Improved authentication method in embedded networks systems. An autonomous vehicle approach

By adding connectivity to in-vehicle networks (including multimedia devices) and external networks (e.g. wireless and Internet) the attack surface was dramatically extended. In this context, there are several types of attacks already been demonstrated on automotive/AV control networks using compromised network connection or physical manipulation. Subsequently, the success attacks violate safety requirements, being able to disrupt system operation or even to take over operational control. In order to avoid false authentication or identity theft of devices or IoT, this paper proposes a time-based authentication method. The proposed method increases the degree of cybersecurity and allows its implementation on independent, low power mobile devices. Finally, a critical conclusion regarding the proposed authentication methods is presented.

Download Full-text

Security for Autonomous Vehicle Networks

2020 IEEE 3rd International Conference on Electronic Information and Communication Technology (ICEICT) ◽

10.1109/iceict51264.2020.9334354 ◽

2020 ◽

Author(s):

Aifen Sui ◽

Gordon Muehl

Keyword(s):

Autonomous Vehicle ◽

Vehicle Networks

Download Full-text

Detection and defense of cyberattacks on the machine learning control of robotic systems

The Journal of Defense Modeling and Simulation Applications Methodology Technology ◽

10.1177/15485129211043874 ◽

2021 ◽

pp. 154851292110438

Author(s):

George W Clark ◽

Todd R Andel ◽

J Todd McDonald ◽

Tom Johnsten ◽

Tom Thomas

Keyword(s):

Machine Learning ◽

Autonomous Vehicles ◽

Defense Mechanisms ◽

Autonomous Vehicle ◽

Learning Algorithms ◽

Learning Model ◽

Machine Learning Algorithms ◽

Robotic Systems ◽

Machine Learning Model ◽

Attack Surface

Robotic systems are no longer simply built and designed to perform sequential repetitive tasks primarily in a static manufacturing environment. Systems such as autonomous vehicles make use of intricate machine learning algorithms to adapt their behavior to dynamic conditions in their operating environment. These machine learning algorithms provide an additional attack surface for an adversary to exploit in order to perform a cyberattack. Since an attack on robotic systems such as autonomous vehicles have the potential to cause great damage and harm to humans, it is essential that detection and defenses of these attacks be explored. This paper discusses the plausibility of direct and indirect cyberattacks on a machine learning model through the use of a virtual autonomous vehicle operating in a simulation environment using a machine learning model for control. Using this vehicle, this paper proposes various methods of detection of cyberattacks on its machine learning model and discusses possible defense mechanisms to prevent such attacks.

Download Full-text

Multilevel Service-Provisioning-Based Autonomous Vehicle Applications

Sustainability ◽

10.3390/su12062497 ◽

2020 ◽

Vol 12 (6) ◽

pp. 2497 ◽

Cited By ~ 8

Author(s):

Mashael Khayyat ◽

Abdullah Alshahrani ◽

Soltan Alharbi ◽

Ibrahim Elgendy ◽

Alexander Paramonov ◽

...

Keyword(s):

Communication Networks ◽

Autonomous Vehicles ◽

Autonomous Vehicle ◽

Access Network ◽

High Mobility ◽

Base Stations ◽

Traffic Density ◽

Fifth Generation ◽

Radio Access ◽

Vehicle Networks

With the recent advances and development of autonomous control systems of cars, the design and development of reliable infrastructure and communication networks become a necessity. The recent release of the fifth-generation cellular system (5G) promises to provide a step towards reliability or a panacea. However, designing autonomous vehicle networks has more requirements due to the high mobility and traffic density of such networks and the latency and reliability requirements of applications run over such networks. To this end, we proposed a multilevel cloud system for autonomous vehicles which was built over the Tactile Internet. In addition, base stations at the edge of the radio-access network (RAN) with different technologies of antennas are used in our system. Finally, simulation results show that the proposed system with multilevel clouding can significantly reduce the round-trip latency and the network congestion. In addition, our system can be adapted in the mobility scenario.

Download Full-text