CAN-D: A Modular Four-Step Pipeline for Comprehensively Decoding Controller Area Network Data

06/09/2020
by   Miki E. Verma, et al.
0

CANs are a broadcast protocol for real-time communication of critical vehicle subsystems. Original equipment manufacturers of passenger vehicles hold secret their mappings of CAN data to vehicle signals, and these definitions vary according to make, model, and year. Without these mappings, the wealth of real-time vehicle information hidden in the CAN packets is uninterpretable, impeding vehicle-related research. Guided by the 4-part CAN signal definition, we present CAN-D (CAN-Decoder), a modular, 4-step pipeline for identifying each signal's boundaries (start bit, length), endianness (byte order), signedness (bit-to-integer encoding), and by leveraging diagnostic standards, augmenting a subset of the extracted signals with physical interpretation. We provide a comprehensive review of the CAN signal reverse engineering research. Previous methods ignore endianness and signedness, rendering them incapable of decoding many standard CAN signal definitions. Incorporating endianness grows the search space from 128 to 4.72E21 signal tokenizations and introduces a web of changing dependencies. We formulate, formally analyze, and provide an efficient solution to an optimization problem, allowing identification of the optimal set of signal boundaries and byte orderings. We provide two novel, state-of-the-art signal boundary classifiers-both superior to previous approaches in precision and recall in three different test scenarios-and the first signedness classification algorithm which exhibits a >97% F-score. CAN-D is the only solution with the potential to extract any CAN signal. In evaluation on 10 vehicles, CAN-D's average ℓ^1 error is 5x better than all previous methods and exhibits lower ave. error, even when considering only signals that meet prior methods' assumptions. CAN-D is implemented in lightweight hardware, allowing for an OBD-II plugin for real-time in-vehicle CAN decoding.

READ FULL TEXT

page 1

page 2

page 9

page 12

page 13

research
12/30/2018

Towards a CAN IDS based on a neural-network data field predictor

Modern vehicles contain a few controller area networks (CANs), which all...
research
11/22/2019

On the Robustness of Signal Characteristic-Based Sender Identification

Vehicles become more vulnerable to remote attackers in modern days due t...
research
07/17/2022

Real Time Vehicle Identification

Identification of the vehicles passing over the roads is a very importan...
research
02/24/2019

Extracting Vehicle Sensor Signals from CAN Logs for Driver Re-identification

Data is the new oil for the car industry. Cars generate data about how t...
research
06/25/2022

Diagnostic Communication and Visual System based on Vehicle UDS Protocol

Unified Diagnostic Services (UDS) is a diagnostic communication protocol...
research
06/30/2021

EVScout2.0: Electric Vehicle Profiling Through Charging Profile

EVs (Electric Vehicles) represent a green alternative to traditional fue...

Please sign up or login with your details

Forgot password? Click here to reset