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 .
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 .
Detailed Action
Claim Rejections – 35 USC § 102/103
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 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.
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 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.
MPEP 2112 Section III.
Where applicant claims a composition in terms of a function, property or characteristic and the composition of the prior art is the same as that of the claim but the function is not explicitly disclosed by the reference, the examiner may make a rejection under both 35 U.S.C. 102 and 103, expressed as a 102/ 103 rejection. "There is nothing inconsistent in concurrent rejections for obviousness under 35 U.S.C. 103 and for anticipation under 35 U.S.C. 102." In re Best, 562 F.2d 1252, 1255 n.4, 195 USPQ 430, 433 n.4 (CCPA 1977). This same rationale should also apply to product, apparatus, and process claims claimed in terms of function, property or characteristic. Therefore, a 35 U.S.C. 102/ 103 rejection is appropriate for these types of claims as well as for composition claims.
Claims 1, 3 – 5, 8, 10, 11, 12, 15 and 17 – 19 are rejected under 35 U.S.C. 102/103 as being unpatentable over Burri (US 2019/0147156 A1) in view of Yamazaki (US 2023/0037546 A1),
Per claim 1, Burri (US 2019/0147156 A1) suggests a system comprising: a processor; and a memory communicatively coupled to the processor, the memory including instructions executable by the processor for causing the processor to perform operations comprising (see Burri para [0015] – [0019] and [0125] – [0127]): receiving a request from a device (reads on "the trigger signal may include a signal transmitted by a mobile device of the consumer," see Burri para [0027]) indicating an identity of a user (reads on "an image of the consumer requesting access to a bank account or funds for verifying identity of the consumer," see Burri para [0031]) and an intention of the user to access at least one resource (reads on "the consumer requesting access to a bank account or funds," see Burri para [0031]) of a computing system at a terminal of the computing system (reads on "the automated teller machine 120 may connect or communicate with other computer systems by near field communications, which includes, without limitation, near field communication (NFC), Bluetooth, radio frequency identification (RFID)," see Burri para [0014]);
determining, based on captured sensor data (reads on "The camera 203 may be configured to capture a video image or a still image," see Burri para [0031]), a plurality of sets of biometric data, each set of biometric data being associated with an individual (reads on "the camera 203 may also detect a distance from the consumer from other persons within a reference proximity or range from the consumer," see Burri para [0034]) of a plurality of individuals within a first predetermined distance from the terminal (reads on "If the camera 203 detects that another person is within a predetermined distance from the consumer or too close to the consumer, along with a facial expression indicative of fear or stress, the camera 203 may record an image of the instance," see Burri para [0034]);
decomposing (reads on Burri's face-recognition processing layer takes the captured facial image and maps it into an enumerated set of distinct facial sub-attributes - eye centers, eye corners, eye widths, mouth width, nose width, eye-socket depth, cheekbone shape, jaw line length, eye-to-nose distance - which is precisely the claimed "decomposing" into "a plurality of biometric sub attributes associated with the individual" (para [0031], para [0046])) at least one of the plurality of sets of biometric data (reads on "pixel coordinates may be mapped with a facial feature or a land mark of the facial image," see Burri para [0031]) into a plurality of biometric sub attributes (reads on "Features of the face may include eyes centers, inside corner of eyes, outside corner of eyes, width of eyes, width of mouth, width of the nose, depth of eye sockets, shape of cheekbones, length of jaw line, distance between eyes to nose and the like," see Burri para [0031]) associated with the individual (reads on "the mapped facial features may be extracted and stored as a facial print of a particular consumer or user," see Burri para [0031]);
retrieving (reads on storing per-user feature-point coordinates as a "face print" in a reference database and retrieves those stored coordinates for comparison at authentication (see Burri para [0032], para [0047]) - the retrieved data is, by the reference's own definition, "a plurality of stored sub attributes associated with the identity of the user.") a plurality of stored sub attributes (reads on "coordinates of various features of a face of a consumer may be stored as a face print and checked against stored reference facial image data or face prints of consumers (e.g., coordinates of various features from the reference stored image data)," see Burri para [0032]) associated with the identity of the user (reads on "checked against reference images of faces or facial features stored in a database," see Burri para [0032]);
determining a confidence score that the individual is the user (reads on "determined level of similarity is at or above a predetermined threshold," see Burri para [0047]) by comparing, using a machine learning model (reads on "The DNN face detection module may be configured to use a DNN to train to detect a face in an image and generate corresponding weights which can be used to identify a face in another analyzed image," see Burri para [0053]), the plurality of biometric sub attributes associated with the individual to the plurality of stored sub attributes (reads on "compare that identified face against the facial images in the user face image store for correspondence," see Burri para [0053]) associated with the identity (reads on "an image of the consumer requesting access to a bank account or funds for verifying identity of the consumer," see Burri para [0031]); and
performing an action (reads on "then the face recognition processing layer 313 determines that the consumer in the captured facial image is the correct consumer requesting the transaction at the ATM," see Burri para [0047]) that includes one of (i) preventing the individual from accessing the at least one resource in response to determining the confidence score is below a pre-set threshold or (ii) allowing the individual to access the at least one resource in response to determining the confidence score is above the pre-set threshold (reads on "If the level of similarity is determined to be at or above the predetermined threshold, then the face recognition processing layer 313 determines that the consumer in the captured facial image is the correct consumer requesting the transaction at the ATM," see Burri para [0047]).
Per claim 3, the prior art of record further suggests wherein the operation of receiving the request indicating the identity and the intention comprises: detecting that a user device is within (reads on "the trigger signal may include a signal transmitted by a mobile device of the consumer," see Burri para [0027]) a second predetermined distance from the terminal (reads on "near field communications, which includes, without limitation, near field communication (NFC), Bluetooth, radio frequency identification CRFID), or other communication technologies that allow direct communication," see Burri para [0014]).
Per claim 4, the prior art of record further suggests wherein the plurality of sets of biometric data includes data captured (reads on Burri's biometric capture (camera image at para [0031]: microphone voice at para [0027]) is itself triggered by the same signal that constitutes the request - the mobile-device or motion-sensor trigger of para [0040] - so the biometric data is, by construction, "data captured from the request-") from the request (reads on "The sensor 207 may further trigger a signal in response to a detection of a motion. The signal may trigger the microphone 201 to acquire sound within a vicinity. Further, the signal may also trigger the camera 203 to wake and capture an image," see Burri para [0040]).
Per claim 5, the prior art of record further suggests wherein the operations further comprise: storing (reads on Burri para [0035] explicitly conditions the storage update on the threshold comparison when the match is above the predetermined threshold (e.g., 99%), the captured facial image is "uploaded to a server to be used as an updated reference facial image." Because Burri's "facial image" and "reference facial image" are both stored as feature-coordinate face prints (para [0032], para [0046]), updating the server's reference data necessarily updates the per-user sub-attributes), in response to determining the confidence score is above the pre-set threshold (reads on "when a match is determined to be above a predetermined threshold (e.g., 99%) between the facial image captured by the camera 203 against the stored reference facial image," see Burri para [0035]), the plurality of biometric sub attributes (reads on "the facial image captured by the camera 203 may be uploaded to a server to be used as an updated reference facial image," see Burri para [0035]) into the stored sub attributes (reads on "the facial image captured by the camera 203 may be uploaded to a server to be used as an updated reference facial image," see Burri para [0035]) associated with the identity (reads on "checked against reference images of faces or facial features stored in a database," see Burri para [0032]).
Claim 8 is analyzed with respect to claim 1.
Claim 10 is analyzed with respect to claim 3.
Claim 11 is analyzed with respect to claim 4.
Claim 12 is analyzed with respect to claim 5.
Claim 15 the non-transitory computer-readable medium (see Burri para [0015] – [0019] and [0125] – [0127]) is analyzed with respect to claim 1.
Claim 17 is analyzed with respect to claim 10.
Claim 18 is analyzed with respect to claim 11.
Claim 19 is analyzed with respect to claim 12.
Claims 2, 9 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Burri in view of Kuchenski (US 2018/0047000 A1)
Per claim 2, the prior art of record suggests claim 1. The prior art of record is silent on explicitly stating to teach wherein the intention is to access the at least one resource at a time at least a predetermined time after receiving the request.
Kuchenski (US 2018/0047000 A1) is relied upon to teach
wherein the intention is to access (reads on Kuchenski's pre-staged ATM transaction model expressly contemplates "request now I access later" - the token, generated upon request, has a "life span" of 15 minutes, 3 days, or a weekly interval (para [0010], para [0016]) and is "used at a later time" to initiate the access (para [0036]) - which is exactly the claimed intention to access "at a time at least a predetermined time after receiving the request") the at least one resource at a time at least a predetermined time (reads on "the token's life span is for a fixed amount of time, e.g., 15 minutes or 3 days," see Kuchenski para [0010]) after receiving the request (reads on "The financial-transaction token is used at a later time by the currency recipient to help initiate a pre-staged financial transaction," see Kuchenski para [0036]).
Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to modify the ATM transaction-initiation architecture of Burri, which receives a consumer request at an ATM and authenticates via biometric capture, by integrating the time-deferred pre-staged-transaction token teaching of Kuchenski (see Kuchenski para [0010]: "the pre-staged transaction can be initiated by a second party by entering a token into an ATM configured to receive it. In this embodiment, the token's life span is for a fixed amount of time, e.g., 15 minutes or 3 days; alternatively, the token's life span is for a fixed number of uses, e.g., 1 time or 5 times") to realize the instant limitation that the intention is to access the at least one resource at a time at least a predetermined time after receiving the request- One or more of the underpinning rationale(s), as under KSR MPEP 2141{A, C}, support this conclusion. Accordingly, it would have been obvious to one of ordinary skill in the art to have configured Burri's ATM consumer-authentication front end to honor a request whose intended resource access is to occur at a later time - i.e., a pre-staged transaction whose token/ request is valid for a 15-minute, 3-day, or weekly window - with Kuchenski's lifetime-bounded token logic governing the deferral and Burri's biometric authentication then executing at redemption, as recited in the instant claims, by applying the lifespan-bounded pre-staged-token design pattern of Kuchenski to the existing ATM consumer-request and authentication flow of Burri. As Kuchenski itself states: "This technology allows a first party to set up a repeating pre-staged fixed-amount of currency that can be withdrawn by a second party using a reusable token- Associated with the token is a regular time interval that allows the token redeemer to receive the fixed amount of currency per time, e.g., once per week like a child's weekly allowance," (see Kuchenski para [0016]), which addresses the well-recognized problem of separating the moment of authorization from the moment of resource access at an ATM, e.g., for scheduled withdrawals, weekly allowances, and asynchronous funds transfers, One of ordinary skill in the art in ATM-based access control would have recognized that Burri's flow assumes near-contemporaneous request and authentication at the terminal and does not provide a time-deferral mechanism, and that Kuchenski's lifespan-bounded pre-staged-token model was a known, predictable solution to exactly that deferral gap, requiring no change to Burri's biometric capture, sub-attribute decomposition, face-print storage, or threshold-decision pipeline. The combination is further supported by MPEP 2141 Rationale A (combining known elements according to known methods to yield predictable results) and Rationale C (use of a known technique pre-staged token with time lifespan - to improve a similar ATM device in the same way). The motivation to combine these references is applied to all claims beneath this heading and is reinforced by their shared domain (ATM cash dispensing) and their shared architectural primitive (an ATM "configured to receive" a digital credential), so substituting Burri's contemporaneous-request assumption with Kuchenski's time-lifespan-bounded request yields the predictable result of a deferred biometric ATM access flow.
Claim 9 is analyzed with respect to claim 10.
Claim 16 is analyzed with respect to claim 11.
Claims 6, 13 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Burri in view of Kohli (US 2018/0089688 A1)
Per claim 6, the prior art of record further suggests the system of claim 1, wherein the operations further comprise, in response to determining the confidence score is below the pre-set threshold; and using another machine learning model" (reads on the second comparison being performed by Burri's "DNN face recognizer module"/ DNN trained to identify a face, see Burri para [0053]). The prior art of record is silent on explicitly stating receiving a plurality of sets of stored sub attributes associated with a plurality of users known to have attempted to access resources of the computing system without authorization; determining a fraud score representing a likelihood that the individual is a first user of the plurality of users known to have attempted to access the resources of the computing system without authorization by comparing, using another machine learning model, the plurality of biometric sub attributes associated with the individual to at least one of the plurality of stored sub attributes associated with the plurality of users known to have attempted to access the resources of the computing system without authorization; and performing another action that includes one of (i) preventing the individual from accessing the resource if the fraud score is above the pre-set threshold or (ii) allowing the individual to access the resource if the fraud score is below the pre-set threshold.
Kohli (US 2018/0089688 A1) is relied upon to teach
receiving (reads on the maintained store from which identifiers are drawn for comparison, "each of the plurality of biometric identifiers are associated with cardholders," see Kohli para [0018]) a plurality of sets of stored sub attributes" (reads on "the plurality of biometric identifiers," see Kohli para [0018]) associated with a plurality of users (reads on "associated with cardholders," see Kohli para [0018]) known to have attempted to access resources of the computing system without authorization (reads on "who have been put on a blacklist, where the cardholder committed fraudulent behavior," see Kohli para [0018]); determining (reads on "calculates a fraud score," see Kohli para [0022]) a fraud score (reads on "a fraud score," see Kohli para [0022]) representing a likelihood that the individual is a first user of the plurality of users known to have attempted to access the resources of the computing system without authorization (reads on determining "if the cardholder has been blacklisted" via match to "blacklisted cardholders," see Kohli para [00211) by comparing (reads on "By comparing the biometric identifier from the cardholder to the plurality of biometric identifiers from blacklisted cardholders," see Kohli para [0021]) the plurality of biometric sub attributes associated with the individual (reads on "the received biometric identifier," see Kohli para [0020]) to at least one of the plurality of stored sub attributes associated with the plurality of users known to have attempted to access the resources of the computing system without authorization (reads on "the stored plurality of biometric identifiers" from "blacklisted cardholders," see Kohli para [0020], para [0021]); and performing (reads on "determines to deny ... determines to approve," see Kohli para [0022]) another action that includes one of (reads on the two-branch deny/approve disposition, see Kohli para [00221) (i) preventing the individual from accessing the resource (reads on "determines to deny the payment transaction," see Kohli para [0022]) if the fraud score is above the pre-set threshold (reads on "If the fraud score exceeds a predetermined threshold," see Kohli para [0022]) (ii) allowing the individual to access the resource (reads on "Otherwise ... approve," see Kohli para [0022]) if the fraud score is below the pre-set threshold (reads on "Otherwise" [score not exceeding threshold], see Kohli para [0022]).
Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to modify the biometric ATM access-control system of Burri - which captures a consumer's facial sub-attributes, compares them against a stored reference gallery using a DNN face-recognizer to authenticate identity, and prevents or allows access based on a similarity threshold - by integrating the blacklist-driven fraud-scoring of Kohli (see Kohli para [0022]: "the biometric verification computer device calculates a fraud score based on the transaction history associated with the match·- If the fraud score exceeds a predetermined threshold, the biometric verification computer device determines to deny the payment transaction- Otherwise approve") to realize the instant limitations- One or more of the underpinning rationale(s), as discussed under KSR MPEP 2141 {(A) combining prior art elements according to known methods to yield predictable results; and (C) use of a known technique to improve similar devices in the same way}, support this conclusion- Accordingly, it would have been obvious to one of ordinary skill in the art to have taken Burri's facial sub-attribute comparison pipeline and added a second comparison stage that scores the individual's sub-attributes against a stored gallery of known bad actors, denying access when that fraud score exceeds a threshold and allowing it otherwise, as recited in the instant claims, by applying the blacklist-match-and-score technique of Kohli to the existing reference-comparison architecture of Burri. As Kohli itself states: "By comparing the biometric identifier from the cardholder to the plurality of biometric identifiers from blacklisted cardholders, the biometric verification computer device may determine if the cardholder has been blacklisted" (see Kohli para [0021]), which addresses the well-recognized problem of distinguishing a legitimate-but-low-confidence consumer from an impostor who is in fact a previously identified fraudster - a gap left open when a first-pass identity-confidence check merely falls below threshold- One of ordinary skill in the art in biometric access control would have recognized that Burri's confidence-only check cannot, by itself, determine whether a below-threshold individual is a known fraudster, and that Kohli's proven blacklist-comparison-and-fraud-score technique was a known, predictable solution to exactly that gap, requiring no change to Burri's underlying biometric capture, sub-attribute decomposition, or DNN comparison machinery. The combination is further supported by MPEP 2141 Rationale A (combining prior art elements according to known methods to yield the predictable result of a layered authenticate-then-screen-for-fraud decision) and Rationale C (using Kohli's known fraud-scoring technique to improve Burri's similar biometric device in the same way), The motivation to combine these references arises directly from the references themselves and from the common problem of unauthorized ATM access, with a reasonable expectation of success because both references already operate on stored biometric galleries and threshold comparisons, making the integration a routine combination of complementary, fully disclosed components. The motivation to combine is applied to all references under this heading.
Claim 13 is analyzed with respect to claim 6.
Claim 20 is analyzed with respect to claim 13.
Claim 7 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Burri in view of Gopinathan (US Patent No. 5819226)
Per claim 7, the prior art of record suggests the system of claim 1, wherein the operations further comprise, in response to determining the confidence score is below the pre-set threshold- The prior art of record is silent on explicitly stating retrieving a plurality of previous requests associated with the user; determining an updated confidence score by comparing a first plurality of characteristics of the request with a second plurality of characteristics associated with the plurality of previous requests, wherein the first plurality of characteristics and the second plurality of characteristics comprise one or more of resource type information, resource value information, temporal information, or terminal information; and performing another action that includes one of (i) preventing the individual from accessing the resource if the updated confidence score is below the pre-set threshold or (ii) allowing the individual to access the resource if the updated confidence score is above the pre-set threshold.
Gopinathan is relied upon to teach
retrieving (reads on "reads ... customer data from databases 805, 806," see Gopinathan col. 25 ll. 65 - col. 26 ll. 63; and customer data "includes ... data on all approved or declined transactions in the previous seven days," see Gopinathan col. 27 ll. 3-15) a plurality of previous requests (reads on "data on all approved or declined transactions in the previous seven days," see Gopinathan col. 27 ll. 3-15) associated with the user (reads on "The customer data from database 806 ... general information on the customer," see Gopinathan col. 27 ll. 3-15); determining (reads on "generates as output fraud scores," see Gopinathan col. 26 ll. 63-65) an updated confidence score (reads on the recomputed "fraud scores representing the likelihood of fraud for each transaction," construed under BRI as a second/updated confidence metric, see Gopinathan col. 26 ll. 63-65) by comparing (reads on the model that "reads current transaction data and customer data" and scores against the customer profile, see Gopinathan col. 25, ll. 60-67, col. 26, 11 60 - col. 27, ll. 15) a first plurality of characteristics of the request (reads on "The current transaction data ... includes ... transaction dollar amount; date; time ...; merchant category code; merchant ZIP code," see Gopinathan col. 26 ll. 60 - col. 27 ll. 15) with a second plurality of characteristics associated with the plurality of previous requests (reads on the "profile record which contains data describing the customer's transactional pattern over the last six months" and "Customer usage pattern[AltContent: ] profiles," see Gopinathan col. 26, 11 60 - col. 27, ll. 15; col. 7 ll. 26-col.8 ll. 34), wherein the first plurality of characteristics and the second plurality of characteristics comprise one or more of resource type information (reads on "Transaction type," see Gopinathan col. 7 ll. 26-col.8 ll. 34), resource value information (reads on "Transaction amount"/ "transaction dollar amount," see Gopinathan col. 7 ll. 26 - col.8 ll. 34; col. 26 11. 64 - col. 27 11. 2), temporal information (reads on "Transaction date and time" and "time-of-day and day-of-week profiles," see Gopinathan col. 7 ll. 26 - col.8 ll. 34; col. 26 11. 64 - col. 27 11. 2), or terminal information (reads on "merchant category code; merchant ZIP code," see Gopinathan col. 7 ll. 26-col.8 ll. 34; col. 26 ll. 64 - col. 27 ll. 2); and performing (reads on the block/forward disposition driven by the threshold comparison, see Gopinathan col. 28 ll. 1-15 and Figure 16) another action that includes one of (reads on the two-branch blocked/sent-for-authorization disposition, see Gopinathan col. 28 ll. 1-15 and Figure 16) (i) preventing the individual from accessing the resource (reads on "the transaction blocked by the authorization system," see Gopinathan col. col. 28 ll. 1-15 and Figure 16) if the updated confidence score is below the pre-set threshold (reads on "if the threshold has been exceeded" [high fraud/ low confidence], see Gopinathan col. col. 28 ll. 1-15 and Figure 16) or (ii) allowing the individual to access the resource (reads on "the low fraud score is sent to the authorization system," see Gopinathan col. col. 28 ll. 1-15 and Figure 16) if the updated confidence score is above the pre-set threshold (reads on "If the threshold is not exceeded" [low fraud/ high confidence], see Gopinathan col. col. 28 ll. 1-15 and Figure 16).
Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to modify the biometric ATM access-control system of Burri - which authenticates a consumer at an ATM by comparing captured facial sub-attributes against a stored reference using a machine learning model and a similarity threshold - by integrating the transactional-history fraud-scoring of Gopinathan (see Gopinathan col. col. 28 ll. 1-15 and Figure 16: "A fraud score (representing the likelihood of fraud for the transaction) is obtained 1606 and compared to a threshold value 1607 ... the transaction blocked by the authorization system if the threshold has been exceeded. If the threshold is not exceeded, the low fraud score is sent to the authorization system 1609") to realize the instant limitations- One or more of the underpinning rationale(s), as discussed under KSR MPEP 2141 {(A) combining prior art elements according to known methods to yield predictable results; and (G) some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to combine the references}, support this conclusion. Accordingly, it would have been obvious to one of ordinary skill in the art to have supplemented Burri's first-pass biometric confidence check with a second, history-based determination that retrieves the user's prior requests and computes an updated confidence (fraud) score by comparing current request characteristics - resource type, value, temporal, and terminal information - against the stored profile of prior requests, then preventing or allowing access on that updated score, as recited in the instant claims, by applying Gopinathan's neural-network transactional-profile scoring technique to the existing access-decision architecture of Burri. As Gopinathan itself states: "Transaction processing component 802 reads current transaction data and customer data from databases 805, 806, and generates as output fraud scores representing the likelihood of fraud for each transaction" (see Gopinathan col. 26 11. 60 - col. 28 1. 8), which addresses the well-recognized problem that a single biometric confidence reading near the threshold is insufficient to distinguish a genuine user having an off-nominal capture from an impostor whose request pattern is anomalous. One of ordinary skill in the art in fraud detection and access control would have recognized that Burri provides no fallback when its identity-confidence score is merely below threshold, and that Gopinathan's proven history-comparison scoring - already operating on per-customer prior-transaction profiles and a threshold gate was a known, predictable solution to exactly that gap, requiring no change to Burri's biometric capture or comparison machinery beyond invoking the secondary scoring when the first score falls short. The combination is further supported by MPEP 2141 Rationale A (combining the prior-art biometric check and the prior-art transactional fraud score according to known methods to yield the predictable result of a two-stage access decision) and Rationale G (Gopinathan's express teaching to score current requests against historical patterns and gate on a threshold supplies the suggestion to add this stage to Burri). The motivation arises from the references themselves and from the shared goal of preventing unauthorized access, with a reasonable expectation of success because both systems already employ threshold-gated scoring over stored per-user data, making the integration a routine, predictable combination- The motivation to combine is applied to all claims under this heading.
Claim 14 is analyzed with respect to claim 7.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Brian Shaw whose telephone number is (571)270-5191. The examiner can normally be reached on Mon-Thurs from 6:00 AM-3:30 PM.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jeff Nickerson can be reached on (469) 295-9235. The fax phone number for the organization where this application or proceeding is assigned is 703-872-9306.
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/BRIAN F SHAW/
Primary Examiner, Art Unit 2432
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