Office Action Predictor
Last updated: April 16, 2026
Application No. 18/749,769

APPARATUS AND METHOD FOR ADVERSARIAL CAN PACKETIZATION FOR PHYSICAL ATTACK OF VEHICLE

Non-Final OA §101§103
Filed
Jun 21, 2024
Examiner
CHACKO, JOE
Art Unit
2457
Tech Center
2400 — Computer Networks
Assignee
Foundation Of Soongsil University-Industry Cooperation
OA Round
1 (Non-Final)
75%
Grant Probability
Favorable
1-2
OA Rounds
3y 3m
To Grant
92%
With Interview

Examiner Intelligence

Grants 75% — above average
75%
Career Allow Rate
429 granted / 575 resolved
+16.6% vs TC avg
Strong +17% interview lift
Without
With
+17.1%
Interview Lift
resolved cases with interview
Typical timeline
3y 3m
Avg Prosecution
20 currently pending
Career history
595
Total Applications
across all art units

Statute-Specific Performance

§101
9.7%
-30.3% vs TC avg
§103
56.3%
+16.3% vs TC avg
§102
24.1%
-15.9% vs TC avg
§112
4.0%
-36.0% vs TC avg
Black line = Tech Center average estimate • Based on career data from 575 resolved cases

Office Action

§101 §103
DETAILED ACTION Claims 1-10 are examined and pending. 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 . Claim Rejections - 35 USC § 101 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 1-9 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. Claims 1-9 recites a "apparatus" is not a process, machine, manufacture or composition of matter. The claimed element "module" is a non-structural limitation, and in light of the specification being silent regarding the “module”. Therefore, applying the broadest reasonable interpretation as understood by one of ordinary skill in the art, the claimed elements may be interpreted as software only. Thus the claimed subject matter as a whole fails to fall within the definition of a process, machine, manufacture or composition of matter, patentable eligible category subject matter. The examiner encourages applicant to define with the claims the embodied features and limitations on hardware structural limitations by tying the process to the hardware structural limitation such as “comprising: at least one hardware processor; a non-transitory computer-readable storage medium storing instructions which, when executed by the at least one hardware processor, are configured to implement,” or any variants supported by the specification. Therefore, the claimed subject matter as a whole fails to fall within the definition of a process, machine, manufacture or composition of matter, patentable eligible category subject matter. 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 1-3 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Lai et al. (CN 114157469A, hereinafter “Lai”) in view of Jan et al. (U.S. 2024/0232335 A1, hereinafter “Jan”). As to claims 1 and 10, Lai discloses an adversarial attack apparatus, comprising: a data generation module configured to collect a plurality of controller area network (CAN) messages, extract preset some piece of data (ID number and data field content) from the collected plurality of CAN messages, add type information (ID number) about the CAN message to the extracted some pieces of data to generate a CAN message packet, and aggregate the generated CAN message packet to configure a CAN message packet dataset (page 3, paragraph 1-3; discloses obtaining the flow data packet on the CAN bus from the real vehicle. Further, obtains ID number from the data packet from the vehicle. Paragraphs 4-5 discloses establishing the corresponding attack data packet for the ID on the CAN bus and its data segment content of the injection attack using the obtained ID number and injecting the created attack data packet into the real vehicle at a certain frequency); message capable of avoiding an intrusion detection system (IDS) of a vehicle (page 5, paragraph 1; discloses CAN messages train the attack detection model to detect and avoid the attack) However, Lai does not explicitly disclose the apparatus wherein a preprocessing module configured to insert noise into some CAN message packets in the CAN message packet dataset, the noise being inserted based on the type information of each CAN message packet; an adversarial attack generation module configured to receive the CAN message packet into which the noise is inserted and generate an adversarial CAN message. In an analogous art, Jan discloses the apparatus wherein preprocessing module configured to insert noise into some CAN message packets in the CAN message packet dataset, the noise being inserted based on the type information of each CAN message packet (para. [0024]; discloses generating a first noise and taking the noise and adding it to the training data message); and an adversarial attack generation module configured to receive the CAN message packet into which the noise is inserted and generate an adversarial CAN message (para. [0025]; discloses adding the first noise into each of the training data to adjust the training data and generating the adversarial training data message). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Lai by incorporating a function to generate a noise to the training message and generating the adversarial training message as 8taught by Jan in order to increase the ability of the system to defend against attacks. As to claim 2, Lai-Jan discloses the adversarial attack apparatus of claim 1, wherein the preprocessing module includes: a data conversion unit configured to convert a data format of each CAN message packet of the CAN message packet dataset (Lai, page 6, paragraph 7; discloses converting the CAN message into characteristic matric representing the time sequence distribution); and a noise insertion unit configured to insert the noise based on the type information of each CAN message packet (Jan, para. [0051]; discloses adding the first noise into each of the validation data to adjust the validation data). As to claim 3, Lai-Jan discloses the adversarial attack apparatus of claim 2, wherein the type information includes class information indicating whether the corresponding CAN message packet is a normal packet or an attack packet and subclass information indicating whether the corresponding CAN message packet is any type of attack among a flooding attack, a fuzzing attack, a relay attack, and a spoofing attack, when the corresponding CAN message packet is the attack packet (Jan, page 8, paragraph 2; discloses data frame that discloses that has different types of attack type in the format). Allowable Subject Matter Claims 4-9 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Shin et al. (U.S. 2017/0286675 A1) discloses anomaly-based intrusion detection system is presented for use in vehicle networks. The intrusion detection system measures and exploits the intervals of periodic in-vehicle messages for fingerprinting electronic control units. Fingerprints are then used for constructing a baseline of clock behaviors, for example with a Recursive Least Squares algorithm. Based on the baseline, the intrusion detection system uses cumulative sum to detect any abnormal shifts in the identification errors. Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOE CHACKO whose telephone number is (571)270-3318. The examiner can normally be reached Monday-Friday 7am-5pm. 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, Ario Etienne can be reached at 5712724001. 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. /JOE CHACKO/Primary Examiner, Art Unit 2457
Read full office action

Prosecution Timeline

Jun 21, 2024
Application Filed
Dec 27, 2025
Non-Final Rejection — §101, §103
Mar 30, 2026
Response Filed

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12598239
ACCELERATING CONNECTIONS TO A HOST SERVER
2y 5m to grant Granted Apr 07, 2026
Patent 12574338
MULTI-TENANT COLLECTIVE COMMUNICATION FABRIC
2y 5m to grant Granted Mar 10, 2026
Patent 12568365
AUTHENTICATION EVENT PROCESSING METHOD, APPARATUS, AND SYSTEM
2y 5m to grant Granted Mar 03, 2026
Patent 12566848
AUTOMATED THREAT MODELING
2y 5m to grant Granted Mar 03, 2026
Patent 12563043
Universal Conceptual Control Management
2y 5m to grant Granted Feb 24, 2026
Study what changed to get past this examiner. Based on 5 most recent grants.

AI Strategy Recommendation

Get an AI-powered prosecution strategy using examiner precedents, rejection analysis, and claim mapping.
Powered by AI — typically takes 5-10 seconds

Prosecution Projections

1-2
Expected OA Rounds
75%
Grant Probability
92%
With Interview (+17.1%)
3y 3m
Median Time to Grant
Low
PTA Risk
Based on 575 resolved cases by this examiner. Grant probability derived from career allow rate.

Sign in for Full Analysis

Enter your email to receive a magic link. No password needed.

Free tier: 3 strategy analyses per month