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 .
Claims 1-20 are pending for examination.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 10 and 12-15 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 10 recites the limitation "the steps" in line 4. There is insufficient antecedent basis for this limitation in the claim.
Claims 12-15 each recite “the steps of”. Since Claims 1-15 are dependent claims, it is unclear whether “the steps” recited in claims 12-15 refers to: (i) only the additional steps newly introduced within claim 12 itself, (ii) the full set of steps recited in the base claim from which claim 12 (and, in turn, claims 13-15) depends, or (iii) some combination or subset thereof. This ambiguity is compounded in claims 13-15, whether it is further unclear whether “the steps” refers back to the steps of the immediately preceding claim, the steps of independent claim, or the cumulative steps introduced across the intervening dependent claims.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-3, 7, 10-12 and 16-17 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by US 20190079782 (Goldberg et al.).
Regarding Claim 1, Goldberg teaches a system for generating dynamic custom graphic user interfaces by performing adaptive pre-caching of data ([¶ 0047] FIG. 3 depicts a block diagram of the general structure of a transactional application core component (TACC) … the TACC 300 include, an authentication engine 302, a dynamic UI & UX engine 304, …a cache 308. [¶ 0065], the TACC uses predictive analysis and AI to pre-load and cache some data determined to be the data most likely to be accessed by the user …The user interface is then dynamically generated with the information and/or options based on such predictions and the user interface is subsequently provided to the user), the system comprising: at least one network communication interface ([¶ 0045] A communications interface 245); at least one non-transitory storage device; and at least one processing device coupled to the at least one non-transitory storage device and the at least one network communication interface (([Fig. 2, 0039], Memory 210, such as read only memory (ROM) and random access memory (RAM), may constitute an illustrative memory device (i.e., a non-transitory processor-readable storage medium). Such memory 210 may include one or more programming instructions stored thereon that, when executed by the processing device 205), wherein the at least one processing device is configured to:
determine initiation of an authentication request by a user via a user device to access an entity application ([¶ 0066], the systems utilized to automatically authenticate/authorize and/or re-authenticate/re-authorize one or more users. …when a user accesses the systems via any of the user interface channels, the TACC may automatically retrieve certain metadata associated with the use. [¶ 0068], the user accessing the application);
in response to determining initiation of the authentication request, capture real-time user data via the user device ([¶ 0066], the TACC may automatically retrieve certain metadata associated with the user, such as geolocation data, identification of the device used, a voice signature, an IP address, or the like [i.e., real-time user data]. [¶ 0068], a user may access the application on his/her mobile device, and information regarding the mobile device, …containing metadata may be extracted);
analyze the real-time user data to authenticate the user ([¶ 0051], Authentication may also be completed by automatically gathering information about the user based on a combination of particular attributes that are extracted automatically by the TACC 300 and/or the authentication engine 302. For example, if a particular number of metadata attributes for a particular user match, the TACC 300 and/or the authentication engine 302 may assign a particular authentication level on the scale. …may further utilize fuzzy logic or the like to analyze auto-retrieved metadata and translate the data to a particular authentication level. [¶ 0066], the TACC may access a set of rules that corresponds to the particular metadata that is accessed to match the metadata to a particular user. If a plurality of attributes match with a particular user, the user may be automatically authenticated);
perform pre-caching of data associated with the entity application on the user device based at least in part on the real-time user data and historical usage data associated with the user ([¶ 0065], the TACC uses predictive analysis and AI to pre-load and cache some data determined to be the data most likely to be accessed by the user …Such a determination may be based on, for example, social media information, user information stored within the system, information regarding historical behavior of the user, and/or automatically retrieved user attributes. [¶ 0049], The TACC 300 may further utilize the cache 308 to preload and/or cache data …can be provided to a user of the user interface channels… predict what a user may desire to access at a particular time, given particular circumstances, and/or the like, and may preload data into the cache);
dynamically generate a custom graphic user interface based on performing pre-caching of the data associated with the entity application; and present the custom graphic user interface to the user via the user device ([¶ 0065], the TACC uses predictive analysis and AI to pre-load and cache some data determined to be the data most likely to be accessed by the user …The user interface is then dynamically generated with the information and/or options based on such predictions, and the user interface is subsequently provided to the user).
Regarding Claim 2, Goldberg teaches the system of claim 1, wherein the at least one processing device is configured to analyze the real-time user data to authenticate the user based on: comparing the real-time user data with one or more user patterns; and determining if an anomaly exists between the real-time user data and the one or more user patterns ([¶ 0066], a user accesses the application and metadata is extracted. …the metadata includes, but is not limited to, geolocation data, identification of a devices that is used, voice signature data, an IP address, facial recognition data, a phone number associated with the device, data regarding security question responses, token data, and/or the like. …a determination is made as to whether the metadata for a particular attribute matches an existing user).
Regarding Claim 3, Goldberg teaches the system of claim 2, wherein the at least one processing device is configured to: determine that an anomaly does not exist between the real-time user data and the one or more user patterns; and authenticate the user ([¶ 0066], when a user accesses the systems …the TACC may automatically retrieve certain metadata associated with the user, such as geolocation data, identification of the device used, a voice signature, an IP address, or the like. In addition, the TACC may access a set of rules that corresponds to the particular metadata that is accessed to match the metadata to a particular user. If a plurality of attributes match with a particular user, the user may be automatically authenticated).
Regarding Claim 7, Goldberg teaches the system of claim 1, wherein the real-time user data comprises at least one of biometric data, behavioral data, and user device operation data ([¶ 0066], accesses the application and metadata is extracted …the metadata includes, but is not limited to, …voice signature data, …facial recognition data, …and/or the like. …a determination is made as to whether the metadata for a particular attribute matches an existing user).
Regarding Claim 10, the claim limitations are identical and/or equivalent in scope to claim 1, therefore, claim 10 is rejected under the same rationale as claim 1. Examiner further notes, Goldberg also teaches a computer program product …comprising a non-transitory computer-readable storage medium having computer executable instructions for causing a computer processor to perform the steps (Fig. 2A, ¶¶ 0039-0041) as required by Claim 10.
Regarding Claims 11 and 12, the claim limitations are identical and/or equivalent in scope to claims 2 and 3, respectively, therefore, claims 11-12 are rejected under the same rationale as claims 2-3.
Regarding Claims 16 and 17, the claim limitations are identical and/or equivalent in scope to claims 1 and 2, respectively, therefore, claims 16-17 are rejected under the same rationale as claims 1-2.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 4, 13 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Goldberg in view of US 11030287 (Obaidi).
Regarding Claim 4, Goldberg does not explicitly teach, however, Obaidi teaches the system of claim 2, wherein the at least one processing device is configured to: determine that an anomaly exists between the real-time user data and the one or more user patterns; and trigger additional authentication mechanism based on determining the anomaly ([C.7:L.10-21], the use of user-behavior-based adaptive authentication is triggered when biometric data of a user obtained by the application fails to match biometric data of an authorized user. In such an example, the application may be monitoring speech picked up by a user device as the user device is being used access a resource. Further, voiceprint analysis of the speech by the application may indicate that an authorized user has not spoken near the user device for a predetermined period of time. Accordingly, the application may trigger the authentication platform to perform user-behavior-based adaptive auth).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Obaidi’s teaching of triggering additional authentication when the real-time biometric data fails to match into Goldberg’s system of capturing real-time user metadata and analyzes it against known attributes to authenticate a user because such incorporation would improve the accuracy and security of Goldberg’s graduated authentication scheme using a known technique applied in the same field for the same predictable result.
Regarding Claims 13 and 18, the claim limitations are identical and/or equivalent in scope to claim 4, therefore, claims 13 and 18 are rejected under the same rationale as claim 4.
Claims 5, 14 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Goldberg in view of Obaidi, and further in view of US 20050097320 (Golan et al.).
Regarding Claim 5, as established in the rejection of claims 1-4 above, Goldberg in view of Obaidi teach determining that an anomaly exists between real-time user data and one or more user pattern, and triggering an additional authentication mechanism based on that determination, however, Goldberg in view of Obaidi do not explicitly teach, but Golan teaches the system of claim 4, wherein the at least one processing device is configured to: calculate an exposure rating associated with the anomaly between the real-time user data based on analyzing the real-time user data ([¶ 0039], A risk scoring module may score the risk [i.e., exposure rating] of an activity, based on for example various sources of information such as the user-computer mapping, deceive fingerprinting, velocity checks, specific users' activity profiles and histories, IP geo-location and IP hijacking detection, or additional or other sources. [¶ 0050], Divergence of the profile of specific transactions from the profile could indicate a higher level of risk. [¶ 0051], Statistical analysis intended to detect suspicious patterns of activities and suspicious deviation from regular behavior profiles. [¶ 0053], the Transaction seems riskier because the operation performed after authentication does not match the usual user profile. [¶ 0092] The decision engine may communicate with a risk module and request the event's risk score. …the risk module may use risk models, run an analysis of the event, and may return a risk score.); determine a level of the exposure rating ([¶ 0024], receive a user a request to begin a transaction…assess the risk level of a transaction, and based on the risk level, set a level of authentication for the transaction); and select a type of the additional authentication mechanism based on the level of the exposure rating ([¶ 0025], the type of authentication required of a user may be selected based on a risk assessment, for example, a set of authentication details among various sets, or a certain authentication mode may be chosen. [¶ 0057], additional authentication methods, in order to adapt the level of security or alter the authentication level requirements following assessment of the transaction risk: Shared secrets… Time sensitive secrets …Randomized secret questions …Out-of-band authentication methods …2-factor authentication. [¶ 0058], The security level of the authentication may be altered and adjusted in the following: (i) Requiring more or less information for the purpose of authenticating a particular transaction, depending on its estimated risk level. (ii) Insisting or not insisting on certain information elements, based on the risk level of the transaction. (iii) Making a certain security measure mandatory or optional).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Golan’s risk-scoring and authentication mechanism selection logic with the combined teachings of Goldberg and Obaidi, because Goldberg already computes a graduated, numeric authentication-confidence value (it’s scale of 1 to 10, fig. 11A/11B) from real-time metadata analysis, therefore, incorporating Golan’s teaching does not alter the basic operation of Goldberg, but merely enhances the response granularity of an already graduated authentication architecture.
Regarding Claims 14 and 19, the claim limitations are identical and/or equivalent in scope to claim 5, therefore, claims 14 and 19 are rejected under the same rationale as claim 5.
Claims 6, 15 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Goldberg in view of US 20180217829 (Mowatt et al.).
Regarding Claim 6, while, Goldberg teaches pre-caching of data associated with an entity application and dynamically generates a custom graphic user interface based on that pre-cached data, however, Goldberg does not explicitly teach, but, Mowatt teaches identify deployment of a new update associated with the entity application; trigger pre-caching of the data associated with the entity application to capture new features provided by the new update; and generate a new custom graphic user interface based on the pre-caching of the data associated with the new update ([Abstract], detect when a user performs actions within a software application, capture data about user actions and application features, and determine …if an updated or new feature to perform the user actions exists in an upgraded version of the application software. …when a rule triggers, store [i.e., cache] user and application data and present to the user a visualization of the updated feature [i.e., new custom graphic user interface] available in the upgraded application software. [¶ 0002] Software applications go through multiple upgrades in functionality throughout their lifespans. [¶¶ 0008-0009] …detect and capture user actions within application software. …access a rules library that associates user actions with features in an upgraded version of the application software; associate user actions to updated features in the upgraded version of the application software using rules in the rules library; upon triggering a rule in the rules library associating a user action with a feature in the rules library, identify a visualization presenting an updated feature in the upgraded version of the application software; store the user action and associated feature in a storage device; and optionally present the visualization to the user via a display. … identifying a visualization presenting an updated feature in the upgraded version of the application software, storing the user action and associated feature, and presenting, on a display, the visualization to the user).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Mowatt’s update-detection and updated visualization mechanism into Goldberg’s system because Goldberg already disclosed historical behavior and real-time metadata signal, using the same architecture and yielding the same kind of output of dynamically generate UI, therefore this is a combination of known elements according to known method, yielding the predictable result of presenting new application functionality to user automatically and efficiently, ensuring the user facing interface stays current.
Regarding Claims 15 and 20, the claim limitations are identical and/or equivalent in scope to claim 6, therefore, claims 15 and 20 are rejected under the same rationale as claim 6.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Goldberg in view of US 20230119939 (Agmon et al.).
Regarding Claim 8, Agmon teaches The system of claim 1, wherein the at least one processing device is configured to adjust the real-time user data based on a type of the user device while analyzing the real-time user data ([0038] user interactions are received from a user device such as smart phone, tablet PC, laptop computer, and the like. …Various parameters of the user interactions may be extracted such as speed, distance, and shape of a swipe, …The extracted parameters may be used to determine features. [0041], a switch to a different device is detected for the user. ….the different device may be a different smart phone model, or a different type of device, i.e., a smart phone to a tablet. [0047], the first device may be a smart phone and the second device may be a tablet PC, or both device may be different models of smart phones, i.e., different manufacturers, different models, or different versions of the same model. [0057-0059], … feature can be shifted between devices. …adapt the feature… Each adaptation describes a transformation that can be performed on the first data set, X.sup.a, to arrive at a transformed data set that more closely aligns with the second data set, X.sup.b. …the adaptations can be done using normalization and de-normalization. …and then de-normalizing according to the second set of feature samples).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Agmon's data adjustment based on device type into Goldberg’s system because applying this known data-normalization technique to Goldberg’s existing real-time metadata analysis step is a combination of known elements according to a known method yielding a predictable result of more accurate cross-device authentication, with a reasonable expectation of success since both reference operate in the same field of real-time, device-derived user verification data.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Goldberg in view of JP 2026047847 (hereinafter, JP’847).
Regarding Claim 9, although, Goldberg already teaches dynamically generates and presents a custom GUI to the user [¶ 0065] and already relies on “historical behavior of the user” as an input to that prediction, however, Goldberg does not explicitly teach, but JP’847 teaches wherein the at least one processing device is configured to: monitor usage of the custom graphic user interface by the user in response to presenting the custom graphic user interface to the user; store the usage of the custom graphic user interface in a data repository ([Program execution flow 1-5 in pages 3-4] collects data on user actions and behaviors when using the system. … Sends collected data to the server in real time. … Extracts behavioral data related to specific users …generates an optimized UI based on user behavior patterns. … Sends the optimized UI to the user's device. …Monitors the usage of the provided UI and collects user reactions and operation logs. …Stores collected feedback data in a database and uses it as new data for analysis).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate JP’847's UI usage monitoring and storage steps into Goldberg’s system of providing customized GUI to the user, such incorporation is a straightforward combination of known elements according to known methods, yielding the predictable result of continuously refreshing the very ‘historical behavior” data Goldberg’s predictive engine already depend on – the two reference share the identical field and identical objective, giving a skilled artisan clear motivation and a reasonable expectation of success in combining them.
Conclusion
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/MOHAMMAD YOUSUF A. MIAN/Examiner, Art Unit 2457
/ARIO ETIENNE/Supervisory Patent Examiner, Art Unit 2457
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