DETAILED ACTION
Notice of 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 .
The present office action is responsive to communications received on 6/24/2025. Claims 1-10 are pending.
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 12 of U.S. Patent No. 12341808. Although the claims at issue are not identical, they are not patentably distinct from each other because claims of the 12341808 contain every element of claims of the instant application. Application claim 1 is anticipated by the patent claim 12.
A later patent claim is not patentably distinct from an earlier patent claim if the later claim is obvious over, or anticipated by, the earlier claim. In re Longi, 759 F.2d at 896, 225 USPQ at 651 (affirming a holding of obviousness-type double patenting because the claims at issue were obvious over claims in four prior art patents); In re Berg, 140 F.3d at 1437, 46 USPQ2d at 1233 (Fed. Cir. 1998) (affirming a holding of obviousness-type double patenting where a patent application claim to a genus is anticipated by a 35 patent claim to a species within that genus). “ELI LILLY AND COMPANY v BARR LABORATORIES, INC., United States Court of Appeals for the Federal Circuit, ON PETITION FOR REHEARING EN BANC (DECIDED: May 30, 2001).
Instant Application No. 19248031
Patent No. 12341808
1. An apparatus, comprising:
a hardware processor;
computer memory comprising computer program code executed by the hardware processor to differentiate traffic received at a server as bot traffic or human traffic, the program code configured to:
receive telemetry comprising values from a diverse set of data fields, wherein a list of data field values comprise a network pattern;
apply a clustering algorithm that identifies bot traffic by determining that the traffic received at the server has similar and repeating network patterns that cluster together, wherein the similar and repeating network patterns are identified from field values other than those associated with a given combination pattern of field values associated with a known device; and
responsive to determining that the traffic received at the server has similar and repeating network patterns that cluster together, return to the server control signaling indicating identification of bot traffic.
12. An apparatus, comprising:
a hardware processor;
computer memory comprising computer program code executed by the hardware processor to differentiate traffic received at a server as bot traffic or human traffic, the program code configured to:
receive telemetry comprising values from a diverse set of data fields, wherein a list of data field values comprise a network pattern (NP);
use data field values associated with a given combination pattern to classify device characteristics associated with the given combination pattern;
use data field values other than the data field values associated with the given combination pattern to build, in real-time, lists of data field values that represent network patterns; and
detect a bot in real-time by identifying, from the network patterns that are built in real-time, similar and repetitive lists of data field values that are not representative of random variation associated with human traffic.
Allowable Subject Matter
Claims 1-10 are allowable over prior art.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding claims 1, the prior art:
Vines (US10326789B1) teaches Web Bot detection and human differentiation. Web Bot detection methods and systems are provided that receive a request, in connection with a network session. The methods and systems determine whether the request is associated with potential Bot activity, and based thereon assign a Bot confidence designation. The Bot confidence designation indicates a likelihood that the request represents an agent-based request. The methods and systems analyze a session trait of the network session relative to predetermined session traits indicative of human-based requests, and assign a human confidence designation based on the analysis. The human confidence designation indicates a likelihood that the request represents a human-based request. The request is then classified to represent an agent-based request or human-based request based on the Bot and human confidence designations.
Su (US8424091B1) teaches Automatic local detection of computer security threats. A system for locally detecting computer security threats in a computer network includes a processing engine, a fingerprint engine, and a detection engine. Data samples are received in the computer network and grouped by the processing engine into clusters. Clusters that do not have high false alarm rates are passed to the fingerprint engine, which generates fingerprints for the clusters. The detection engine scans incoming data for computer security threats using the fingerprints.
However, the prior art – individually, or in a reasonable combination – fails to teach the invention described in the claims as a whole.
“identifies bot traffic by determining that the traffic received at the server has similar and repeating network patterns that cluster together, wherein the similar and repeating network patterns are identified from field values other than those associated with a given combination pattern of field values associated with a known device;”
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
"Humans and Bots in Internet Chat: Measurement, Analysis, and Automated Classification", by Steven Gianvecchio.
US20190019109A1, “Systems and methods for calibrating a machine learning model”, by Fred Sadaghiani.
US9875360B1, “Simulation and virtual reality based cyber behavioral systems”, by Robert L. Grossman.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HAN YANG whose telephone number is (408)918-7638. The examiner can normally be reached on Monday to Friday, 9:00-5:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Carl Colin can be reached on 571-272-3862. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/HAN YANG/Primary Examiner, Art Unit 2493
