Search Results

Abstract In the pursuit of advancing autonomous vehicles (AVs), data-driven algorithms have become pivotal in replacing human perception and decision-making. While deep neural networks (DNNs) hold promise for perception tasks, the potential for catastrophic consequences due to algorithmic flaws is concerning. A well-known incident in 2016, involving a Tesla autopilot misidentifying a white truck as a cloud, underscores the risks and security vulnerabilities. In this article, we present a novel threat model and risk assessment (TARA) analysis on AV data storage, delving into potential threats and damage scenarios. Specifically, we focus on DNN parameter manipulation attacks, evaluating their impact on three distinct algorithms for traffic sign classification and lane assist.

Abstract Secure boot is a fundamental security primitive for establishing trust in computer systems. For real-time safety applications, the time taken to perform the boot measurement conflicts with the need for near instant availability. To speed up the boot measurement while establishing an acceptable degree of trust, we propose a dual-phase secure boot algorithm that balances the strong requirement for data tamper detection with the strong requirement for real-time availability. A probabilistic boot measurement is executed in the first phase to allow the system to be quickly booted. This is followed by a full boot measurement to verify the first-phase results and generate the new sampled space for the next boot cycle. The dual-phase approach allows the system to be operational within a fraction of the time needed for a full boot measurement while producing a high detection probability of data tampering.

New vision @ Gentex Creating a vital ADAS partner through home-grown R&D and manufacturing in (of all places) western Michigan. Positioning for hybrid growth BorgWarner "modularizes" to provide OEMs optimal electrified-driveline flexibility. Editorial: Beleaguered diesel could use a break-or a breakthrough SAE Standards News Kickoff to begin testing program to validate SAE J2954 wireless charging Recommended Practice Supplier Eye Will you be an active participant or passive bystander? The Navigator For future vehicles, communication equals trust Tenneco readies new semi-active digital suspension for 2020 New 90-degree turbo V6 leads Audi's hybridization blitz GKN using modular control algorithms for added systems integration U of M students engineer new autonomous shuttle system Jaguar's 2018 E-Pace shares Land Rover bones Ford pumps powertrains for 2018 F-150 2018 Subaru Crosstrek moves to new global platform Nissan's Ponz Pandikithura on EV lifecycle value

Editorial AV lidar enters a new reality The Navigator UNECE takes first step toward AV regulation Special Delivery - by 'Bot Michigan start-up Refraction AI aims to be the go-to for last-mile, semi-autonomous, all-weather delivery robots. Lidar Infiltrates ADAS Once considered a necessity only in fully autonomous vehicles, lidar sensors are now being evaluated for lower-level driver-assistance systems. Training Data-hungry AI Algorithms Large-scale data refinement is key to bringing more sophisticated automated-driving functions to series production. Simulation's Next Generation Do autonomous-vehicle developers have their simulation strategies all wrong? Some experts think so - but suggest there's a practical solution. Marelli's COVID-killing HVAC Insert With big implications for shared mobility, a new photocatalytic cabin-air purifier claims to kill viruses - including COVID-19. Is Ground-penetrating Radar Next for AV Sensing?

In this paper, we outline past, present and future applications of automotive security for engine ECUs. Electronic immobilizers and anti-tuning countermeasures have been used for several years. Recently, OEMs and suppliers are facing more and more powerful attackers, and as a result, have introduced stronger countermeasures based on hardware security. Finally, with the advent of connected cars, it is expected that many things that currently require a physical connection will be done remotely in a near future. This includes remote diagnostics, reprogramming and engine calibration.

Abstract Testing and verifying the security of connected and autonomous vehicles (CAVs) under cyber-physical attacks is a critical challenge for ensuring their safety and reliability. Proposed in this article is a novel testing framework based on a model of computation that generates scenarios and attacks in a closed-loop manner, while measuring the safety of the unit under testing (UUT), using a verification vector. The framework was applied for testing the performance of two cooperative adaptive cruise control (CACC) controllers under false data injection (FDI) attacks. Serving as the baseline controller is one of a traditional design, while the proposed controller uses a resilient design that combines a model and learning-based algorithm to detect and mitigate FDI attacks in real-time.

CAN bus network proved to be efficient and dynamic for small compact cars as well as heavy-duty vehicles (HDV). However, HDVs are more susceptible to malicious attacks due to lack of security in their intra-vehicle communication protocols. SAE proposed a new standard named J1939-91C for CAN-FD networks which provides methods for establishing trust and securing mutual messages with optional encryption. J1939-91C ensures message authenticity, integrity, and confidentiality by implementing complex cryptographic operations including hash functions and random key generation. In this paper, the three main phases of J1939-91C, i.e., Network Formation, Rekeying, and Message Exchange, are simulated and tested on Electronic Control Units (ECUs) supporting CAN-FD network. Numerous test vectors were generated and validated to support SAE J1939-91C. The mentioned vectors were produced by simulating different encryption and hashing algorithms with variable message and key lengths.

In conjunction with an increasing number of related laws and regulations (such as UNECE R155 and ISO 21434), these drive security requirements in different domains and areas. 2 In this paper we examine the upcoming trends in EE architectures and investigate the underlying cyber-security threats and corresponding security requirements that lead to potential requirements for “Automotive Embedded Hardware Trust Anchors” (AEHTA).

The caveat to these additional capabilities is issues like cybersecurity, complexity, etc. This paper is an exploration into FuSa and CAVs and will present a systematic approach to understand challenges and propose potential framework, Intelligent Vehicle Monitoring for Safety and Security (IVMSS) to handle faults/malfunctions in CAVs, and specifically autonomous systems.

Here, we discuss the On-Board Diagnostic (OBD) regulations for next generation BEV/HEV, its vulnerabilities and cybersecurity threats that come with hacking. We propose three cybersecurity attack detection and defense methods: Cyber-Attack detection algorithm, Time-Based CAN Intrusion Detection Method and, Feistel Cipher Block Method. ...These control methods autonomously diagnose a cybersecurity problem in a vehicle’s onboard system using an OBD interface, such as OBD-II when a fault caused by a cyberattack is detected, All of this is achieved in an internal communication network structure.

Annual conference government policy, regulatory makers, automotive industry neutral forum discuss US government regulation, technology, customer acceptance future vehicle design. industry event safety, emission control, fuel efficiency, automated vehicles.

Vehicle cybersecurity consists of internal security and external security. Dedicated security hardware will play an important role in car’s internal and external security communication. ...For certain AURIX MCU consisting of HSM, the experiment result shows that cheaper 32-bit HSM’s AES calculating speed is 25 times of 32-bit main controller, so HSM is an effective choice to realize cybersecurity. After comparing two existing methods that realize secure CAN communication, A Modified SECURE CAN scheme is proposed, and differences of the three schemes are analyzed.

Abstract Vehicle-to-Vehicle (V2V) communication is a vehicular communication technology to reduce traffic accidents and congestion. To protect V2V communication, multiple security standards have been developed. This article provides an overview of the China V2V security draft standard and compares it to the American IEEE1609.2 V2V standard and to the Security Credential Management System (SCMS). The article provides an overview of the Chinese cryptographic algorithms used in the China V2V standard, and points out differences in the certificate format, such as the lack of implicit certificates in the China V2V standard. The China V2V PKI architecture is similar to the American SCMS, however, the Chinese system utilizes a set of Root Certificate Authorities (CA) that are trusted via an out-of-band channel whereas the American SCMS supports elector-based addition and revocation of Root CAs.

Abstract Aircraft cybersecurity efforts have tended to focus at the strategic or tactical levels without a clear connection between the two. ...CSSEP’s process model postulates that security is best achieved by a balance of cybersecurity, cyber resiliency, defensibility, and recoverability and that control is best established by developing security constraints versus attempting to find every vulnerability. ...CSSEP identifies the major functions needed to do effective aircraft cybersecurity and provides a flexible framework as the “missing link” to connect the strategic and tactical levels of aircraft cybersecurity.

Cyber security is becoming increasingly critical in the car industry. Not only the entry points to the external world in the car need to be protected against potential attack, but also the on-board communication in the car require to be protected against attackers who may try to send unauthorized CAN messages. However, the current CAN network was not designed with security in mind. As a result, the extra measures have to be taken to address the key security properties of the secure CAN communication, including data integrity, authenticity, confidentiality and freshness. While integrity and authenticity can be achieved by using a relatively straightforward algorithms such as CMAC (Cipher-based Message Authentication Code) and Confidentiality can be handled by a symmetric encryption algorithm like AES128 (128-bit Advanced Encryption Standard), it has been recognized to be more challenging to achieve the freshness of CAN message.

The authors previously presented at SAE 2015, the use of acoustic diagnostic network algorithms (Acoustic DNA) for the measurement and analysis of noise paths in motor vehicles. To further the understanding of the huge amount of data created in this method, especially by the end user or customer, a secure web based application platform has been engineered. The current paper presents operating aspects of the web based approach, including cyber security, multi device accessibility and intuitive user interface together with an innovative optimization toolbox from which both noise sources and vehicle body systems can be modified to be target compliant.

Due to the rapid development in the technological aspect of the autonomous vehicle (AV), there is a compelling need for research in the field vehicle efficiency and emission reduction without affecting the performance, safety and reliability of the vehicle. Electric vehicle (EV) with rechargeable battery has been proved to be a practical solution for the above problem. In order to utilize the maximum capacity of the battery, a proper power management and control mechanism need to be developed such that it does not affect the performance, reliability and safety of vehicle. Different optimization techniques along with deterministic dynamic programming (DDP) approach are used for the power distribution and management control. The battery-operated electric vehicle can be recharged either by plug-in a wired connection or by the inductive mean (i.e. wirelessly) with the help of the electromagnetic field energy.