Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
The Amendments filed June 27th, 2026, have been entered. Claims 1, 2, 4, 5, 7-9, 12-14, and 16-20 have been amended and no other claims have been canceled or added. Claims 1-20 remain pending in the application. Applicants’ amendments to claims have overcome the 112(b) rejection previously set forth in the Non-Final Office Action mailed May 4th, 2026.
Response to Arguments
Applicant's arguments regarding the 35 U.S.C 103 rejections of claims 1-20 filed June 27th, 2026 have been fully considered but they are not persuasive. For claims 1-20, the applicant states that the claims are allowable for at least the reason that each such claim depends directly or indirectly on an allowable independent claim. In response to arguments, Examiner maintains their original rejection for claims 3, 6, 10, 11, and 15 due to the original references still teaching the original claim limitations. Zhang teaches that not only can the first identifier of the first device be found at a modem or router, that same router or modem can access the traffic patterns of the first device and see that the first identifier can be a MAC address. Pastore can still provide the ML update to local routers and/or modems.
Applicants remaining arguments with respect to claims 1, 2, 4, 5, 7-9, 12-14, and 16-20 have been considered but are either rejected under repetitions of the original rejection or are moot in view of the new ground of rejection.
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 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al,U.S. PG PUB (US 20180159751 A1), published June 7, 2018 in view of Pastore et al, U.S. PG PUB (20220083904), published March 17, 2022 and further in view of Mermoud et al, U.S. Patent (US 11416522 B1), published August 16, 2022 and Liu et al, NPL (More Classifiers, Less Forgetting: A Generic Multi-classifier Paradigm for Incremental Learning), published November 13, 2020.
With regard to independent claim 1,
Zhang teaches, “A method, comprising: responsive to determining that a local device classification” (Paragraph 0042, 0043; EN: This denotes that the device classification is stored locally, and the system is aware of the stored classification). “associated with a first identifier of a first device operating in a network” (pg.3-4, paragraph 0038; EN: This denotes that the data used by the system to classify the device can be a MAC address, IP address, etc. It also indicates that device is a part of a network). “Is available from a local device classification database” (Paragraph 0043 and 0062, Fig. 4; EN: Paragraph 0043 denotes that the device classification is stored locally, and the system is aware of the stored classification. Paragraph 0062 indicates that the device information database is used as part of the classification of devices). “identifying, by a processing system including a processor” (Paragraph 0079; EN: This denotes that the system uses a processor). “the local device classification from the local device classification database as a current device classification for the first device;” (Paragraph 0043; EN: This denotes that the device classification is stored locally, and the system is aware of the stored classification. It also denotes that the current device classification is the classification that is stored until it is later updated by the system as needed).
“Responsive to determining that the local device classification associated with the first identifier of the first device is not available from the local device classification database:” (Paragraph 0033 and 0062, Fig. 4; EN: Paragraph 0033 denotes that there is scanning for new devices connected to the network and that these devices would be unknown to the database and wouldn’t be shown before the scan. After scanning the new devices, paragraph 0062 and Fig. 4 indicate that the device information database may be used by a classifier device to classify one or more of the scanned devices coupled to the network). “generating, by the processing system, a local classifier device classification associated with a first device via a local … device classifier” (Paragraph 0021; EN: This denotes the classifier creating a classification for devices). “According to first-device information associated with the first device;” (Paragraph 0038; EN: This denotes that the information used to classify the device, such as MAC address or IP address, can be accessed by another device).
“identifying, by the processing system, the generated local classifier device classification as the current device classification for the first device;” (Paragraph 0043; EN: This denotes that the device classification is stored locally, and the system is aware of the stored classification). “storing, by the processing system, the generated local classifier device classification at the local device classification database;” (Paragraph 0043; EN: This denotes that the device classification is stored locally, and the system is aware of the stored classification). “the generated local classifier device classification” (Paragraph 0021; EN: This denotes the classifier creating a classification for devices).
However, Zhang fails to explicitly disclose, “machine learning device classifier”, “storing, by the processing system, … at a device classification for ML training database via the network;”, “receiving, by the processing system, an ML model update from a trainer for the local ML device classifier via the network,”, “wherein: a remote classifier device classification is determined via a remote ML device classifier according to historical network information associated with the first device;”, “and the trainer computes an error between the generated local classifier device classification and the remote classifier device classification, and generates the ML model update based on the error;”, “updating, by the processing system, the local ML device classifier according to the ML model update;”, and “and monitoring, by the processing system, a quality of service (QoS) associated with the first device according to the current device classification for the first device” .
Mermoud teaches, “machine learning device classifier” (Col. 5, lines 54-63; EN: This denotes classifying a device through the use of ML classifiers). “storing, by the processing system, … at a device classification for ML training database via the network;” (Col. 5, lines 27-41; EN: This denotes the storage of various data structures and software programs that can be accessed by a processor). “and monitoring, by the processing system, a quality of service (QoS) associated with the first device according to the current device classification for the first device” (Col. 8, lines 44-63; EN: This denotes enforcing network policies for classified devices. The policy can include QoS).
Zhang and Mermoud are considered to be analogous art to the claimed invention due to the fact that they both disclose device classification. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the identification of stored classifications of Zhang with the network enforcing policies of Mermoud. One would be motivated to do so to improve the security policies involved with device classification and what the devices are allowed to do.
However, Zhang and Mermoud fail to explicitly disclose “receiving, by the processing system, an ML model update from a trainer for the local ML device classifier via the network,”, “wherein: a remote classifier device classification is determined via a remote ML device classifier according to historical network information associated with the first device;”, “and the trainer computes an error between the generated local classifier device classification and the remote classifier device classification, and generates the ML model update based on the error;”, and “updating, by the processing system, the local ML device classifier according to the ML model update;”.
Pastore discloses, “receiving, by the processing system, an ML model update from a trainer for ML device classifier via the network” (Paragraph 0031; EN: This denotes sending ML model updates from the global models to the local models). “wherein: a remote classifier device classification is determined via a remote ML device classifier according to historical network information associated with the first device;” (Paragraph 0006; EN: This denotes that the global model/ aggregator uses cluster information to define classes). “and the trainer … the generated local classifier device classification and the remote classifier device classification, …;” (Paragraph 0031; EN: This denotes the use of global models and local models). “updating, by the processing system, the local ML device classifier according to the ML model update;” (Paragraph 0086; EN: This denotes updating local device classifiers based on updated ml model parameters).
Zhang, Pastore, and Mermoud are considered to be analogous art to the claimed invention due to the fact that they all disclose device classification. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the device classification of Zhang with the machine learning capabilities of Pastore and Mermoud. One would be motivated to do so to improve the accuracy of device classification and improving the act of device classifications itself.
However, Zhang, Pastore, and Mermoud fail to disclose “… computes an error between the generated… classifier device classification and the…. classifier device classification, and generates the ML model update based on the error;”.
Liu teaches, “… computes an error between the generated…classifier device classification and the….classifier device classification, and generates the ML model update based on the error;” (Pg.4-6, Fig.2, Section: 3-3.1; EN: This denotes computing a cross entropy loss between the main classifier and the side classifiers, which in turns leads continuously updating the model with the new data).
Zhang, Pastore, Mermoud, and Liu are considered to be analogous art to the claimed invention due to the fact that they all disclose the usage of a type of classifier. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the device classification of Zhang, the machine learning capabilities of Pastore and Mermoud with the multi-classifier (MUC) of Liu. One would be motivated to do so to improve the accuracy of device classification and improving the act of device classifications itself.
With regard to dependent claim 2,
Zhang teaches the limitation “The method of claim 1, further comprising: querying, by the processing system, the local device classification database based on the first identifier of the first device;” (Paragraph 0020; EN: This denotes using the classifier device to classify devices based on information gathered from the device itself). “and determining, by the processing system, whether a local device classification associated with the first identifier of the first device is available from the local device classification database” (Paragraph 0043; EN: This denotes that the device classification is stored locally, and the system is aware of the stored classification).
With regard to dependent claim 3,
Zhang fails to explicitly teach “The method of claim 1, further comprising receiving, by the processing system, the first identifier of the first device wherein the local ML device classifier is located at a modem/router device.”
Mermoud teaches the limitation “The method of claim 1, further comprising receiving, by the processing system, the first identifier of the first device wherein the local ML device classifier is located at a modem/router device.” (Col. 8, lines 9-18; EN: This denotes hosting the device classification on networking devices such as routers and taking captured data to identify classified devices).
With regard to dependent claim 4,
Zhang teaches the limitation “The method of claim 1, further comprising receiving, by the processing system, the first-device information associated with the first device” (Paragraph 0019; EN: This denotes that the classifier device can access information used for device classification).
With regard to dependent claim 5,
Zhang teaches, “the local device classification, the generated local classifier device classification, or the remote classifier device classification identifies the first device as a mobile device, a gaming device, or an Internet of Things (IoT) device” (Paragraph 0050-0051, 0073; EN: This denotes a system that contains a classifier device or a virtual machine configured to classify one or more devices coupled to a network. This system also has a third-party interface, which is configured to communicate with one or more third party, remote, or external system to access information about a soon to be classified device that can communicate with a mobile device management (MDM) system. MDM systems are configured for administration of mobile devices, such as smart phones, and may provide detailed device information used for classification).
With regard to dependent claim 6,
Zhang teaches the limitation “The method of claim 1, wherein the first identifier of the first device is a media access control (MAC) address” (Paragraph 0023; EN: This denotes that the basic information associated with the classified device can include media access control (MAC) address).
With regard to dependent claim 7,
Zhang teaches the limitation “The method of claim 1, wherein the first-device information data associated with the first device includes an organizational unique identifier (OUI) associated with the first device” (Paragraph 0023; EN: This denotes that the basic information associated with the classified device can include an organizational unique identifier (OUI)).
With regard to dependent claim 8,
Zhang teaches the limitation “The method of claim 1, wherein first-device information associated with the first device includes a hostname associated with the first device” (Paragraph 0023; EN: This denotes that the basic information associated with the classified device can include a hostname).
With regard to dependent claim 9,
Zhang teaches the limitation “The method of claim 1, wherein first-device information associated with the first device includes hypertext transfer protocol (HTTP) user agent information associated with the first device” (Paragraph 0023; EN: This denotes that the basic information associated with the classified device can include hypertext transfer protocol (HTTP) user agent information).
With regard to dependent claim 10,
Zhang teaches the limitation “The method of claim 1, wherein the historical network information includes traffic patterns associated with the first device, network logs associated with the first device, or any combination thereof” (Paragraph 0038; EN: This denotes the access of traffic data and network logs associated with the classified devices).
With regard to dependent claim 11,
Zhang-Pastore discloses “the method of claim 1, wherein the ML model update is provided to a local router/modem device of a plurality of router/modem devices” (Paragraph 0094; EN: This denotes downloading software programs and federated learning programs through the network and combining them).
With regard to independent claim 12,
This claim is similar in scope to claim 1 and is rejected under a similar rationale.
With regard to independent claim 13,
This claim is similar in scope to claim 5 and is rejected under a similar rationale.
With regard to dependent claim 14,
This claim is similar in scope to claim 2 and is rejected under a similar rationale.
With regard to dependent claim 15,
This claim is similar in scope to claim 3 and is rejected under a similar rationale.
With regard to dependent claim 16,
Zhang teaches the limitation “The device of claim 12, wherein the first-device information associated with the first device includes an organizational unique identifier (OUI) associated with the first device, a hostname associated with the first device, hypertext transfer protocol (HTTP) user agent information associated with the first device, or any combination thereof” (Paragraph 0023; EN: This denotes the basic information associated with the classified device).
With regard to independent claim 17,
This claim is similar in scope to claim 1 and is rejected under a similar rationale.
With regard to dependent claim 18,
Zhang teaches the limitation “The non-transitory machine-readable medium of claim 17 wherein the operations further comprise: identifying the generated local classifier device classification as a current device classification for the first device;” (Paragraph 0043; EN: This denotes that the device classification is stored locally, and the system is aware of the stored classification).
With regard to dependent claim 19,
This claim is similar in scope to claim 2 and is rejected under a similar rationale.
With regard to dependent claim 20,
This claim is similar in scope to claim 16 and is rejected under a similar rationale.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SETH CAPRIANO-UMARI SHELTON whose telephone number is (571)270-0213. The examiner can normally be reached 8am-5pm.
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/SETH CAPRIANO-UMARI SHELTON/ Examiner, Art Unit 2141
/MATTHEW ELL/ Supervisory Patent Examiner, Art Unit 2141
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