DETAILED ACTION
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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 01/08/2026 has been entered.
Status of Claims
Claims 1, 5, 15, and 20 have been amended. Claim 21 is new. Claims 1-21 are pending and presented for examination.
Response to Arguments
Applicant’s amendment, filed 01/08/2026, to claim 5 has overcome the previous claim objection. Therefore, the claim objection to claim 5 has been withdrawn.
Applicant's arguments, filed 01/08/2026, regarding the 35 U.S.C. 101 rejection of claims 1-20 have been fully considered, but they are not persuasive.
Response to remarks under “I. The Claims Are Not “Directed To” an Abstract Idea (Step 2A, Prong One)”
The remarks are relying on features not being claimed. For example, claim 1 does not require use of specialized technical tools, e.g. TOR browsers, proxies, to access non-indexed networks, or using a transfer entropy algorithm. Claim 21 recites “using a transfer entropy,” which is analogous to using a value. Transfer entropy is a measure, or statistic. Using a measure or statistic does not require a particular machine and can be practically performed in the human mind or by a human using a pen and paper. Even if using a transfer entropy were to be interpreted as using an algorithm/calculation, this would fall under another abstract idea: mathematical calculation. Therefore, the remarks do not pertain to what is being claimed and cannot be persuasive.
Response to remarks under “II. The Claims Integrate the Alleged Exception into a Practical Application (Step 2A, Prong Two)”
The limitation “generate a multi-dimensional structure” was grouped under the abstract idea of mental processes. The remarks appear to suggest that such limitation was an additional element, and therefore, has not provided any evidence as to why such limitation cannot fall under mental processes. Aside from the generic computing components, the additional elements were “obtain blockchain data…,” “obtain open web data,” and “obtain non-open web data…” The remarks have not provided any evidence as to why these additional elements integrate the judicial exception into a practical application.
When the limitations are considered individually and as a whole in combination, the claims do not improve the functioning of the computer itself. Allowing the computer to identify risks, as asserted by the remarks, is the same as using the computer as a tool to perform the abstract idea. Using the computer as a tool is not improving the computer itself. At most, it is improving the process of ranking cryptocurrency addresses by using a computer. The process of ranking cryptocurrency addresses is not a technology or technical field. Furthermore, the claimed invention has not claimed any limitations that would require a particular machine to transform “disparate, unstructured data from the dark web and structured data from the blockchain into a unified structure.” There is nothing technical about clustering keywords and identifying potentially nefarious use of a cryptocurrency address, generating a multi-dimensional data structure, or performing a causality analysis using obtained data. Such processes are not claimed in sufficient detail that would suggest the requirement of a particular machine to perform the operations.
Response to remarks under “III. The Claims Recite an Inventive Concept (Step 2B)”
Per MPEP 2106.05 – “The search for an inventive concept should not be confused with a novelty or non-obviousness determination… As made clear by the courts, the "‘novelty’ of any element or steps in a process, or even of the process itself, is of no relevance in determining whether the subject matter of a claim falls within the § 101 categories of possibly patentable subject matter."”
Furthermore, the claimed invention does not claim using causality algorithm, it is claiming using a transfer entropy, which is a measure or statistic. Therefore, the claimed invention is using a value to perform a causality analysis. When the limitations are considered individually and as an ordered combination, they amount to no more than using a value to rank cryptocurrency addresses. At most, this is an improvement to the ranking process itself, but it is not an improvement to the functioning of a computer, technology, or technical field.
Please see below for an updated patent eligibility analysis in light of the amendments.
Response to remarks under “Claim Rejection Under 35 U.S.C. 103”
The instant specification discloses in [0042] – “TE may measure the amount of directed transfer of information between two random processes (such as transactions between cryptocurrency addresses).” Therefore, the interpretation that the transfer of information is analogous to Kuchar’s financial/transaction values is reasonable at least based on what the instant specification discloses. Furthermore, in light of the amendments, the remarks related to the “amount of information” is not relevant to what is being claimed. The amendments now claim “transfer of information,” not “amount of information transferred.”
The claimed invention does not claim “uses the results of the causality analysis (the information transfer metric) to populate or weigh the data structure used for ranking.” The multi-dimensional data structure is generated based on the obtained data, not the causality analysis. Furthermore, Lee was used to disclose “indications of whether the at least one cryptocurrency address has interacted with the at least one dark web address,” not Kuchar.
Applicant’s remarks regarding the combination of Kuchar and Lee do not contain any evidence as to why modifying Kuchar with Lee would change the principle operation of Kuchar. Providing a conclusory statement without any evidence cannot be persuasive. Furthermore, the claimed invention does not require “amount of information transferred.” Therefore, the remarks regarding the claimed invention requiring a fundamentally different metric – “amount of information transferred” – is not relevant to what is being claimed.
However, Examiner agrees that Kuchar et al. U.S. 2021/0192526 in view of Lee et al. “Cybercriminal Minds: An Investigative Study of Cryptocurrency Abuses in the Dark Web,” and further in view of Vlahovic et al. U.S. 2023/0113795 do not disclose the newly amended limitation. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Razak et al. “Quantifying ‘Causality’ in Complex Systems: Understanding Transfer Entropy.”
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 1-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1:
Claims 1-21 fall into at least one of the four categories of statutory subject matter. The eligibility analysis proceeds to Step 2A.1.
Step 2A.1:
The limitations of independent claim 1 have been denoted with letters by the Examiner for easy reference. Independent claims 15 and 20 recite similar distinguishing features as claim 1, therefore the following eligibility analysis shall also apply to claims 15 and 20.
a memory configured to store at least one cryptocurrency address; and
one or more processors coupled to the memory, the one or more processors being configured to:
obtain blockchain data, the blockchain data comprising data indicative of a plurality of cryptocurrency transactions;
obtain open web data;
obtain non-open web data, the non-open web data comprising at least dark web data indicative of a plurality of dark web cryptocurrency transactions;
extract one or more keywords from the non-open web data;
analyze, using a machine learning model, a plurality of cryptocurrency addresses and the extracted one or more keywords by clustering the one or more keywords into one or more groups, wherein at least one of the one or more groups indicates nefarious purposes, and identifying, based on the one or more groups of keywords, a potentially nefarious use of a cryptocurrency address from the plurality of cryptocurrency addresses;
generate a multi-dimensional data structure for at least one cryptocurrency address based on the obtained blockchain data, the obtained open web data, and the obtained non-open web data, wherein the multi-dimensional data structure comprises one or more indications of whether at least one cryptocurrency address has interacted with the at least one dark web address;
perform a causality analysis on the blockchain data to measure a directed transfer of information between two random processes associated with the two or more of the plurality of cryptocurrency addresses to determine a causal relationship;
determine a reputation ranking for the at least one cryptocurrency address based on the generated multi-dimensional data structure, based on the analysis of the plurality of cryptocurrency addresses and the extracted one or more keywords and based on the causality analysis; and
output, using a user interface, the determined reputation ranking for the at least one cryptocurrency address.
Under the broadest reasonable interpretation, F-J recite limitations that are reasonably categorized under mental processes - concepts performed in the human mind or by a human using a pen and paper, including observation, evaluation, judgment, opinion. Analyzing the data to determine a ranking can be reasonably performed in the human mind or by a human using a pen and paper.
Claims 1, 15, and 20 recite at least one abstract idea. The eligibility analysis proceeds to Step 2A.2.
Step 2A.2:
The judicial exception is not integrated into a practical application. In particular, claim 1 recites the additional element(s) not in bold above.
Limitations A-B of claim 1, “using a user interface” of claims 1, 15, and 20, and the “non-transitory computer-readable storage media” and “one or more processors” of claim 20 are all recited at a high-level of generality (see [0033], [0087], [0106] of the instant application for general definitions of the identified elements). The abstract idea in claims 1, 15, and 20 are merely software instructions that as an ordered combination with the additional elements amount to no more than a computer that is programmed to carry out the abstract idea. These additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea MPEP 2106.05(f).
Limitations C-E and K amount to no more than necessary data gathering and outputting. Such mere data gathering and outputting are recited at a high-level of generality, and thus, are insignificant extra-solution activity. These limitations do not impose any meaningful limits on the claim because all uses of the recited judicial exception require such data gathering and output MPEP 2106.05(g).
In limitation G, “using a machine learning model” is recited at a high-level of generality such that it provides nothing more than mere instructions to implement an abstract idea on a generic computer. The machine learning model is used to generally apply the abstract idea without placing any limits on how the machine learning model functions, and/or how the analyzing is accomplished. Furthermore, the recitation of “using a machine learning model” merely indicates a field of use or a technological environment in which the judicial exception is performed. Therefore, this limitation is no more than generally linking the use of the judicial exception to a particular technological environment or field of use MPEP 2106.05(h).
When the additional elements are considered individually and as an ordered combination with the abstract idea, claims 1, 15, and 20 amount to no more than mere software instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. These additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Claims 1, 15, and 20 do not recite additional elements that integrate the judicial exception into a practical application. The eligibility analysis proceeds to Step 2B.
Step 2B:
The additional elements, both individually and as an ordered combination, do not amount to significantly more than the judicial exception because the outcome of the considerations at Step 2B will be the same when considerations from Step 2A.2 are re-evaluated. Furthermore, as discussed above in Step 2A.2, limitations C-E and K are recited at a high level of generality such that it amounts to receiving or transmitting data over a network, which has been determined by the courts to be well-understood, routine, and conventional activity when claimed in a generic manner MPEP 2106.05(d), subsection II.
As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply the exception in a generic computer environment. Mere instructions to apply an exception in a generic computing environment and/or using a generic computer component cannot provide an inventive concept.
Claims 1, 15, and 20 are not patent eligible.
Dependent Claims
Dependent claims 2-5, 7-10, 13-14, 16-19, and 21 elaborate on the abstract idea identified above without reciting any new additional elements. When the limitations are considered individually and as a whole in combination with the independent claims from which they depend, the claims do not recite additional elements that amount to significantly more than the judicial exception.
Dependent claim 6 recites “the one or more processors are configured to execute a machine learning algorithm.” The limitation is an additional element. However, as noted above, this limitation has been recited at a high-level of generality such that it is no more than mere instructions to implement an abstract idea on a generic computer because it does not meaningfully limit how the neighborhood is determined. Furthermore, the limitations is no more than generally linking the use of the judicial exception to a particular technological environment or field of use. When the limitation is considered individually and as a whole in combination with the independent claim from which it depends, the claim does not recite additional elements that amount to significantly more than the judicial exception.
Dependent claim 11 recites “apply a user configurable weighted formula.” This limitation recites another abstract idea: mathematical concepts, including mathematical relationships, mathematical formulas or equations, mathematical calculations. Applying a formula is considered a mathematical formula and/or mathematical calculation. The claim does not recite any new additional elements. When the limitation is considered individually and as a whole in combination with the independent claim from which it depends, the claim does not recite additional elements that amount to significantly more than the judicial exception.
Dependent claim 12 is directed to a user interface that provides a link to the determined reputation ranking. This limitation is considered an additional element. However, it has been recited in a high-level of generality such that it is an insignificant extra-solution activity because it amounts to no more than mere data outputting. Data outputting on a user interface amounts to no more than receiving or transmitting data over a network, which has been determined by the courts to be well-understood, routine, and conventional activity when claimed in a generic manner. When the limitation is considered individually and as a whole in combination with the independent claim from which it depends, the claim does not recite additional elements that amount to significantly more than the judicial exception. As noted in the interview summary 09/12/2025, Examiner suggested incorporating elements from [0035] of the specification for patent subject matter eligibility, including elements related to “insert a link…” and any additional language required to clarify the claimed invention. This includes, but is not limited to, “scan a web page…search for cryptocurrency addresses..” from [0035] of the specification. Since the amended language merely provides a link, the subject matter is still considered patent ineligible.
In summary, the dependent claims considered both individually and as an ordered combination do not provide meaningful limitations to transform the abstract idea(s) into a patent eligible application such that the abstract idea amounts to significantly more than the abstract idea itself. The claims do not recite an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or provide meaningful limitations beyond generally linking an abstract idea to a particular technological environment. Therefore, claims 1-21 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
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 1-10 and 14-21 are rejected under 35 U.S.C. 103 as being unpatentable over Kuchar et al. U.S. 2021/0192526 (herein referred to as “Kuchar”), in view of Lee et al. “Cybercriminal Minds: An Investigative Study of Cryptocurrency Abuses in the Dark Web,” (herein referred to as “Lee”), in view of Razak et al. “Quantifying ‘Causality’ in Complex Systems: Understanding Transfer Entropy” (herein as “Razak”), and further in view of Vlahovic et al. U.S. 2023/0113795 (herein referred to as “Vlahovic”).
Re Claim 1, Kuchar discloses a cryptocurrency ranking system comprising:
a memory configured to store at least one cryptocurrency address [0107]; and
one or more processors coupled to the memory, the one or more processors being configured to [0105], [0107]:
obtain blockchain data, the blockchain data comprising data indicative of a plurality of cryptocurrency transactions Fig. 3, 302, [0039];
obtain open web data ([0039] – “acquires and processes a variety of types of data, such as custody and fraud data,” [0050] – “The databases may be provided by public entities (i.e. open web data)”);
obtain non-open web data […] ([0039] – “acquires and processes a variety of types of data, such as custody and fraud data,” [0050] – “The databases may be provided by…and/or private entities (i.e. non-open web data)”);
analyze, using a machine learning model, a plurality of cryptocurrency addresses […] ([0084] – “a scoring model (e.g. a machine learned model),” [0083] – “scoring models 700 that are used to generate trust scores for a blockchain address,” thereby suggesting the address is analyzed in order for a trust score to be generated);
generate a multi-dimensional data structure for the at least one cryptocurrency address based on the obtained blockchain data, the obtained open web data, and the obtained non-open web data […] (Fig. 6B, [0037], [0040], [0073-74] – generation of a graph data structure based on blockchain data, fraud data);
perform a causality analysis on the blockchain data […] ([0064] – “In some implementations, the blockchain processing module 202-2 may determine values associated with the amount of funds transacted by a blockchain address. For example, the blockchain processing module 202-2 may determine: 1) a total amount of funds received by the blockchain address, 2) a total amount of funds sent by the blockchain address, 3) the total amount of funds transacted in and out of the blockchain address, and 4) the average transaction amount for the blockchain address, [0068] – “In some implementations, the blockchain processing module 202-2 may determine values associated with how the blockchain address interacts with other blockchain addresses.” The instant specification discloses in [0042] - “causality analysis 122 may include one or more algorithms using Transfer Entropy (TE)…TE may measure the amount of directed transfer of information between two random processes (such as transactions between cryptocurrency addresses).” Therefore, the instant specification suggests that the analysis of the claimed invention can include the transactions between the addresses).
determining a trust score […] for the at least one cryptocurrency address based on the generated multi-dimensional data structure based on the analysis of the plurality of cryptocurrency addresses […] and based on causality analysis ([0080] – “generate one or more trust scores for a blockchain address based on the scoring features associated with the blockchain address,” [0079] – scoring features may be based on the graph, i.e. generated multi-dimensional data structure, [0081] – “the scoring features based on any of the blockchain values described herein,” i.e. analysis of the plurality of cryptocurrency addresses and causality analysis).
However, Kuchar do not expressly disclose
the non-open web data comprising at least dark web data indicative of a plurality of dark web cryptocurrency transactions;
extract one or more keywords from the non-open web data;
analyze the extracted one or more keywords by clustering the one or more keywords into one or more groups, wherein at least one of the one or more groups indicates nefarious purposes, and identifying, based on the one or more groups of keywords, a potentially nefarious use of a cryptocurrency address from the plurality of cryptocurrency addresses;
wherein the multi-dimensional data structure comprises one or more indications of whether the at least one cryptocurrency address has interacted with at least one dark web address;
determining a reputation ranking for the at least one cryptocurrency address based on the extracted one or more keywords.
Lee discloses a study of cryptocurrency abuses in the dark web. Specifically, Lee discloses
the non-open web data comprising at least dark web data indicative of a plurality of dark web cryptocurrency transactions (pg. 2, Col. 1, 2nd paragraph – collecting dark web data comprising dark websites and cryptocurrency addresses to understand usage of cryptocurrency);
extract one or more keywords from the non-open web data (pg. 4, Col. 2, 2nd paragraph – “They then extract text information from visited pages and store the information to a distributed database,” Table II – the extracted addresses – Since the claimed invention has not provided any limitations on what can constitute a keyword, under the broadest, most reasonable interpretation, the addresses are reasonably analogous to one or more keywords);
analyze the extracted one or more keywords (Figure 2, B. Extracting cryptocurrency addresses – “the Address extraction module filters out invalid and unnecessary cryptocurrency addresses,” i.e. analyze the keywords) by clustering the one or more keywords into one or more groups, wherein at least one of the one or more groups indicates nefarious purposes (C. Classifying illicit Bitcoin addresses – “classify 5,440 Bitcoin addresses (i.e. one or more keywords) into the two categories: benign and potentially illicit addresses,” i.e. one or more groups, potentially illicit addresses being a group that indicates a nefarious purpose), and identifying, based on the one or more groups of keywords, a potentially nefarious use of a cryptocurrency address from the plurality of cryptocurrency addresses (C. Classifying illicit Bitcoin addresses – the Bitcoin addresses are classified into either the benign or potentially illicit addresses category, classifying an address as a potentially illicit address is the same as identifying a potentially nefarious use of such classified address);
wherein the multi-dimensional data structure comprises one or more indications of whether the at least one cryptocurrency address has interacted with at least one dark web address (pg. 2, Col. 1, 3rd paragraph – analysis findings include illicit uses of Bitcoin on the dark web, indicating bitcoin addresses used for illicit intent, i.e. indication that a bitcoin address interacted with a dark website).
determine a taint value […] for the at least one cryptocurrency address based on the extracted one or more keywords (pg. 9, Col. 2, 3rd paragraph – “computation of the taint values of each destination Bitcoin address,” Col. 1, 2nd paragraph – taint analysis models based on how much BTCs flows into each destination Bitcoin address from a given Bitcoin address, i.e. extracted one or more keywords).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine Kuchar’s blockchain transaction safety system and method with the teachings of collecting and analyzing cryptocurrency transactions within the dark web in Lee. One would be motivated to make this combination to prevent illicit cryptocurrency activities Lee, pg. 3, III. Motivation and Challenges, 3rd paragraph.
However, Kuchar in view of Lee do not explicitly teach the following limitations in italics:
perform a causality analysis on the blockchain data to measure a directed transfer of information between two random processes associated with the two or more of the plurality of cryptocurrency addresses to determine a causal relationship.
Razak discloses using transfer entropy to measure causality. Specifically, Razak discloses
perform a causality analysis on the blockchain data to measure a directed transfer of information between two random processes associated with the two or more of the plurality of cryptocurrency addresses to determine a causal relationship (pg. 2, Transfer Entropy – X and Y are the two random processes, using transfer entropy can determine if Y causes X, 1st paragraph – “Continuing the assumption that Y causes X, one would expect the relationship between X and Y to be asymmetric and that the information flows in a direction from the source Y to the target X,” source Y and target X are analogous to two random processes associated with the two or more of the plurality of cryptocurrency addresses).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Kuchar in view of Lee’s causality analysis on blockchain data to include the teachings of using transfer entropy to determine a causal relationship in Razak. Transfer entropy is a well-known causality measure Razak, pg. 2, 4th paragraph – “two of the most popular ‘causality’ measure are…Transfer Entropy,” therefore, the combination is applying a known technique to a known device, method, or product ready for improvement to yield predictable results.
However, Kuchar in view of Lee and Razak do not explicitly teach the following limitations in italics:
determine a reputation ranking for the at least one cryptocurrency address based on the generated multi-dimensional data structure, based on the analysis of the plurality of cryptocurrency addresses and the extracted one or more keywords and based on the causality analysis; and
output, using a user interface, the determined reputation ranking for the at least one cryptocurrency address.
Vlahovic discloses generating a tokenized reputation score associated with a blockchain account address. Specifically, Vlahovic disclose
determine a reputation ranking for the at least one cryptocurrency address based on the generated multi-dimensional data structure and based on the analysis of the plurality of cryptocurrency addresses and the extracted one or more keywords and based on the causality analysis [0065] – “The reputation score 212 can be expressed in a variety of ways, including but not limited to…a ranking,” [0100] – “the reputation score 212 can be generated based on additional data or property associated with the blockchain account address 208”; and
output, using a user interface, the determined reputation ranking for the at least one cryptocurrency address ([0065-66] – display an indication of the reputation score, displayed via a client device 106, i.e. user interface).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine Kuchar in view of Lee and Razak’s blockchain transaction safety system and method with the teachings of determining a reputation ranking and outputting the reputation ranking in Vlahovic. The combination teaches determining and outputting a reputation ranking for each of the blockchain addresses based on a variety of received/obtained data, such as those as taught in Kuchar, Lee and Razak. One would be motivated to make this combination because providing a reputation ranking can help overcome the challenges of establishing a reputation online when conducting interactions over the Internet Vlahovic, [0003-4].
Re Claim 2, Kuchar in view of Lee, Razak, and Vlahovic teach the cryptocurrency ranking system of claim 1, and Kuchar in view of Lee, Razak, and Vlahovic further teach wherein the one or more processors are further configured to, prior to generating the multi-dimensional data structure for the at least one cryptocurrency address, determine a neighborhood associated with the at least one cryptocurrency address, the neighborhood comprising at least one of first cryptocurrency addresses transactionally associated with the at least one cryptocurrency address or second cryptocurrency addresses transactionally associated with the at least one of the first cryptocurrency addresses (Kuchar, [0068] – determine how the blockchain address interact with other blockchain addresses).
Re Claim 3, Kuchar in view of Lee, Razak, and Vlahovic teach the cryptocurrency ranking system of claim 2, and Kuchar in view of Lee, Razak, and Vlahovic further teach wherein as part of determining the neighborhood, the one or more processors are further configured to:
extract open web persona data from the open web data, the open web persona data including attributes associated with a cryptocurrency user (Kuchar, Fig. 3, 300 – acquire and process custody and fraud data, [0039] – “The data acquisition and processing module 200 may store custody and fraud data 224 related to a blockchain address in the blockchain address record 220,” [0050] – “databases may be provided public entities,” i.e. open web data);
extract non-open web persona data from the non-open web data, the non-open web persona data including attributes associated with the cryptocurrency user (Kuchar, Fig. 3, 300 – acquire and process custody and fraud data, [0039] – “The data acquisition and processing module 200 may store custody and fraud data 224 related to a blockchain address in the blockchain address record 220,” [0050] – “databases may be provided by…private entities,” i.e. non-open web data;
determine whether there is a correlation between any of a plurality of addresses and the at least one cryptocurrency address based on the open web persona data and the non-open web persona data, wherein the neighborhood comprises any correlated addresses of the plurality of addresses to the at least one cryptocurrency address (Kuchar, [0068] – “the blockchain processing module 202-2 may determine the list of addresses that have interacted with the blockchain address and/or the total number of addresses that have interacted with the blockchain address…This value may be iteratively computed to determine how important an address is to its local neighborhood and the blockchain as a whole,” Fig. 5, [0040] – “The blockchain acquisition and processing module 202 may store raw and processed blockchain data 228 relevant to a blockchain address in the blockchain address record 220,” i.e. based on open web and non-open web persona data).
Re Claim 4, Kuchar in view of Lee, Razak, and Vlahovic teach the cryptocurrency ranking system of claim 2, and Kuchar in view of Lee, Razak, and Vlahovic further teach wherein as part of determining the neighborhood, the one or more processors are configured to:
perform a provenance analysis on the data indicative of the plurality of cryptocurrency transactions (Kuchar, [0068, 71, 73] – how the blockchain address interacts with other addresses and patterns of transactions are determined); and
abstract, from the data indicative of the plurality of cryptocurrency transactions, at least one of (i) an address originating a cryptocurrency transaction with the at least one cryptocurrency address (Kuchar, [0068] – “determine the list of addresses that have interacted with the blockchain address…(e.g. as senders and/or receivers)”), (ii) an address terminating the cryptocurrency transaction with the at least one cryptocurrency address, or (iii) connectivity between two or more addresses involved in the cryptocurrency transaction, wherein the at least one of the first cryptocurrency addresses comprise the at least one of (i) the address originating the cryptocurrency transaction with the at least one cryptocurrency address (Kuchar, [0068] – “determine the list of addresses that have interacted with the blockchain address…(e.g. as senders and/or receivers)”), (ii) the address terminating the cryptocurrency transaction with the at least one cryptocurrency address, or (iii) the two or more addresses involved in the cryptocurrency transaction.
Re Claim 5, Kuchar in view of Lee, Razak, and Vlahovic teach the cryptocurrency ranking system of claim 4, and Kuchar in view of Lee, Razak, and Vlahovic further teach wherein the one or more processors are further configured to perform the causality analysis on the blockchain data are further configured to perform the causality analysis on the data indicative of the plurality of cryptocurrency transactions to verify the plurality of cryptocurrency transactions (Kuchar, [0061] – “Blocks may be assigned as part of the mining process whereby actors on the blockchain compete to verify the validity of a set of transactions”).
Re Claim 6, Kuchar in view of Lee, Razak, and Vlahovic teach the cryptocurrency ranking system of claim 2, and Kuchar in view of Lee, Razak, and Vlahovic further teach wherein as part of determining the neighborhood associated with the at least one cryptocurrency address, the one or more processors are configured to execute a machine learning algorithm Kuchar, [0084] – “generate a scoring model (e.g. a machine learned model).”
Re Claim 7, Kuchar in view of Lee, Razak, and Vlahovic teach the cryptocurrency ranking system of claim 1, and Kuchar in view of Lee, Razak, and Vlahovic further teach wherein the one or more processors are further configured to, prior to generating the multi-dimensional data structure for the at least one cryptocurrency address:
extract at least one of keywords or features from the open web data (Kuchar, [0082] –behavior-based data associated with the blockchain address is analyzed against a behavior template, [0050] – data can be sourced from public entities, i.e. open web data, a behavior is analogous to a feature); and
Re Claim 8, Kuchar in view of Lee, Razak, and Vlahovic teach the cryptocurrency ranking system of claim 7, and Kuchar in view of Lee, Razak, and Vlahovic further teach wherein the one or more processors are further configured to, prior to generating the multi-dimensional data structure for the at least one cryptocurrency address:
perform an analysis on the plurality of cryptocurrency addresses and at least one of the extracted at least one of keywords or features from the open web data or the extracted at least one of keywords from the non-open web data (Kuchar, [0083] – “receive scoring features for a blockchain address and output a trust score for the blockchain address,” and “trust system can use a deep neural net to score,” i.e. perform an analysis); and
based on the analysis, determine at least one respective label for one or more of the plurality of addresses Kuchar, [0083] – “output a trust score for the blockchain address.”
Re Claim 9, Kuchar in view of Lee, Razak, and Vlahovic teach the cryptocurrency ranking system of claim 1, and Kuchar in view of Lee, Razak, and Vlahovic further teach wherein the non-open web data comprises private data Kuchar, [0050] – “The databases may be provided by…and/or private entities.”
Re Claim 10, Kuchar in view of Lee, Razak, and Vlahovic teach the cryptocurrency ranking system of claim 9, and Kuchar in view of Lee, Razak, and Vlahovic further teach wherein the multi-dimensional data structure comprises one or more indications of (i) whether the at least one cryptocurrency address is listed in at least one reputable open web page, (ii) whether the at least one cryptocurrency address has at least one interaction with an open web address, (iii) whether the at least one cryptocurrency address has at least one interaction with a suspicious open web address Kuchar, [0079] – “include…the number of fraudulent blockchain addresses with which the blockchain address has interacted,” or (iv) whether the at least one cryptocurrency address is listed in at least one dark web page.
Re Claim 14, Kuchar in view of Lee, Razak, and Vlahovic teach the cryptocurrency ranking system of claim 1, and Kuchar in view of Lee, Razak, and Vlahovic further teach wherein the multi-dimensional data structure comprises a vector (Kuchar, Fig. 6B – direction and label, i.e. vector).
Re Claims 15-19, they are the method claims of system claims 1-5, respectively. They recite similar distinguishing features as system claims 1-5. Therefore, they are rejected for the same reasons above.
Claim 20 is the non-transitory computer-readable storage media claim of system claim 1. It recites similar distinguishing features as system claim 1. Therefore, it is rejected for the same reasons above. Furthermore, Kuchar discloses a memory component that may include computer-readable instructions executed by one or more processing units [0107].
Re Claim 21, Kuchar in view of Lee, Razak, and Vlahovic teach the cryptocurrency ranking system of claim 2, and Kuchar in view of Lee, Razak, and Vlahovic further teach wherein as part of performing the causality analysis, the one or more processors are configured to:
perform the causality analysis on the blockchain data using transfer entropy Razak, pg. 2 – “Transfer Entropy”.
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify Kuchar in view of Lee’s causality analysis to include the teachings of using transfer entropy to determine a causal relationship in Razak. Transfer entropy is a well-known causality measure Razak, pg. 2, 4th paragraph – “two of the most popular ‘causality’ measure are…Transfer Entropy,” therefore, the combination is applying a known technique to a known device, method, or product ready for improvement to yield predictable results.
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Kuchar et al. U.S. 2021/0192526 (herein referred to as “Kuchar”), in view of Lee et al. “Cybercriminal Minds: An Investigative Study of Cryptocurrency Abuses in the Dark Web,” (herein referred to as “Lee”), in view of Razak et al. “Quantifying ‘Causality’ in Complex Systems: Understanding Transfer Entropy” (herein as “Razak”), and further in view of Vlahovic et al. U.S. 2023/0113795 (herein referred to as “Vlahovic”) as applied to claim 1 above, and further in view of Ludwig U.S. 2020/0402061 (herein referred to as “Ludwig”).
Re Claim 11, Kuchar in view of Lee, Razak, and Vlahovic teach the cryptocurrency ranking system of claim 1, however, Kuchar in view of Lee, Razak, and Vlahovic do not explicitly teach wherein as part of determining the reputation ranking for the at least one cryptocurrency address, the one or more processors are configured to apply a user configurable weighted formula to the multi-dimensional data structure.
Ludwig discloses a method for identifying malicious Internet content and campaigns directed to cryptocurrency transactions. Specifically, Ludwig discloses in [0035] the transaction graph can be queried by receiving selection of at least one rule from an initial pattern-based rule set, and such selection can be done by a user. As an example, the database component may select all transactions where at least ten different input transaction addresses exist, and one hundred percent of input transactions are transferred more than once to the same target address. Since the number and percent of transactions are a requirement of the query, the formula is considered “weighted.” Querying the transaction graph is analogous to “applying” a user configurable weighted formula, wherein the user selecting the at least one rule is analogous to “user configurable.” The at least one rule from a rule set is analogous to a “weighted formula.”
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine Kuchar in view of Lee, Razak, and Vlahovic’s blockchain transaction safety system and method with the teachings of applying a user configurable weighted formula to the multi-dimensional data structure in Ludwig. One would be motivated to make the combination to enrich the labeling of the transactions with reputation scores, entity identifiers, etc., and thereby enhancing visibility of malicious entities Ludwig, [0002], [0036].
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Kuchar et al. U.S. 2021/0192526 (herein referred to as “Kuchar”), in view of Lee et al. “Cybercriminal Minds: An Investigative Study of Cryptocurrency Abuses in the Dark Web,” (herein referred to as “Lee”), in view of Razak et al. “Quantifying ‘Causality’ in Complex Systems: Understanding Transfer Entropy” (herein as “Razak”), and further in view of Vlahovic et al. U.S. 2023/0113795 (herein referred to as “Vlahovic”) as applied to claim 1 above, and further in view of Dixon et al. U.S. 2012/0311705 (herein referred to as “Dixon”).
Re Claim 12, Kuchar in view of Lee, Razak, and Vlahovic teach the cryptocurrency ranking system of claim 1, and Kuchar in view of Lee, Razak, and Vlahovic further teach wherein the user interface comprises at least one of a web site interface, a smartphone application interface, a web browser plug-in interface, or a web-based application programming interface […] (Kuchar, [0023, 25, 33], Fig. 10A/B – smartphone, web browser application, web-based interface).
However, Kuchar in view of Lee, Razak, and Vlahovic do not explicitly teach
wherein the user interface provides a link to the determined reputation ranking.
Dixon discloses a system, method, and computer program product for presenting an indicia of risk reflecting an analysis within a graphical user interface. Specifically, Dixon discloses
wherein the user interface provides a link to the determined reputation ranking [0180] – “On the page will be a link to the reputation server 110 Website to get more, detailed information about the page.”
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine Kuchar in view of Lee, Razak, and Vlahovic’s blockchain transaction safety system and method with the teachings of providing a link to the determined reputation ranking in Dixon. One would be motivated to make the combination to reduce the risk of unsafe commerce and fraudulent transactions Dixon, [0166], [0301].
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Kuchar et al. U.S. 2021/0192526 (herein referred to as “Kuchar”), in view of Lee et al. “Cybercriminal Minds: An Investigative Study of Cryptocurrency Abuses in the Dark Web,” (herein referred to as “Lee”), in view of Razak et al. “Quantifying ‘Causality’ in Complex Systems: Understanding Transfer Entropy” (herein as “Razak”), and further in view of Vlahovic et al. U.S. 2023/0113795 (herein referred to as “Vlahovic”) as applied to claim 1 above, and further in view of Kim U.S. 2023/0039832.
Re Claim 13, Kuchar in view of Lee, Razak, and Vlahovic teach the cryptocurrency ranking system of claim 1, and Kuchar in view of Lee, Razak, and Vlahovic further teach wherein the at least one cryptocurrency address is at least one cryptocurrency address of a plurality of cryptocurrency addresses for a first cryptocurrency Kuchar, [0026] – “Example blockchain networks may include, but are not limited to Bitcoin, Ethereum, etc.,” and wherein the one or more processors are further configured to:
generate a respective multi-dimensional data structure for each cryptocurrency address of the plurality of cryptocurrency addresses for the first cryptocurrency based on the obtained blockchain data, the obtained open web data, and the obtained non-open web data (Kuchar, Fig. 6B, [0040], [0073-74] – graph data structure for blockchain addresses based on blockchain data, fraud data);
determining a trust score […] for the at least one cryptocurrency address based on the generated respective multi-dimensional data structure ([0080] – “generate one or more trust scores for a blockchain address based on the scoring features associated with the blockchain address,” [0079] – scoring features may be based on the graph, i.e. generated respective multi-dimensional data structure).
However, Kuchar in view of Lee and Razak do not explicitly teach the limitations in italics:
determine a respective reputation ranking for each respective cryptocurrency address based on the generated respective multi-dimensional data structure.
Vlahovic discloses generating a tokenized reputation score associated with a blockchain account address. Specifically, Vlahovic disclose
determine a reputation ranking for the at least one cryptocurrency address based on the generated multi-dimensional data structure [0065] – “The reputation score 212 can be expressed in a variety of ways, including but not limited to…a ranking,” [0100] – “the reputation score 212 can be generated based on additional data or property associated with the blockchain account address 208”; and
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine Kuchar in view of Lee and Razak’s blockchain transaction safety system and method with the teachings of determining a reputation ranking based on additional data in Vlahovic. One would be motivated to make this combination because providing a reputation ranking can help overcome the challenges of establishing a reputation online when conducting interactions over the Internet Vlahovic, [0003-4].
However, Kuchar in view of Lee, Razak, and Vlahovic do not explicitly teach the limitations in italics:
determine an overall reputation ranking for the first cryptocurrency based on the determined respective reputation rankings; and
output the determined overall reputation ranking for the first cryptocurrency.
Kim discloses a method and system for transaction of digital asset. Specifically, Kim discloses
determine an overall reputation ranking for the first cryptocurrency based on the determined respective reputation rankings ([0057] – “In the fund associated with the digital asset, the reputation determined in each of the subsequent transactions of the digital asset may be accumulated,” [0109] – “the reputation of the digital asset may be calculated,” i.e. ranked, [0003] – “digital assets such as in-game items, digital contents, cryptocurrency” thereby suggesting the digital assets can be cryptocurrency); and
output the determined overall reputation ranking for the first cryptocurrency [0095] – “the information associated with the digital asset, transaction information 624 of the digital asset…may be displayed. The digital asset transaction information 624 may include information on…the reputation”
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine Kuchar in view of Lee, Razak, and Vlahovic’s blockchain transaction safety system and method with the teachings of determining and outputting an overall reputation of a first cryptocurrency in Kim. One would be motivated to make this combination to allow purchasers of the digital asset to easily recognize the value of the digital asset Kim, [0030].
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHRISTINE DANG whose telephone number is (571)270-5880. The examiner can normally be reached M-F 9-5pm MT.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Patrick McAtee can be reached at (571) 272-7575. 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.
/CHRISTINE DANG/Examiner, Art Unit 3698