Automotive Cybersecurity: An Introduction to ISO/SAE 21434

2021 ◽  
Author(s):  
David Ward ◽  
Paul Wooderson
Keyword(s):  
Cyber Physical Systems ◽  
Cyber Attack ◽  
Global Level ◽  
Automated Systems ◽  
Physical Systems ◽  
Personal Computing ◽  
Healthcare Data ◽  
Digital World ◽  
Cyber Crimes ◽  
Financial Transactions

Industries, regulators, and consumers alike see cybersecurity as an ongoing challenge in our digital world. Protecting and defending computer assets against malicious attacks is a part of our everyday lives. From personal computing devices to online financial transactions to sensitive healthcare data, cyber crimes can affect anyone. As technology becomes more deeply embedded into cars in general, securing the global automotive infrastructure from cybercriminals who want to steal data and take control of automated systems for malicious purposes becomes a top priority for the industry. Systems and components that govern safety must be protected from harmful attacks, unauthorized access, damage, or anything else that might interfere with safety functions. Automotive Cybersecurity: An Introduction to ISO/SAE 21434 provides readers with an overview of the standard developed to help manufacturers keep up with changing technology and cyber-attack methods. ISO/SAE 21434 presents a comprehensive cybersecurity tool that addresses all the needs and challenges at a global level. Industry experts, David Ward and Paul Wooderson, break down the complex topic to just what you need to know to get started including a chapter dedicated to frequently asked questions. Topics include defining cybersecurity, understanding cybersecurity as it applies to automotive cyber-physical systems, establishing a cybersecurity process for your company, and explaining assurances and certification.

Dual Redundant Cyber-Attack Tolerant Control Systems Strategy for Cyber-Physical Systems

2019 ◽  
Author(s):  
Marco A. Gamarra ◽  
Sachin Shetty ◽  
Oscar R. Gonzalez ◽  
Laurent Njilla ◽  
Marcus Pendleton ◽  
...  
Keyword(s):  
Control Systems ◽  
Cyber Physical Systems ◽  
Cyber Attack ◽  
Physical Systems

scholarly journals Expressive and Deployable Swarm Intelligence Based Cybersecurity for Wireless Sensor Network

2019 ◽  
pp. 761-770
Author(s):  
I. Govindharajn ◽  
P. Jeeva ◽  
M. Kanimozhi ◽  
S. Kodieswari ◽  
A. Narmadha
Keyword(s):  
Swarm Intelligence ◽  
Cyber Security ◽  
Cyber Physical Systems ◽  
Wireless Sensor ◽  
Grey Wolf Optimizer ◽  
Cyber Attack ◽  
Grey Wolf ◽  
Physical Systems ◽  
Mobile Anchor ◽  
Mobile Anchor Node

Wireless sensor networks (WSNs) play a pivotal role in Cyber Physical Systems (CPSs), particularly for operations such as observing the location and monitoring it. To enhance the cyber security in WSN-enabled CPSs, various researchers have proposed a various category of algorithms, inspired by biological phenomena. These algorithm works on the basis of mobility of head node (Mobile Anchor Node). However, these WSNs mobile anchor node are subject to various types of optimization like Grey wolf optimizer (GWO) and Whale optimization Algorithm (WOA). Complexity is one of the limitation of these algorithm and also it is vulnerable to damage, theft, or destruction of sensitive data, in addition to that interference in services also occur in CPSs. To prevent these cyber-attack, we proposed generic bio-inspired model ie., enhanced Grey wolf optimizer path planning called Swarm Intelligence for WSN Cyber security that addresses drawbacks of prior bio-inspired approaches. In this model WSN enabled Cyber Physical Systems use ID-Based Aggregate Signature Scheme to detect the cyber-attack and keep data integrity

scholarly journals RADIO FREQUENCY IDENTIFICATION IN CYBER-PHYSICAL SYSTEMS

2021 ◽  
Vol 82 (2) ◽  
pp. 22-28
Author(s):  
Kamila Mašková ◽  
◽  
Iryna Petrovska ◽  
Oleksandr Ryshkovskyy ◽  
Svyatoslav Yatsyshyn ◽  
...  
Keyword(s):  
Radio Frequency Identification ◽  
Cyber Physical Systems ◽  
Programmable Logic ◽  
Automated Systems ◽  
Automatic Tracking ◽  
Physical Systems ◽  
Frequency Identification ◽  
Universal Interface ◽  
Profibus Dp ◽  
Rfid Antennas

Automated systems that are part of cyber-physical systems provide distribution of goods or prefabricated components, as well as their documenting and automatic tracking in real-time. Workpieces are marked with RFID transponders. RFID antennas allow contactless reading and/or recording of information, RFID electronics process and transmit it to the programmable logic controller via PROFIBUS DP, PROFINET, Ethernet IP, Ethernet TCP/IP, or EtherCAT interface. The peculiarities of the universal interface for the needs of cyber-physical systems equipped with RFID means and the main metrological characteristics of the latter are studied in the work.

scholarly journals In-Factory Learning – Qualification For The Factory Of The Future

2015 ◽  
Vol 66 (1) ◽  
pp. 159-164 ◽  
Author(s):  
Fabian Quint ◽  
Katharina Mura ◽  
Dominic Gorecky
Keyword(s):  
Mixed Reality ◽  
Cyber Physical Systems ◽  
Learning System ◽  
Digital Content ◽  
Internet Technologies ◽  
Physical Systems ◽  
Digital World ◽  
Engineering Information ◽  
Physical Objects ◽  
Factory Of The Future

Abstract The Industry 4.0 vision anticipates that internet technologies will find their way into future factories replacing traditional components by dynamic and intelligent cyber-physical systems (CPS) that combine the physical objects with their digital representation. Reducing the gap between the real and digital world makes the factory environment more flexible, more adaptive, but also more complex for the human workers. Future workers require interdisciplinary competencies from engineering, information technology, and computer science in order to understand and manage the diverse interrelations between physical objects and their digital counterpart. This paper proposes a mixed-reality based learning environment, which combines physical objects and visualisation of digital content via Augmented Reality. It uses reality-based interaction in order to make the dynamic interrelations between real and digital factory visible and tangible. We argue that our learning system does not work as a stand-alone solution, but should fit into existing academic and advanced training curricula.

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