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 1-19 have been examined and 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 § 2146 et seq. 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 filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual 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/apply/applying-online/eterminal-disclaimer.
Claims 1, 10, and 11 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 10, and 11 of U.S. Patent No. 12284195 (hereinafter ‘195). Although the claims at issue are not identical, they are not patentably distinct from each other because claim 1 of ‘195 recites every element of claim 1 of the instant application, except for the recitation of continuously detecting cloud identity misuse leveraging runtime context. However, it would have been obvious to a person of ordinary skill in the art to apply the recited invention steps to an techniques for detecting cloud identity misuse leveraging runtime context. As taught by Kilby 12659326 B1 (col 3, lines 54-56 and 63-67; col 75, lines 45-48 50-60; col 75, lines 45-48 50-60; col 11, lines 60-64; and col 11, lines 60-64), in view of Srivastava 20200336508 A1 (¶¶0004 0075-0076 0078 and 0092), each of these components are used interchangeably. Therefore, it would have been obvious to a person of ordinary skill in the art to modify claims 1, 10, and 11 to achieve the identical invention as recited in claims 1, 10, and 11 of the instant invention. In the same manner, it would have been obvious to modify claims 1, 10, and 11 of ‘195 to achieve the invention as recited in claims 1, 10, and 11, in which the only difference is the manner in which the invention is performed.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 03/03/2025, 09/16/2025 and 04/08/2026 was filed. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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 (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 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.
The factual inquiries 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(s) 1-6, 8-16 and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Kilby et al, hereinafter (“Kilby”), US Patent 12659326 B1, in view of Srivastava US PG Publication 20200336508 A1.
Regarding claims 1, 10 and 11, Kilby teaches a method for detecting cloud identity misuse in a cloud computing environment, comprising:
deploying a runtime sensor on a workload in a cloud computing environment [col 3, lines 54-56 and 63-67 compute assets like physical machines in software runtime environments that include workloads. col 6, lines 34-37 agent 38-1 through 38-N installed on each compute asset 16];
receiving event data from the runtime sensor [col 75, lines 45-48 and 50-60 data processing resources 20 receive snapshot analysis data to a collection of runtime workload data 504. col 76, lines 1-15 anomaly-based detection operation on workload 502];
detecting an identifier of a runtime process in the received event data [col 11, lines 60-64 process identifier scans within proc/pid directory];
generating an activity baseline for the runtime process based at least on the received event data, wherein the runtime sensor is configured to detect a plurality of runtime process identifiers on the workload [col 8, lines 50-55 implementation 100 of configuration 10 shows activities occurring within datacenters modeled using data platform 12 to model a baseline of data center activity to detect anomalies of collected];
While Kilby teaches detecting an event in a cloud log [col 63, lines 38-40 and 50-53 SIEM processes observe and analyze attacks/activities of interest that may be log or stored for subsequent examination.]; however, Kilby fails to explicitly teach but Srivastava teaches detecting an event in a cloud log, the event including an identifier of the workload [¶0004 collected data from one or more sources such as Cloud Logs; where collected datasets produce a consistent set of labels for each event. ¶0024 circuitry configured to collect data from several security data sources; profiles are assigned labels if the profile entity is found to be interacting in an event and the event has been assigned a label; generates the profile where the logs are stored. ¶¶0076 and 0078 profile merging to create entity profile: profile ID, timestamp.];
associating the runtime process detected by the runtime sensor on the workload with the event detected in the cloud log based at least on the identifier of the workload [¶0075 system may then detect changes in sequence of operations for a profile as another signal of suspicion sequence and correlation of different types of activity/labels. ¶¶0123-0125 behavior sequencing label and profile highlighting bad (suspicious) behaviors; current ID profiles build model to predict behavior]; and
determining that the event detected in the cloud log is an anomalous event based on the generated activity baseline of the runtime process [¶0092 system need to be able to detect label severity configuration. ¶0108 11. ProfileAnomaly(risk level) – function returns profiles showing anomalous behaviour].
Kilby teaches all the features of claims 1, 10, and 11 not detecting an event in a cloud log, the event including an identifier of the workload; associating the runtime process detected by the runtime sensor on the workload with the event detected in the cloud log based at least on the identifier of the workload and determining that the event detected in the cloud log is an anomalous event based on the generated activity baseline of the runtime process. Kilby teaches an agentless disk scanning in cloud environment. Srivastava teaches a system to stitch cybersecurity, measure network cyber health, generate business and network risks, enable realtime zero trust verifications, and recommend ordered, predictive risk mitigations. Because both Kilby and Srivastava are in the same field of endeavor, it would have been obvious to one skilled in the art before the effective filing date of the claimed invention was made to use the sequence detection to identify one or more risks associated with each profile as taught by Srivastava to improve the risk migitation against anomalous behaviors [Srivastava, Abstract].
Regarding claims 2 and 12, the combination of Kilby and Srivastava teach claim 1 as described above.
Kilby teaches further comprising: detecting a code object utilized to deploy the workload in the cloud computing environment [col 3, lines 54-56 and 63-65 deployed container images of compute assets 16 of cloud environment 14; col 80, lines 12-19 workload 502 within Google Cloud Platform (GCP) environment 1102 include container image, workload, etc.]; inspecting the code object for a cybersecurity object, wherein the cybersecurity object indicates an identity utilized by the workload [col 80, lines43-45 and 61-67 unprivileged agentless workload 1106 generates replication dataset of workload 502 which is further analyzed for security, compliance, etc.]; associating the runtime process with the event based on an identifier of the workload and the indicated identity [col 8, lines 48-60 …an identity of a user accessing workload 502, a time associated with workload 502, one or more events associated with workload 502… ].
Regarding claims 3 and 13, the combination of Kilby and Srivastava teach claim 1 as described above.
Kilby teaches further comprising: generating the activity baseline based on a plurality of events detected in the received event data [col 15, lines 50-61 received traffic connections used to establish baseline for detecting deviations].
Regarding claims 4 and 14, the combination of teach claim 3 as described above.
Kilby teaches further comprising: generating the activity baseline based only on a group of events of the plurality of events corresponding to a first event type [See col 15, lines 50-61. Examiner interprets that the generated baselines can correlate information as needed; as such analogous to generating the activity baseline based only on a group of events of the plurality of events corresponding to a first event type].
Regarding claims 5 and 15, the combination of Kilby and Srivastava teach claim 1 as described above.
Kilby teaches further comprising: generating the activity baseline based on runtime data from a plurality of workloads, each workload deployed based on a common code object [See col 3, lines 54-56 and 63-65].
Regarding claims 6 and 16, the combination of teach claim 5 as described above.
Kilby teaches wherein the common code object is a software image [See col 3, lines 54-56 and 63-65 ].
Regarding claims 8 and 18, the combination of Kilby and Srivastava teach claim 1 as described above.
While Kilby teaches detecting a plurality of processes by the runtime sensor on the workload; [col 63, lines 38-40 and 50-53 SIEM processes observe and analyze attacks/activities of interest that may be log or stored for subsequent examination. See also col 75, lines 45-48 and 50-60]; however, Kilby fails to explicitly teach but Srivastava teaches further comprising: generating a unique activity baseline for each detected process. [See ¶0075 system may then detect changes in sequence of operations for a profile as another signal of suspicion sequence and correlation of different types of activity/labels. ¶¶0123-0125 behavior sequencing label and profile highlighting bad (suspicious) behaviors; current ID profiles build model to predict behavior. Examiner interprets each activity baseline modeled will be inherently unique with behavior distinctive for the suspicious sequence of activities analyzed; as such appears to teach detecting a plurality of processes by the runtime sensor on the workload; and generating a unique activity baseline for each detected process]
Kilby teaches all the features of claims 1, 10, and 11 not urther comprising: generating a unique activity baseline for each detected process. Kilby teaches an agentless disk scanning in cloud environment. Srivastava teaches a system to stitch cybersecurity, measure network cyber health, generate business and network risks, enable realtime zero trust verifications, and recommend ordered, predictive risk mitigations. Because both Kilby and Srivastava are in the same field of endeavor, it would have been obvious to one skilled in the art before the effective filing date of the claimed invention was made to use the sequence detection to identify one or more risks associated with each profile as taught by Srivastava to improve the risk migitation against anomalous behaviors [Srivastava, Abstract].
Regarding claims 9 and 19, the combination of Kilby and Srivastava teach claim 1 as described above.
Kilby teaches further comprising: generating the activity baseline further based on detected events in the cloud log. [See col 15, lines 50-61 received traffic connections used to establish baseline for detecting deviations].
Claim(s) 7 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Kilby et al, hereinafter (“Kilby”), US Patent 12659326 B1, in view of Srivastava US PG Publication 20200336508 A1, in view of Kaliya Perumal et al, hereinafter (“Kaliya”) US PG Publication 20220239683 A1.
Regarding claims 7 and 17, the combination of Kilby and Srivastava teach claim 1 as described above.
However, the combination of Kilby and Srivastava fail to explicitly teach but Kaliya teaches further comprising: removing a data point from the activity baseline based on an eviction policy. [See ¶¶0097-0098 stored entries for tuples have been removed; eviction policies]
Kilby teaches all the features of claims 1, 10, and 11 not further comprising: removing a data point from the activity baseline based on an eviction policy. Kaliya teaches a security threat detection based on network flow analysis. Kilby teaches an agentless disk scanning in cloud environment. Srivastava teaches a system to stitch cybersecurity, measure network cyber health, generate business and network risks, enable realtime zero trust verifications, and recommend ordered, predictive risk mitigations. Because Kilby, Srivastava, and Kaliya are all from the same field of endeavor, it would have been obvious to one skilled in the art before the effective filing date of the claimed invention was made to use the sequence detection to identify one or more risks associated with each profile as taught by Srivastava to improve the risk migitation against anomalous behaviors and further identify tuple (data) to be removed using an eviction policy [Kaliya].
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Harel (12549589 B1) teaches detection engine having risk-based severity alerts.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SAKINAH WHITE-TAYLOR whose telephone number is (571)270-0682. The examiner can normally be reached Monday-Friday, 10:45a-6:45p.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, CATHERINE THIAW can be reached at 571-270-1138. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
SAKINAH WHITE-TAYLOR
Primary Examiner
Art Unit 2407
/Sakinah White-Taylor/Primary Examiner, Art Unit 2407
Prosecution Insights