PATENT CLAIM ANALYSIS

Application Number: 15868663
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2018-05
Patent Classification: ["340", "426100"]

Abstract:
An anti-fraud method for use in an in-vehicle network system including a plurality of electronic control units that exchange, in an in-vehicle network, data frames, each having added thereto a message authentication code (MAC). The method includes generating a first MAC by using a MAC key and a value of a counter that counts a number of times a data frame having added thereto a MAC is transmitted to the in-vehicle network. The method also includes performing verification that the data frame received has added thereto the generated first MAC and incrementing a number of error occurrences when the verification has failed for the data frame, the data frame including a predetermined ID. When the number of error occurrences exceeds a predetermined threshold, a process associated in advance with the predetermined ID is executed.

Claim (Index 9):
The method according to  claim 1 , wherein\n each of the plurality of electronic control units belonging to a group among a plurality of types of groups, and the method further comprises executing, when the verification has failed, by each of the plurality of electronic control units, a process determined in advance in association with a group to which an electronic control unit belongs.

Metadata:
- Claim Count in Document: 29.0
- Percentile: 86.0
- Lexical Diversity: 2.01389
- Patent Class: 340.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['15636007', '15183443', '15183398', '15163234', '15275860']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.7623225486272189
- 35 USC 102 Novelty (BERT): 0.5813891724850763
- Combined Prediction Score: 0.7442292110130047
- Mean Citation Score: 403.893598
- Max Citation Score: 510.13803
- Similarity Product: 373.9076009046865

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test