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Author: Jordi Guijarro
Publisher:
ISBN: 9781638280613
Category : COMPUTERS
Languages : en
Pages : 0
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Book Description
The damaging effects of cyberattacks to an industry like the Cooperative Connected and Automated Mobility (CCAM) can be tremendous. From the least important to the worst ones, one can mention for example the damage in the reputation of vehicle manufacturers, the increased denial of customers to adopt CCAM, the loss of working hours (having direct impact on the European GDP), material damages, increased environmental pollution due e.g., to traffic jams or malicious modifications in sensors' firmware, and ultimately, the great danger for human lives, either they are drivers, passengers or pedestrians.Connected vehicles will soon become a reality on our roads, bringing along new services and capabilities, but also technical challenges and security threats. To overcome these risks, the CARAMEL project has developed several anti-hacking solutions for the new generation of vehicles.CARAMEL (Artificial Intelligence-based Cybersecurity for Connected and Automated Vehicles), a research project co-funded by the European Union under the Horizon 2020 framework programme, is a project consortium with 15 organizations from 8 European countries together with 3 Korean partners. The project applies a proactive approach based on Artificial Intelligence and Machine Learning techniques to detect and prevent potential cybersecurity threats to autonomous and connected vehicles. This approach has been addressed based on four fundamental pillars, namely: Autonomous Mobility, Connected Mobility, Electromobility, and Remote Control Vehicle. This book presents theory and results from each of these technical directions.
Author: Jordi Guijarro
Publisher:
ISBN: 9781638280613
Category : COMPUTERS
Languages : en
Pages : 0
Get Book Here
Book Description
The damaging effects of cyberattacks to an industry like the Cooperative Connected and Automated Mobility (CCAM) can be tremendous. From the least important to the worst ones, one can mention for example the damage in the reputation of vehicle manufacturers, the increased denial of customers to adopt CCAM, the loss of working hours (having direct impact on the European GDP), material damages, increased environmental pollution due e.g., to traffic jams or malicious modifications in sensors' firmware, and ultimately, the great danger for human lives, either they are drivers, passengers or pedestrians.Connected vehicles will soon become a reality on our roads, bringing along new services and capabilities, but also technical challenges and security threats. To overcome these risks, the CARAMEL project has developed several anti-hacking solutions for the new generation of vehicles.CARAMEL (Artificial Intelligence-based Cybersecurity for Connected and Automated Vehicles), a research project co-funded by the European Union under the Horizon 2020 framework programme, is a project consortium with 15 organizations from 8 European countries together with 3 Korean partners. The project applies a proactive approach based on Artificial Intelligence and Machine Learning techniques to detect and prevent potential cybersecurity threats to autonomous and connected vehicles. This approach has been addressed based on four fundamental pillars, namely: Autonomous Mobility, Connected Mobility, Electromobility, and Remote Control Vehicle. This book presents theory and results from each of these technical directions.
Author: Muhammad Habib ur Rehman
Publisher: Springer Nature
ISBN: 3030706044
Category : Technology & Engineering
Languages : en
Pages : 207
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Book Description
This book covers the research area from multiple viewpoints including bibliometric analysis, reviews, empirical analysis, platforms, and future applications. The centralized training of deep learning and machine learning models not only incurs a high communication cost of data transfer into the cloud systems but also raises the privacy protection concerns of data providers. This book aims at targeting researchers and practitioners to delve deep into core issues in federated learning research to transform next-generation artificial intelligence applications. Federated learning enables the distribution of the learning models across the devices and systems which perform initial training and report the updated model attributes to the centralized cloud servers for secure and privacy-preserving attribute aggregation and global model development. Federated learning benefits in terms of privacy, communication efficiency, data security, and contributors’ control of their critical data.
Author: Álvaro Rocha
Publisher: Springer Nature
ISBN: 3031542355
Category :
Languages : en
Pages : 481
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Book Description
Author: Qadeer Ahmed
Publisher: SAE International
ISBN: 1468608150
Category : Technology & Engineering
Languages : en
Pages : 32
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Book Description
Given the rapid advancements in engineering and technology, it is anticipated that connected and automated vehicles (CAVs) will soon become prominent in our daily lives. This development has a vast potential to change the socio-technical perception of public, personal, and freight transportation. The potential benefits to society include reduced driving risks due to human errors, increased mobility, and overall productivity of autonomous vehicle consumers. On the other hand, the potential risks associated with CAV deployment related to technical vulnerabilities are safety and cybersecurity issues that may arise from flawed hardware and software. Cybersecurity and Digital Trust Issues in Connected and Automated Vehicles elaborates on these topics as unsettled cybersecurity and digital trust issues in CAVs and follows with recommendations to fill in the gaps in this evolving field. This report also highlights the importance of establishing robust cybersecurity protocols and fostering digital trust in these vehicles to ensure safe and secure deployment in our modern transportation system. Click here to access The Mobility Frontier: Cybersecurity and Trust Click here to access the full SAE EDGETM Research Report portfolio. https://doi.org/10.4271/EPR2024009
Author: Jyoti Choudrie
Publisher: Springer Nature
ISBN: 9819766788
Category :
Languages : en
Pages : 611
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Book Description
Author: Fei Hu
Publisher: CRC Press
ISBN: 100087723X
Category : Computers
Languages : en
Pages : 357
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Book Description
Deep Learning (DL) is an effective approach for AI-based vehicular networks and can deliver a powerful set of tools for such vehicular network dynamics. In various domains of vehicular networks, DL can be used for learning-based channel estimation, traffic flow prediction, vehicle trajectory prediction, location-prediction-based scheduling and routing, intelligent network congestion control mechanism, smart load balancing and vertical handoff control, intelligent network security strategies, virtual smart and efficient resource allocation and intelligent distributed resource allocation methods. This book is based on the work from world-famous experts on the application of DL for vehicle networks. It consists of the following five parts: (I) DL for vehicle safety and security: This part covers the use of DL algorithms for vehicle safety or security. (II) DL for effective vehicle communications: Vehicle networks consist of vehicle-to-vehicle and vehicle-to-roadside communications. This part covers how Intelligent vehicle networks require a flexible selection of the best path across all vehicles, adaptive sending rate control based on bandwidth availability and timely data downloads from a roadside base-station. (III) DL for vehicle control: The myriad operations that require intelligent control for each individual vehicle are discussed in this part. This also includes emission control, which is based on the road traffic situation, the charging pile load is predicted through DL andvehicle speed adjustments based on the camera-captured image analysis. (IV) DL for information management: This part covers some intelligent information collection and understanding. We can use DL for energy-saving vehicle trajectory control based on the road traffic situation and given destination information; we can also natural language processing based on DL algorithm for automatic internet of things (IoT) search during driving. (V) Other applications. This part introduces the use of DL models for other vehicle controls. Autonomous vehicles are becoming more and more popular in society. The DL and its variants will play greater roles in cognitive vehicle communications and control. Other machine learning models such as deep reinforcement learning will also facilitate intelligent vehicle behavior understanding and adjustment. This book will become a valuable reference to your understanding of this critical field.
Author: Norman Fenton
Publisher: CRC Press
ISBN: 1351978977
Category : Mathematics
Languages : en
Pages : 661
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Book Description
Since the first edition of this book published, Bayesian networks have become even more important for applications in a vast array of fields. This second edition includes new material on influence diagrams, learning from data, value of information, cybersecurity, debunking bad statistics, and much more. Focusing on practical real-world problem-solving and model building, as opposed to algorithms and theory, it explains how to incorporate knowledge with data to develop and use (Bayesian) causal models of risk that provide more powerful insights and better decision making than is possible from purely data-driven solutions. Features Provides all tools necessary to build and run realistic Bayesian network models Supplies extensive example models based on real risk assessment problems in a wide range of application domains provided; for example, finance, safety, systems reliability, law, forensics, cybersecurity and more Introduces all necessary mathematics, probability, and statistics as needed Establishes the basics of probability, risk, and building and using Bayesian network models, before going into the detailed applications A dedicated website contains exercises and worked solutions for all chapters along with numerous other resources. The AgenaRisk software contains a model library with executable versions of all of the models in the book. Lecture slides are freely available to accredited academic teachers adopting the book on their course.
Author: Gereon Meyer
Publisher: Springer
ISBN: 3319405039
Category : Technology & Engineering
Languages : en
Pages : 292
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Book Description
This edited book comprises papers about the impacts, benefits and challenges of connected and automated cars. It is the third volume of the LNMOB series dealing with Road Vehicle Automation. The book comprises contributions from researchers, industry practitioners and policy makers, covering perspectives from the U.S., Europe and Japan. It is based on the Automated Vehicles Symposium 2015 which was jointly organized by the Association of Unmanned Vehicle Systems International (AUVSI) and the Transportation Research Board (TRB) in Ann Arbor, Michigan, in July 2015. The topical spectrum includes, but is not limited to, public sector activities, human factors, ethical and business aspects, energy and technological perspectives, vehicle systems and transportation infrastructure. This book is an indispensable source of information for academic researchers, industrial engineers and policy makers interested in the topic of road vehicle automation.
Author: Anand Paul
Publisher: Elsevier
ISBN: 0128095466
Category : Transportation
Languages : en
Pages : 244
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Book Description
Intelligent Vehicular Network and Communications: Fundamentals, Architectures and Solutions begins with discussions on how the transportation system has transformed into today's Intelligent Transportation System (ITS). It explores the design goals, challenges, and frameworks for modeling an ITS network, discussing vehicular network model technologies, mobility management architectures, and routing mechanisms and protocols. It looks at the Internet of Vehicles, the vehicular cloud, and vehicular network security and privacy issues. The book investigates cooperative vehicular systems, a promising solution for addressing current and future traffic safety needs, also exploring cooperative cognitive intelligence, with special attention to spectral efficiency, spectral scarcity, and high mobility. In addition, users will find a thorough examination of experimental work in such areas as Controller Area Network protocol and working function of On Board Unit, as well as working principles of roadside unit and other infrastructural nodes. Finally, the book examines big data in vehicular networks, exploring various business models, application scenarios, and real-time analytics, concluding with a look at autonomous vehicles. - Proposes cooperative, cognitive, intelligent vehicular networks - Examines how intelligent transportation systems make more efficient transportation in urban environments - Outlines next generation vehicular networks technology
Author: Raj Ponnaluri
Publisher: Elsevier
ISBN: 0128208856
Category : Transportation
Languages : en
Pages : 250
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Book Description
Disruption in Transportation, as some experts say, is here; so is this book at this critical inflection point in the history of transportation planning, engineering, and operations. With a focus on improving safety and maximizing available systems to accommodate all modes of travel, this work brings together an array of topics and themes on transportation technologies under the banner of Connected and Automated Vehicles (CAV). The emerging technology implementing entities, industry leaders, original equipment manufacturers, standard development organizations, researchers, and others are singularly focused on a global multilogue to promote Safety, Mobility, Environment, and Economic Development (SMEEd). These discussions are technologically interdisciplinary and procedurally cross-functional, hence the need for CAV: Developing Policies, Designing Programs, and Deploying Projects. This book is aimed at the policy-maker who wants to know the high-level detail; the planner who chooses to pursue the most efficient path to implementation; the professional engineer who needs to design a sustainable system; the practitioner who considers deployable frameworks; the project manager who oversees the system deployment; the private sector consultant who develops and delivers a CAV program; and the researcher who evaluates the project benefits and documents lessons learned. This book makes a business case for implementing CAV technologies to achieve SMEEd goals; presents the possibilities and challenges to deploying emerging technologies; identifies the institutional roles and responsibilities; and develops a policy framework for mainstreaming CAV. - A comprehensive perspective on emerging technologies and CAV policies, planning, and practice - A practical guide to support the development of a policy framework, business case, and justify funding - A real-world experience-driven discussion with case studies, lessons learned, and road map creation - A goal-oriented and practitioner-focused detail to draft, design, and deploy emerging technologies and CAV to achieve safety and mobility outcomes
