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As a promising strategic industry group that is rapidly evolving around the world, autonomous vehicle is entering a critical phase of commercialization from demonstration to end markets. The global automotive industry and governments are facing new common topics and challenges brought by autonomous vehicle, such as how to test, assess, and administrate the autonomous vehicle to ensure their safe running in real traffic situations and proper interactions with other road users. Starting from the facts that the way to autonomous driving is the process of a robot or a machine taking over driving tasks from a human. This paper summarizes the main characteristics of autonomous vehicle which are different from traditional one, then demonstrates the limitations of the existing certification mechanism and related testing methods when applied to autonomous vehicle.

Recent developments in the commercialization of mobility services have brought unprecedented connectivity to the automotive sector. While the adoption of connected features provides significant benefits to vehicle owners, adversaries may leverage zero-day attacks to target the expanded attack surface and make unauthorized access to sensitive data. Protecting new generations of automotive controllers against malicious intrusions requires solutions that do not depend on conventional countermeasures, which often fall short when pitted against sophisticated exploitation attempts. In this paper, we describe some of the latent risks in current automotive systems along with a well-engineered multi-layer defense strategy. Further, we introduce a novel and comprehensive attack and performance test framework which considers state-of-the-art memory corruption attacks, countermeasures and evaluation methods.

Multiple approaches have been created to enhance intra-vehicle communications security over the past three decades since the introduction of the Controller Area Network (CAN) protocol. The twin pair differential-mode communications bus is tremendously robust in the face of interference, yet physical access to the bus offers a variety of potential attack vectors whereby false messages and/or denial of service are achievable. This paper evaluates extensions of a Physical-layer (PHY) common-mode watermark-based authentication technique recently developed to improve authentication on the CAN bus by considering the watermark as a side-channel communications means for high value information. We also propose and analyze higher layer algorithms, with benefits and pitfalls, for employing the watermark as a physical-layer firewall.

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.

As an important part of intelligent driving vehicles and intelligent networked transportation systems, environmental perception technology can provide important decision-making basis for the overall planning of intelligent driving vehicles and transportation systems. This paper reviews the current research on environment perception technology in the current intelligent networked transportation system, and analyzes four key research directions and related progress of environmental sensing technologies, including single sensor device, high-precision map, multi-sensor information fusion and vehicle-road collaboration. On the basis of analyzing and summarizing existing related research, this article elaborates the development trend and key directions of future environmental perception technology, including the integration of deep learning, vehicle-road integration, information security and multi-dimensional perception technology related development directions.

Facial recognition software (FRS) is a form of biometric security that detects a face, analyzes it, converts it to data, and then matches it with images in a database. This technology is currently being used in vehicles for safety and convenience features, such as detecting driver fatigue, ensuring ride share drivers are wearing a face covering, or unlocking the vehicle. Public transportation hubs can also use FRS to identify missing persons, intercept domestic terrorism, deter theft, and achieve other security initiatives. However, biometric data is sensitive and there are numerous remaining questions about how to implement and regulate FRS in a way that maximizes its safety and security potential while simultaneously ensuring individual’s right to privacy, data security, and technology-based equality.

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.

Automotive safety is always the focus of consumers, the selling point of products, the focus of technology. In order to achieve automatic driving, interconnection with the outside world, human-automatic system interaction, the security connotation of intelligent and connected vehicles (ICV) changes: information security is the basis of its security. Functional safety ensures that the system is operating properly. Behavioral safety guarantees a secure interaction between people and vehicles. Passive security should not be weakened, but should be strengthened based on new constraints. In terms of information safety, the threshold for attacking cloud, pipe, and vehicle information should be raised to ensure that ICV system does not fail due to malicious attacks. The cloud is divided into three cloud platforms according to functions: ICVs private cloud, TSP cloud, public cloud.

To help address the issue of message authentication on the Controller Area Network (CAN) bus, researchers at Virginia Tech and Ford Motor Company have developed a proof-of-concept time-evolving watermark-based authentication mechanism that offers robust, cryptographically controlled confirmation of a CAN message's authenticity. This watermark is injected as a common-mode signal on both CAN-HI and CAN-LO bus voltages and has been proven using a low-cost software-defined radio (SDR) testbed. This paper extends prior analysis on the design and proof-of-concept to consider robustness testing over the range of voltages, both steady state drifts and transients, as are commonly witnessed within a vehicle. Overall performance results, along with a dynamic watermark amplitude control, validate the concept as being a practical near-term approach at improving authentication confidence of messages on the CAN bus.

Significant growth of Unmanned Aerial Vehicles (UAV) has unlocked many services and applications opportunities in the healthcare sector. Aerial transportation of medical cargo delivery can be an effective and alternative way to ground-based transport systems in times of emergency. To improve the security and the trust of such aerial transportation systems, Blockchain can be used as a potential technology to manage, operate and monitor the entire process. In this paper, we present a blockchain network solution based on Ethereum for the transportation of medical cargo such as blood, medicines, vaccines, etc. The smart contract solution developed in solidity language was tested using the Truffle program. Ganache blockchain test network was employed to host the blockchain network and test the operation of the proposed blockchain model. The suitability of the model is validated in real-time using a UAV and all the flight data are captured and uploaded into the blockchain.

With the rapid development of connected and autonomous vehicles, more sophisticated automotive systems running large portions of software and implementing a variety of communication interfaces are being developed. The ever-expanding codebase increases the risk for software vulnerabilities, while at the same time the large number of communication interfaces make the systems more susceptible to be targeted by attackers. As such, it is of utmost importance for automotive organizations to identify potential vulnerabilities early and continuously in the development lifecycle in an automated manner. In this paper, we suggest a practical approach for integrating fuzz testing into a Continuous Integration (CI) pipeline for automotive systems. As a first step, we have performed a Threat Analysis and Risk Assessment (TARA) of a general E/E architecture to identify high-risk interfaces and functions.

Vehicles have more connectivity options now-a-days and these increasing connection options are giving more chances for an intruder to exploit the system. So, the vehicle manufacturers need to make the ECU in the vehicle more secure. To make the system secure, the embedded system must secure all the assets in the system. Examples of assets are Software, Kernel or Operating system, cryptographic Keys, Passwords, user data, etc. In this, securing the Kernel is extremely important as an intruder can even exploit the operating system characteristics just by changing the kernel code without introducing a trojan in the system. Also, the Kernel is the one entity that manages all permissions, so, if the kernel is hacked, these permissions also get compromised. The proposed approach is to make the kernel secure by doing the integrity check periodically of the kernel code loaded into the main memory of the system.

Access control enforces security policies for controlling critical resources. For V2X (Vehicle to Everything) autonomous military vehicle fleets, network middleware systems such as ROS (Robotic Operating System) expose system resources through networked publisher/subscriber and client/server paradigms. Without proper access control, these systems are vulnerable to attacks from compromised network nodes, which may perform data poisoning attacks, flood packets on a network, or attempt to gain lateral control of other resources. Access control for robotic middleware systems has been investigated in both ROS1 and ROS2. Still, these implementations do not have mechanisms for evaluating a policy's consistency and completeness or writing expressive policies for distributed fleets. We explore an RBAC (Role-Based Access Control) mechanism layered onto ROS environments that uses local permission caches with precomputed truth tables for fast policy evaluation.

The new generation vehicles these days are managed by networked controllers. A large portion of the networks is planned with more security which has recently roused researchers to exhibit various attacks against the system. This paper talks about the liabilities of the Controller Area Network (CAN) inside In-vehicle communication protocol and a few potentials that could take due advantage of it. Moreover, this paper presents a few security measures proposed in the present examination status to defeat the attacks. In any case, the fundamental objective of this paper is to feature a comprehensive methodology known as Intrusion Detection System (IDS), which has been a significant device in getting network data in systems over many years. To the best of our insight, there is no recorded writing on a through outline of IDS execution explicitly in the CAN transport network system.

In agriculture industry, increasing use of Vehicle Internet of Things (IoT), telematics and emerging technologies are resulting in smarter machines with connected solutions. Inter and Intra Communication with vehicle to vehicle and inside vehicle - Electronic Control Unit (ECU) to ECU or ECU (Electronic Control Unit) to sensor, requirement for flow of data increased in-turn resulting in increased need for secure communication. In this paper, we focus on functional verification and validation of secure Controller Area Network (CAN) for intra vehicular communication to establish confidentiality, integrity, authenticity, and freshness of data, supporting safety, advanced automation, protection of sensitive data and IP (Intellectual Property) protection. Network security algorithms and software security processes are the layers supporting to achieve our cause.

Autonomous vehicles might one day be able to implement privacy preserving driving patterns which humans may find too difficult to implement. In order to measure the difference between location privacy achieved by humans versus location privacy achieved by autonomous vehicles, this paper measures privacy as trajectory anonymity, as opposed to single location privacy or continuous privacy. This paper evaluates how trajectory privacy for randomized driving patterns could be twice as effective for autonomous vehicles using diverted paths compared to Google Map API generated shortest paths. The result shows vehicles mobility patterns could impact trajectory and location privacy. Moreover, the results show that the proposed metric outperforms both K-anonymity and KDT-anonymity.

Upon their arrival, Unmanned Autonomous Systems (UAS) brought with them many benefits for those involved in a military campaign. They can use such systems to reconnoiter dangerous areas, provide 24-hr aerial security surveillance for force protection purposes or even attack enemy targets all the while avoiding friendly human losses in the process. Unfortunately, these platforms also carry the inherent risk of being built on innately vulnerable cybernetic systems. From software which can be tampered with to either steal data, damage or even outright steal the aircraft, to the data networks used for communications which can be jammed or even eavesdropped on to gain access to sensible information. All this has the potential to turn the benefits of UAS into liabilities and although the last decade has seen great advances in the development of protection and countermeasures against the described threats and beyond the risk still endures.

Autonomous driving represents the ultimate goal of future automobile development. As a collaborative application that integrates vehicles, road infrastructure, network and cloud, autonomous driving business requires a high-degree dynamic cooperation among multiple resources such as data, computing and communications that are distributed throughout the system. In order to meet the anticipated high demand for resources and performance requirements of autonomous driving, and to ensure the safety and comfort of the vehicle users and pedestrians, a top concern of autonomous driving is to understand the system requirements for resources and conduct an in-depth analysis of the autonomous driving business. In this context, this paper presents a comprehensive analysis of the typical business for autonomous driving and establishes an analysis model for five common capabilities, i.e. collection, transmission, intelligent computing, human-machine interaction (HMI), and security.

In the past, aircraft network design did not demand for information security considerations. The aircraft systems were simple, obscure, proprietary and, most importantly for security, the systems have been either physically isolated or they have been connected by directed communication links. The union of the aircraft systems thus formed a federated network. These properties are in sharp contrast with today’s system designs, which rest upon platform-based solutions with shared resources being interconnected by a massively meshed and shared communication network. The resulting connectivity and the high number of interfaces require an in-depth security analysis as the systems also provide functions that are required for the safe operation of the aircraft. This network design evolution, however, resulted in an iterative and continuous adaption of existing network solutions as these have not been developed from scratch.

There continues to be massive advancements in modern connected vehicles and with these advancements, connectivity continues to rapidly become more integral to the way these vehicles are designed and operated. Vehicle connectivity was originally introduced for the purpose of providing software updates to the vehicle’s main system software, and we have seen the adoption of Over The Air updates (OTA) become mainstream with most OEMs. The exploitation of this connectivity is far more reaching than just basic software updates. In the latest vehicles it is possible to update software not just on the main vehicle systems, but to potentially update embedded software in all smart ECUs within the vehicle. Only using the connectivity to push data to the vehicle is not making full use of the potential of this increased connectivity. Being able to collect vehicle data for offline analysis and processing also brings huge benefits to the use of this technology.