Andrade/Tu teaches the method of claim 3:
Andrade/Tu does not explicitly teach; However, Fang teaches:
Performing an action responsive to detection of two transactions subsequent to two swap transactions. (Fang, Col 2, lines 60 -Col 3 lines 3; Col 6, lines 13-58, discloses a system that monitors or tracks blockchain user actions including withdraw 124, deposit 126, swap 128 and/or a transfer 130 of funds or cryptocurrency and uses a risk policy engine and a security control system and detects suspicious behavior based on past transactions to generate high risk score and based on the high risk score the system may block, freeze or suspend the transaction and/or the account that is performing the actions.)
Fang does not explicitly teach; However, Andrade teaches:
Wherein Performing an action comprises revoking, by the rule engine, the first transaction (Andrade, para 410 discloses the system monitors transactions against a defined set of rules (e.g., laws and/or regulations and/or by CBEM users to regulate or limit transactions) to detect suspicious activity and the transaction can be reversed.)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have modified the teaching of Andrade/Tu by incorporating Fang’s method monitoring blockchain activities including swaps, deposits, withdrawals, and transfers and detecting suspicious behavior based on past transaction to generate high risk score that triggers security actions like blocking, freezing or suspending transactions. One would be motivated to make such modifications in Andrade/Tu’s system to improve security by identifying risky transactions associated with a cryptocurrency exchange to block the transaction, as well as freeze or suspend the accounts.
Regarding Claim 6, Andrade/Tu teaches the method of claim 1:
Andrade/Tu does not explicitly teach; However, Fang teaches:
computing the risk factor using an artificial intelligence (Al) model trained to compute the risk factor. (Fang, Col 7, lines 28-37; Fig 3, Step 308, 310, Fang discloses that the method 300 analyzes the digital data and transforms the digital data to an identified behavior category, thereby creating classified risk data, wherein the analyzing and transforming includes a risk classification engine including a machine learning model. In block 310, the method 300 analyzes the classified risk data and assigns a risk score to each classified risk data, wherein the analyzing and assigning includes a risk scoring regression engine and machine learning.)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have modified the teaching of Andrade/Tu by incorporating Fang’s method of computing risk factor using machine learning. One would be motivated to make such modifications in Andrade/Tu’s system to improve security by identifying risky transactions associated with a cryptocurrency exchange to block the transaction, as well as freeze or suspend the accounts.
Regarding Claim 7, Andrade/Tu/Fang teaches the method of claim 6:
Andrade/Tu does not explicitly teach; However, Fang teaches:
training the Al model to compute the risk factor (Fang, Col 7, lines 28-37; Fig 3, Step 308, 310, Fang discloses that the method 300 analyzes the digital data and transforms the digital data to an identified behavior category, thereby creating classified risk data, wherein the analyzing and transforming includes a risk classification engine including a machine learning model. In block 310, the method 300 analyzes the classified risk data and assigns a risk score to each classified risk data, wherein the analyzing and assigning includes a risk scoring regression engine and machine learning.)
based on monitoring of the blockchain network. (Fang, Col 7, lines 28-37; discloses using machine learning model trained on blockchain transaction to learn from the transaction data.)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have modified the teaching of Andrade/Tu by incorporating Fang’s method of computing risk factor using machine learning. One would be motivated to make such modifications in Andrade/Tu’s system to improve security by identifying risky transactions associated with a cryptocurrency exchange to block the transaction, as well as freeze or suspend the accounts.
Regarding Claim 13, Andrade/Tu teaches the system of claim 12:
Andrade/Tu does not explicitly teach; However, Fang teaches:
Performing an action responsive to detection of a deposit transaction subsequent to a swap transaction. (Fang, Col 2, lines 60 -Col 3 lines 3; Col 6, lines 13-58, discloses a system that monitors or tracks blockchain user actions including withdraw 124, deposit 126, swap 128 and/or a transfer 130 of funds or cryptocurrency and uses a risk policy engine and a security control system and detects suspicious behavior based on past transactions to generate high risk score and based on the high risk score the system may block, freeze or suspend the transaction and/or the account that is performing the actions.)
Fang does not explicitly teach; However, Andrade teaches:
Wherein Performing an action comprises rule engine configured to: revoke the first transaction (Andrade, para 410 discloses the system monitors transactions against a defined set of rules (e.g., laws and/or regulations and/or by CBEM users to regulate or limit transactions) to detect suspicious activity and the transaction can be reversed.)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have modified the teaching of Andrade/Tu by incorporating Fang’s method monitoring blockchain activities including swaps, deposits, withdrawals, and transfers and detecting suspicious behavior based on past transaction to generate high risk score that triggers security actions like blocking, freezing or suspending transactions. One would be motivated to make such modifications in Andrade/Tu’s system to improve security by identifying risky transactions associated with a cryptocurrency exchange to block the transaction, as well as freeze or suspend the accounts.
Regarding Claim 14, Andrade/Tu teaches the system of claim 12:
Andrade/Tu does not explicitly teach; However, Fang teaches:
Performing an action responsive to detection of two transactions subsequent to two swap transactions. (Fang, Col 2, lines 60 -Col 3 lines 3; Col 6, lines 13-58, discloses a system that monitors or tracks blockchain user actions including withdraw 124, deposit 126, swap 128 and/or a transfer 130 of funds or cryptocurrency and uses a risk policy engine and a security control system and detects suspicious behavior based on past transactions to generate high risk score and based on the high risk score the system may block, freeze or suspend the transaction and/or the account that is performing the actions.)
Fang does not explicitly teach; However, Andrade teaches:
Wherein Performing an action comprises rule engine configured to: revoke the first transaction (Andrade, para 410 discloses the system monitors transactions against a defined set of rules (e.g., laws and/or regulations and/or by CBEM users to regulate or limit transactions) to detect suspicious activity and the transaction can be reversed.)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have modified the teaching of Andrade/Tu by incorporating Fang’s method monitoring blockchain activities including swaps, deposits, withdrawals, and transfers and detecting suspicious behavior based on past transaction to generate high risk score that triggers security actions like blocking, freezing or suspending transactions. One would be motivated to make such modifications in Andrade/Tu’s system to improve security by identifying risky transactions associated with a cryptocurrency exchange to block the transaction, as well as freeze or suspend the accounts.
Regarding Claim 15, Andrade/Tu teaches the system of claim 10:
Andrade/Tu does not explicitly teach; However, Fang teaches:
an artificial intelligence (Al) module configured to compute the risk factor. (Fang, Col 7, lines 28-37; Fig 3, Step 308, 310, Fang discloses that the method 300 analyzes the digital data and transforms the digital data to an identified behavior category, thereby creating classified risk data, wherein the analyzing and transforming includes a risk classification engine including a machine learning model. In block 310, the method 300 analyzes the classified risk data and assigns a risk score to each classified risk data, wherein the analyzing and assigning includes a risk scoring regression engine and machine learning.)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have modified the teaching of Andrade/Tu by incorporating Fang’s method of computing risk factor using machine learning. One would be motivated to make such modifications in Andrade/Tu’s system to improve security by identifying risky transactions associated with a cryptocurrency exchange to block the transaction, as well as freeze or suspend the accounts.
Regarding Claim 16, Andrade/Tu/Fang teaches the system of claim 15:
Andrade/Tu does not explicitly teach; However, Fang teaches:
train the Al module to compute the risk factor (Fang, Col 7, lines 28-37; Fig 3, Step 308, 310, Fang discloses that the method 300 analyzes the digital data and transforms the digital data to an identified behavior category, thereby creating classified risk data, wherein the analyzing and transforming includes a risk classification engine including a machine learning model. In block 310, the method 300 analyzes the classified risk data and assigns a risk score to each classified risk data, wherein the analyzing and assigning includes a risk scoring regression engine and machine learning.)
based on monitoring of the blockchain network. (Fang, Col 7, lines 28-37; discloses using machine learning model trained on blockchain transaction to learn from the transaction data.)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have modified the teaching of Andrade/Tu by incorporating Fang’s method of computing risk factor using machine learning. One would be motivated to make such modifications in Andrade/Tu’s system to improve security by identifying risky transactions associated with a cryptocurrency exchange to block the transaction, as well as freeze or suspend the accounts.
Claims 8 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Andrade (US 20180240107 A1) in view of Tu (US 20220005022 A1) in view of Sequeira (EP 4475481 A1) in view of Fang (US11436615 B2).
Regarding Claim 8, Andrade/Tu/Fang teaches the method of claim 7:
Andrade/Tu does not explicitly teach; However, Fang teaches:
training the Al model to compute the risk factor based on certain condition (Fang, [Col 7, lines 30-35] discloses the use of machine learning to analyze and assigning risk score; [Col 9, lines 29-60], discloses the use of temporal, sequential, linkage, statistics, derived features which incorporate the time interval and time series entropy and maximum transaction amount, a sum of inbound and outbound amount represents quantitative/statistic features which are used by the machine leaning model for risk scoring.)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have modified the teaching of Andrade/Tu by incorporating Fang’s method of training the machine leaning model to compute risk factor based on certain conditions. One would be motivated to make such modifications in Fang’s system to improve security by identifying risky transactions associated with a cryptocurrency exchange to block the transaction, as well as freeze or suspend the accounts.
Andrade/Tu/Fang does not explicitly teach; However, Sequeira teaches:
Wherein certain condition comprises a combination of a duration of an approval being open and a size of the smart contract. (Sequeira, para 39-43, discloses that the revocation of the authorization certificate is triggered by revocation conditions such as a high number of requests within a short time or a too high amount of monetary value requested to be transferred; para 43, a time-out of requests to be responded by the requesting unit having the second certificate revoked. It may be implemented that a plurality of time-outs, e.g., a predefined number such as 3, 5 or 10 time-outs, result in the revocation of the requesting unit, because the trustworthiness is lost.)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have modified the teaching of Andrade/Tu by incorporating Sequeira method of defining certain conditions as being temporal based and value-based factors. One would be motivated to make such modifications in Andrade/Tu’s system to improve detection of suspicious or high-risk blockchain transactions by enabling the system to account for both temporal and value-based factors, both of which directly impact risk
Regarding Claim 17, Andrade/Tu/Fang teaches the system of claim 15:
Andrade/Tu does not explicitly teach; However, Fang teaches:
train the Al module to compute the risk factor based on certain condition (Fang, [Col 7, lines 30-35] discloses the use of machine learning to analyze and assigning risk score; [Col 9, lines 29-60], discloses the use of temporal, sequential, linkage, statistics, derived features which incorporate the time interval and time series entropy and maximum transaction amount, a sum of inbound and outbound amount represents quantitative/statistic features which are used by the machine leaning model for risk scoring.)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have modified the teaching of Andrade/Tu by incorporating Fang’s method of training the machine leaning model to compute risk factor based on certain conditions. One would be motivated to make such modifications in Fang’s system to improve security by identifying risky transactions associated with a cryptocurrency exchange to block the transaction, as well as freeze or suspend the accounts.
Andrade/Tu/Fang does not explicitly teach; However, Sequeira teaches:
Wherein certain condition comprises a combination of a duration of an approval being open and a size of the smart contract. (Sequeira, para 39-43, discloses that the revocation of the authorization certificate is triggered by revocation conditions such as a high number of requests within a short time or a too high amount of monetary value requested to be transferred; para 43, a time-out of requests to be responded by the requesting unit having the second certificate revoked. It may be implemented that a plurality of time-outs, e.g., a predefined number such as 3, 5 or 10 time-outs, result in the revocation of the requesting unit, because the trustworthiness is lost.)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have modified the teaching of Andrade/Tu by incorporating Sequeira method of defining certain conditions as being temporal based and value-based factors. One would be motivated to make such modifications in Andrade/Tu’s system to improve detection of suspicious or high-risk blockchain transactions by enabling the system to account for both temporal and value-based factors, both of which directly impact risk
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.
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/AMIT KHADKA/Examiner, Art Unit 2432
/Jeffrey Nickerson/Supervisory Patent Examiner, Art Unit 2432
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