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 .
Information Disclosure Statement
The information disclosure statement filed on Feb. 13, 2026 fails to comply with the provisions of 37 CFR 1.97, 1.98 and MPEP § 609 because – it refers to International Search Report and Written Opinion mailed on May 23, 2024 in PCT/IB2024/055000.
It appears that the claims in PCT are different than current application.
It has been placed in the application file, but the information referred to therein has not been considered as to the merits. Applicant is advised that the date of any re-submission of any item of information contained in this information disclosure statement or the submission of any missing element(s) will be the date of submission for purposes of determining compliance with the requirements based on the time of filing the statement, including all certification requirements for statements under 37 CFR 1.97(e). See MPEP § 609.05(a).
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP §§ 706.02(l)(1) - 706.02(l)(3) for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claim 1 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1 of U.S. Patent No. 12,520,142 B2, claim 1 of U.S. Patent No. 12,047,773 B2, claim 1 of U.S. Patent No. 11,272,362 B2 Mar. 8, 2022, claim 1 of U.S. Patent No. 10,588,017 B2 Mar. 10, 2020, claim 1 of U.S. Patent No. 10,187,799 B2 Jan. 22, 2019 and claim 19 of U.S. Patent No. 9,788,203 B2 Oct. 10, 2017. Although the claims at issue are not identical, they are not patentably distinct from each other because -
Claim 1 of current application is as below:
A computer-implemented method comprising:
obtaining sensor data, the sensor data being recorded by a mobile device while a user of the mobile device performs a selected task;
determining a feature representation of the selected task performed by the user of the mobile device, the feature representation being based on the obtained sensor data;
analyzing the feature representation against a user model that is generated by one or more instances in which an authenticated user performed the selected task and developed the muscle memory;
determining, based on analyzing the feature representation, a likelihood that the user of the mobile device is the authenticated user; and
authenticating the user of the mobile device based on the likelihood.
Here, it is obvious modification from allowed US patent’s claim 1 and come up with independent claim 1 of current application by deleting and rewording the claims language of allowed claim 1.
Claim 1 of U.S. Patent No. 12,520,142 is as below:
A computer-implemented method comprising:
obtaining sensor data, the sensor data being recorded by a mobile device while a user of the mobile device performs a selected task, the selected task being of a type in which muscle memory is developed by users performing the type of task;
determining a feature representation of the user performing the task at each of multiple instances, the feature representation being based on the obtained sensor data;
determining a model based at least in part on the feature representation of the sensor data obtained when the user performs the task at each of the multiple instances;
wherein determining the model includes learning one or more model parameters that are associated with one or more features of the feature representation, the one or more parameters configuring the model to be specific to the user;
in response to the task being performed on the mobile device, analyzing, based on the model, a data set obtained from one or more sensors of the mobile device in connection with the task being performed;
based on the analyzing, making a determination as to whether the task is performed by the user;
generating an authentication output based on the determination; and
adjusting the one or more parameters based on the authentication output.
Claim 1 of U.S. Patent No. 12,047,773 is as below:
A computer-implemented method comprising:
obtaining sensor data, the sensor data being recorded by a mobile device while a user of the mobile device performs a selected task, the sensor data representing a motion of the mobile device in three-dimensional space while the selected task is performed;
determining a feature representation of the selected task performed by the user of the mobile device, the feature representation being based on the obtained sensor data that represents the motion of the mobile device in three-dimensional space while the selected task is performed;
analyzing the feature representation against a user model that is generated by one or more instances in which an authenticated user performed the selected task;
determining, based on analyzing the feature representation, a likelihood that the user of the mobile device is the authenticated user; and authenticating the user of the mobile device based on the likelihood.
Here, it is obvious modification from allowed US patent’s claim 1 and come up with independent claim 1 of current application by deleting and rewording the claims language of allowed claim 1.
Claim 1 of U.S. Patent No. 11,272,362 is as below:
A computer-implemented method comprising:
providing one or more prompts for display on a mobile device, the one or more prompts being indicative of a task that a user of the mobile device is to perform, the task being associated with an activity that is dependent on muscle memory previously developed through interactions with the mobile device;
obtaining sensor data from a plurality of sensors of different types that are incorporated within the mobile device while the user of the mobile device performs the task;
determining a feature representation of the activity performed by the user of the mobile device, the feature representation being based on sensor data obtained from multiple sensors of different types of the plurality of sensors;
analyzing the feature representation against a user model that is generated by one or more instances in which an authenticated user performed the activity and developed the muscle memory;
determining, based on analyzing the feature representation, a likelihood that the user of the mobile device is the authenticated user; and
authenticating the user of the mobile device based on the likelihood.
Here, it is obvious modification from allowed US patent’s claim 1 and come up with independent claim 1 of current application by deleting and rewording the claims language of allowed claim 1.
Claim 1 of U.S. Patent No. 10,588,017 is as below:
A method of task-based behavioral biometric implicit authentication of a user on a mobile device, the method comprising:
displaying first prompts on a display of the mobile device, the first prompts instructing the user in a first performance of a task, the task comprising a performance of an activity dependent on muscle memory;
recording first sensor data obtained from a plurality of sensors incorporated within the mobile device, the sensor data obtained during the first performance; processing the first sensor data to determine first parameters of a predetermined model of the activity and storing the first parameters in a user model associated with the activity and the user, the user model being stored in a database within the mobile device;
displaying second prompts on the display, the second prompts instructing the user in a second performance of the task;
recording second sensor data obtained during the second performance; comparing the second sensor data to the user model to generate an authentication decision; and
processing the second sensor data to determine second parameters of the predetermined model of the activity and storing the second parameters in the user model associated with the activity and the user, the second parameters updating the user model;
wherein:
the muscle memory is previously built up by the user repeatedly performing interactions with the device.
Here, it is obvious modification from allowed US patent’s claim 1 and come up with independent claim 1 of current application by deleting and rewording the claims language of allowed claim 1.
Claim 1 of U.S. Patent No. 10,187,799 is as below:
A method for authenticating a user of a mobile device performed by the
mobile device, the method comprising:
prompting the user to perform a task comprising the user performing a behavioral task with the mobile device, the behavioral task leveraging the muscle memory of the user;
during the input of the behavioral task, utilizing a plurality of internal sensors to determine a first data set of a behavioral characteristic of the user;
prompting the user to perform a capture a biometric characteristic of the user utilizing a second internal sensor incorporated in the mobile device;
utilizing the second internal sensor to determine a second data set of the biometric characteristic of the user;
making a first comparison between the first data set and a first pre-recorded data set, and a second comparison between the second data set to a second pre-recorded data set, the first pre-recorded data set based on a plurality of previous performances of the behavioral task, the second pre-recorded data set based on a plurality of previous captures of the biometric characteristic; and
making a user authentication decision comprising the first comparison and the second comparison, the user authentication decision authenticating an action of the user;
wherein the action comprises a use of an application, the method further comprising prompting the user to perform the task comprising the user performing the behavioral task with the mobile device;
during the input of the behavioral task, utilizing the plurality of internal sensors to determine a third data set of the behavioral characteristic of the user;
making a third comparison between the third data set and the first pre-recorded data set; and
making a second authentication decision comprising the third comparison and the second comparison, the user authentication decision re-authenticating the action of the user.
Here, it is obvious modification from allowed US patent’s claim 1 and come up with independent claim 1 of current application by deleting and rewording the claims language of allowed claim 1.
Claim 19 of U.S. Patent No. 9,788,203 is as below:
A method for implicit authentication for a mobile device associated
with a user,
wherein the implicit authentication is behavioural, biometric and task-based,
the task-based behavioral biometric implicit authentication
comprises at least one authentication task, and
the authentication task chosen so as to leverage the user's muscle memory; wherein said mobile device comprises
a touchscreen,
a transaction authentication information unit,
one or more sensors coupled to the transaction authentication information unit, the one or more sensors comprising:
(1) one or more touchscreen sensors coupled to said touchscreen,
(2) an accelerometer, and
(3) a gyroscope, and
an anomaly detector coupled to the transaction authentication information unit; said method comprising:
obtaining, by the one or more sensors, one or more sets of data associated with one or more performances of the at least one authentication task by the user, the one or more sets of data comprising data related to the tracking of a user's input on the touchscreen and the movement of the mobile device during the at least one authentication task;
transmitting, by the one or more sensors, the obtained one or more sets of data
to the transaction authentication information unit;
generating, using the anomaly detector, an authentication model using the transmitted one or more data sets,
said generating comprising constructing a set of features for a user profile associated with the one or more performances of the at least one authentication task, and one or more parameters associated with said set of features;
training the anomaly detector using the one or more data sets transmitted to the transaction authentication information unit, said training comprising
learning so as to adjust the one or more parameters associated with
the set of features,
said learning performed using one or more learning algorithms,
storing the user profile associated with the adjusted one or more parameters in the database; and
authenticating, by the anomaly detector, the user using the one or more data sets transmitted to the transaction authentication information unit, the authenticating comprising analyzing, by the anomaly detector, at least one of the one or more data sets using one or more anomaly detection algorithms together with the stored user profile, and
deciding, by the anomaly detector, whether the authentication is successful or unsuccessful based on said analyzing.
Here, it is obvious modification from allowed US patent’s claim 19 and come up with independent claim 1 by deleting and rewording the claims language of allowed claim 19.
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 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim 1 is rejected under 35 U.S.C. 103 as being unpatentable over
Lau US PGPub: US 2013/0102283 A1 Apr. 25, 2013 and in view of
Laubach US PGPub: US 2012/0235938 A1 Sep. 20, 2012.
Regarding claim 1, Lau discloses,
a computer-implemented method, a computer system comprising: one or more processors; memory storing instructions; wherein the one or more processors execute the instructions to perform operations and non-transitory computer readable medium that stores instructions, that when executed by one or more processors of a computer system, cause the computer system to perform operations that include: (methods, system and apparatuses for authenticating a user of a mobile device – ABSTRACT, Figs. 1, 3, 4, 6, 7, paragraphs 0006, 0007, 0018. methods, systems and apparatuses for user behavior analysis and authentication of a user of a mobile device – paragraphs 0002, 0012. biometric fingerprint – paragraph 0018, biometric sensors – paragraph 0047 and biometric pattern – paragraph 0048. The level of confidence used for allowing or not allowing access to various access systems, such as computer systems, websites that require logging in, building/door entry, automotive vehicle entry and ignition, and payment systems of various kinds, including credit cards. The user is attempting to use the credit card at a merchant – paragraph 0074. methods, systems and apparatuses for user behavior analysis and authentication of a user of a mobile device – paragraphs 0002, 0012 and level of confidence for allowing or not allowing access – paragraph 0074) comprising:
obtaining sensor data (the sensed motion is tracked over time. The sensed motion include for signal, signals form the user’s mobile device’s accelerometer, gyroscope, compass, altimeter, changes in WiFi signal strength, changes in the GPS readings, barometric pressure sensor…..fingerprint sensors or bio-sensors – paragraph 0078. A history of motion of the motion device can be tracked/established, that includes, for example, a mode of transportation pattern, and a motion activity pattern. Additionally, location information can be tracked that includes, for example, place visits profile - including location, time of day, day of week, day of year, weekend vs. weekday, holidays, seasons and time duration. The tracked motion and location information provide a set of very unique mobile behavioral fingerprints and footprints. Here, a mode of transportation pattern, and a motion activity pattern etc., - paragraph 0041),
the sensor data being recorded by a mobile device while a user of the mobile device performs a selected task (semi-automatic processing in which a user’s input or feedback can optionally be included with the processing to improve the process - paragraphs 0024, 0029, 0061. The user-input information received from a keyboard or touch screen 282 – Fig. 2/282, paragraph 0061. The database scheme used in the location system, users table is to store information of each user registered with the system – Fig. 5, paragraph 0097. The methods, systems and apparatuses for user behavior analysis and authentication of a user of a mobile device – paragraphs 0002, 0012. Various sensors are connected with the controller 210 – Fig. 2. Also, the data processing can be performed in the background, and operate on persistently collected sensor data – optionally uploading the data to a server – paragraph 0024);
determining a feature representation of the selected task performed by the user of the mobile device, the feature representation being based on the obtained sensor data (each of motion patterns provides a set of very unique mobile behavioral fingerprints and footprints. If the device deviates from that profiles, the described embodiments, for example, generates a red flag. The red flag is generated by the authentication, and influences identification of the user, security of the mobile device, security access provided to the user of the mobile device, and/or access to commerce – paragraph 0028. The database scheme used in the location system, users table is to store information of each user registered with the system – Fig. 5, paragraph 0097);
analyzing the feature representation against a user model that is generated by one or more instances in which an authenticated user performed the selected task (each of motion patterns provides a set of very unique mobile behavioral fingerprints and footprints. If the device deviates from that profiles, the described embodiments, for example, generates a red flag. The red flag is generated by the authentication, and influences identification of the user, security of the mobile device, security access provided to the user of the mobile device, and/or access to commerce – paragraph 0028);
determining, based on analyzing the feature representation (each of motion patterns provides a set of very unique mobile behavioral fingerprints and footprints. If the device deviates from that profiles, the described embodiments, for example, generates a red flag. The red flag is generated by the authentication, and influences identification of the user, security of the mobile device, security access provided to the user of the mobile device, and/or access to commerce – paragraph 0028), a likelihood that the user of the mobile device is the authenticated user; and authenticating the user of the mobile device based on the likelihood (the user profile 410 and the later generated present user profile are used by an authentication engine 46- to authenticate the present user of the user of the mobile device – Figs. 4/460, 6/670, paragraphs 0087, 0088, 0098. the motion behavior includes at least one motion detector within the mobile device sensing motion of the mobile device over time, The sensed motion is tracked over time. The sensed motion include for signal, signals form the user’s mobile device’s accelerometer, gyroscope, compass, altimeter, changes in WiFi signal strength, changes in the GPS readings, barometric pressure sensor…..fingerprint sensors or bio-sensors – paragraph 0078. Methods, systems and apparatuses for user behavior analysis and authentication of a user of a mobile device – paragraphs 0002, 0012 and level of confidence for allowing or not allowing access – paragraph 0074. The level of authentication uses mobile behavioral fingerprints and footprints can be used to lower the rate of fraudulent payments, transactions, access control, authentication, and improve fraud detection, and security systems – paragraph 0076. An authentication provides a confidence level in whether the present user is the user of the mobile device – paragraphs 0018, 0019. Some types of services along the this part of the trail can be recommended to the user, with the expectation that it is more likely for the user to use the service, because it is easier for the user to stop by the service – paragraph 0050),
but, does not disclose, analyzing the feature representation against a user model that is generated by developed the muscle memory.
Laubach teaches, through repeated use, the one or more touches, taps, holds, slides and directional flicks that are used to access and perform different operations become ingrained in the user’s muscle memory. Automatically utilizing this innate muscle memory, the user can recreate these actions without conscious effort in order to perform desired operations on a touch operated device (paragraph 0025). This allows the user to leverage her/his muscle memory to perform various operations (paragraph 0090).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify methods, system and apparatuses for authenticating a user of a mobile device of Lau (Lau, ABSTRACT, Figs. 1, 3, 4, 6, 7, paragraphs 0006, 0007, 0018), wherein the methods, system and apparatuses of Lau, would have incorporated the touch-based user interface enhancements for computer systems and electronic devices that allows the user to leverage her/his muscle memory to perform various operations (Laubach, paragraphs 0024, 0090) for enhancements to both pointer-based and screen-based UIs that allow users to better interact with computers and devices using existing touch hardware, and leverage the use's innate muscle memory so that with repeated use output actions can be performed with little mental, visual or physical effort (Laubach, paragraph 0013).
The prior art made of record and not relied upon is considered pertinent to applicant'’ disclosure.
1. Dutt teaches, system and method of behavioural biometric authentication using program modelling.
US PGPub: US 2016/0259924 A1 Sep. 8, 2016.
2. Dutt teaches, context-dependent authentication system, method and device.
US PGPub: US 2014/0337243 A1 Nov. 13, 2014.
3. Sundaram US PGPub: US 2007/0219801 A1 Sep. 20, 2007.
A system, method and computer program product are described for updating a biometric model of a user enrolled in a biometric system based on changes in a biometric feature of the user (ABSTRACT, Figs. 2 – 6, paragraphs 0008 – 0012).
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/NIMESH PATEL/Primary Examiner, Art Unit 2642
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