scholarly journals DEPENDABLE INTERNET OF THINGS FOR NETWORKED CARS

2017 ◽  
pp. 226-237
Author(s):  
Bernhard Großwindhager ◽  
Astrid Rupp ◽  
Martin Tappler ◽  
Markus Tranninger ◽  
Samuel Weiser ◽  
...  

The Internet of Things (IoT) extends the Internet to include also wireless embedded computers that are often equipped with sensors and actuators to monitor and control their physical environment. The IoT is increasingly used for safety-critical applications such as smart factories or networked cars, where a failure of the IoT may lead to catastrophic consequences. The IoT is therefore in urgent need of dependability, where reliability, availability, and security properties can be guaranteed even in harsh environments (e.g., radio interference) and under deliberate attacks (e.g., exploiting side channels). In this paper we give an overview of recent research activities in the LEAD project “Dependable Internet of Things in Adverse Environments” towards a dependable IoT, specifically dependable wireless communication and localization using Ultra-Wide-Band technology, secure execution of real-time software, protocol testing and verification, and dependable networked control. We also present the TruckLab testbed, where our research results can be integrated and validated in a platooning use case. In this testbed, model trucks are automatically controlled to follow a lead truck.

Connectivity ◽  
2020 ◽  
Vol 148 (6) ◽  
Author(s):  
S. A. Zhezhkun ◽  
◽  
L. B. Veksler ◽  
S. M. Brezitsʹkyy ◽  
B. O. Tarasyuk

This article focuses on the analysis of promising technologies for long-range traffic transmission for the implementation of the Internet of Things. The result of the review of technical features of technologies, their advantages and disadvantages is given. A comparative analysis was performed. An analysis is made that in the future heterogeneous structures based on the integration of many used radio technologies will play a crucial role in the implementation of fifth generation networks and systems. The Internet of Things (IoT) is heavily affecting our daily lives in many domains, ranging from tiny wearable devices to large industrial systems. Consequently, a wide variety of IoT applications have been developed and deployed using different IoT frameworks. An IoT framework is a set of guiding rules, protocols, and standards which simplify the implementation of IoT applications. The success of these applications mainly depends on the ecosystem characteristics of the IoT framework, with the emphasis on the security mechanisms employed in it, where issues related to security and privacy are pivotal. In this paper, we survey the security of the main IoT frameworks, a total of 8 frameworks are considered. For each framework, we clarify the proposed architecture, the essentials of developing third-party smart apps, the compatible hardware, and the security features. Comparing security architectures shows that the same standards used for securing communications, whereas different methodologies followed for providing other security properties.


Author(s):  
Paul Fremantle ◽  
Philip Scott

The rapid growth of small Internet connected devices, known as the Internet of Things (IoT), is creating a new set of challenges to create secure, private infrastructures. This paper reviews the current literature on the challenges and approaches to security and privacy in the Internet of Things, with a strong focus on how these aspects are handled in IoT middleware. We focus on IoT middleware because many systems are built from existing middleware and these inherit the underlying security properties of the middleware framework. The paper is composed of three main sections. Firstly, we propose a matrix of security and privacy threats for IoT. This matrix is used as the basis of a widespread literature review aimed at identifying requirements on IoT platforms and middleware. Secondly, we present a structured literature review of the available middleware and how security is handled in these middleware approaches. We utilise the requirements from the first phase to evaluate. Finally, we draw a set of conclusions and identify further work in this area.


2017 ◽  
Author(s):  
Paul Fremantle ◽  
Philip Scott

The rapid growth of small Internet connected devices, known as the Internet of Things (IoT), is creating a new set of challenges to create secure, private infrastructures. This paper reviews the current literature on the challenges and approaches to security and privacy in the Internet of Things, with a strong focus on how these aspects are handled in IoT middleware. We focus on IoT middleware because many systems are built from existing middleware and these inherit the underlying security properties of the middleware framework. The paper is composed of three main sections. Firstly, we propose a matrix of security and privacy threats for IoT. This matrix is used as the basis of a widespread literature review aimed at identifying requirements on IoT platforms and middleware. Secondly, we present a structured literature review of the available middleware and how security is handled in these middleware approaches. We utilise the requirements from the first phase to evaluate. Finally, we draw a set of conclusions and identify further work in this area.


2021 ◽  
Author(s):  
Jehad Ali ◽  
Byeong-hee Roh

Separating data and control planes by Software-Defined Networking (SDN) not only handles networks centrally and smartly. However, through implementing innovative protocols by centralized controllers, it also contributes flexibility to computer networks. The Internet-of-Things (IoT) and the implementation of 5G have increased the number of heterogeneous connected devices, creating a huge amount of data. Hence, the incorporation of Artificial Intelligence (AI) and Machine Learning is significant. Thanks to SDN controllers, which are programmable and versatile enough to incorporate machine learning algorithms to handle the underlying networks while keeping the network abstracted from controller applications. In this chapter, a software-defined networking management system powered by AI (SDNMS-PAI) is proposed for end-to-end (E2E) heterogeneous networks. By applying artificial intelligence to the controller, we will demonstrate this regarding E2E resource management. SDNMS-PAI provides an architecture with a global view of the underlying network and manages the E2E heterogeneous networks with AI learning.


Author(s):  
Jathan Sadowski ◽  
Frank Pasquale

There is a certain allure to the idea that cities allow a person to both feel at home and like a stranger in the same place. That one can know the streets and shops, avenues and alleys, while also going days without being recognized. But as elites fill cities with “smart” technologies — turning them into platforms for the “Internet of Things” (IoT): sensors and computation embedded within physical objects that then connect, communicate, and/or transmit information with or between each other through the Internet — there is little escape from a seamless web of surveillance and power. This paper will outline a social theory of the “smart city” by developing our Deleuzian concept of the “spectrum of control.” We present two illustrative examples: biometric surveillance as a form of monitoring, and automated policing as a particularly brutal and exacting form of manipulation. We conclude by offering normative guidelines for governance of the pervasive surveillance and control mechanisms that constitute an emerging critical infrastructure of the “smart city.”


2020 ◽  
Author(s):  
Tanweer Alam ◽  
Baha Rababah ◽  
Rasit Eskicioglu

Increasing the implication of growing data generated by the Internet of Things (IoT) brings the focus toward extracting knowledge from sensors’ raw data. In the current cloud computing architecture, all the IoT raw data is transmitted to the cloud for processing, storage, and control things. Nevertheless, the scenario of sending all raw data to the cloud is inefficient as it wastes the bandwidth and increases the network load. This problem can be solved by Providing IoT Gateway at the edge layer with the required intelligence to gain the Knowledge from raw data to decide to actuate or offload complicated tasks to the cloud. This collaboration between cloud and edge called distributed intelligence. This work highlights the distributed intelligence concept in IoT. It presents a deep investigation of distributed intelligence between cloud and edge layers under IoT architecture, with an emphasis on its vision, applications, and research challenges. This work aims to bring the attention of IoT specialists to distributed intelligence and its role to deduce current IoT challenges such as availability, mobility, energy efficiency, security, scalability, interoperability, and reliability.


Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 27
Author(s):  
Franco Cicirelli ◽  
Antonio Guerrieri ◽  
Andrea Vinci

The Internet of Things (IoT) and related technologies are promising in terms of realizing pervasive and smart applications, which, in turn, have the potential to improve the quality of life of people living in a connected world [...]


Author(s):  
М.А. Держо ◽  
М.М. Лаврентьев ◽  
А.В. Шафаренко

В данной работе обсуждаются фундаментальные вопросы разработки программ магистратуры в области Интернета вещей (Internet of Things — IoT). Мы кратко сравниваем предложения Сколтеха и Стэнфорда и утверждаем, что наиболее гибкое решение достигается посредством вводного блока и четырех параллельных потоков учебных курсов: обработка сигналов и управление, обучение машин и искусственный интеллект (ИИ), программирование и схемотехника платформ с применением микроконтроллеров, и, наконец, сети и кибербезопасность. Вводный блок предполагается оснастить достаточным количеством предметов по выбору, чтобы поступающие выпускники бакалавриата из областей прикладной математики, информационных технологий и электроники/телекоммуникаций могли приобрести необходимые знания для освоения потоковых курсов. Мы утверждаем, что еще одним необходимым отличием программы IoT должен явиться междисциплинарный групповой дипломный проект значительного объема, также основанный на потоковых курсах. This paper discusses the fundamentals of postgraduate curriculum development for the area of the Internet of Things (IoT). We provide a brief contrasting analysis of Skoltech and Stanford Masters programs and argue that the most flexible way forward is via the introduction of a leveling-off, elective introductory stage, and four parallel course streams: signal processing and control; Artificial Intelligence (AI), and machine learning; microcontroller systems design; and networks and cyber security. The leveling-off stage is meant to provide sufficient electives for graduates of applied math, Information Technologies (IT), or electronics/telecom degrees to learn the necessary fundamentals for the stream modules. We argue that another distinguishing feature of an IoT masters program is a large project drawing on the stream modules and requiring a multidisciplinary, team development effort.


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