Dynamic Adaptive Streaming over HTTP (DASH) is a standard for delivering video in segments and adapting each segment’s bitrate (quality), to adjust to changing and limited network bandwidth. We study segment prefetching, informed by machine learning predictions of bitrates of client segment requests, implemented at the network edge. We formulate this client segment request prediction problem as a supervised learning problem of predicting the bitrate of a client’s next segment request, in order to prefetch it at the mobile edge, with the objective of jointly improving the video streaming experience for the users and network bandwidth utilization for the service provider. The results of extensive evaluations showed a segment request prediction accuracy of close to 90% and reduced video segment access delay with a cache hit ratio of 58%, and reduced transport network load by lowering the backhaul link utilization by 60.91%.

The purpose of this study was to address the challenge of teaching sustainable development to computer engineering students. Part of the problem is that they perceive the topic as irrelevant for their future profession. The chosen approach was to introduce a project element into a course on sustainable development where the students developed applications for sustainable mobility together with the local public transport authority, an academic institution and a multinational telecom company. Thus the course project was organized to facilitate entrepreneurial experiences, as defined in the EU's EntreComp model, as well as relating theoretical concepts to experiences in a concrete context. The students were then asked to analyze and reflect upon their design choices and approaches in relation to sustainable development and ethical considerations. The findings conclude that the course changes improved the overall student satisfaction while succeeding in anchoring sustainable development in a context the students could relate to. The collaboration was also perceived as fruitful by the external stakeholders who encouraged the students to stay in touch for their bachelor theses and internships. The theoretical implication is a first attempt in integrating sustainable development education with entrepreneurial experiences while the practical implication is a description of how the integration can be realized. The contribution is therefor of value for both educational researchers by opening novel research opportunities and teachers by describing new possibilities for sustainable development education.

In order to facilitate deterministic behavior; industrial real-time communication stacks need another design than non-real-time communication stacks typically found in e.g., Internet of Things and Cloud solutions. We propose a flexible stack design that enable code reuse between testbeds and simulators, as well as how stack layers are driven and prioritized. The design can be generalized and used for non-real-time bare-metal solutions like battery powered Internet of Things. Our approach aims at extending the use of simulation during development of industrial systems in order to find logical errors and wrong assumptions earlier in the development. Conducted and evaluated experiments show that the proposed solutions are able to extend the use of simulation during development of real-time communication software. This is achieved by reusing the same code on an industrial testbed and in a discrete event simulator. In addition, the experiments show that the stack design is generalizable and enable reuse with other non-real-time embedded systems. The contribution consists of a set of building blocks for real-time systems that enable control over the system timing when executing on a simulation host while reusing the source code from an industrial testbed. Overall, this will improve the engineering situation, with respect to code reuse, flexibility and debugging. © 2023 The Author(s)

Internet of Things or IoT deployments are becoming more and more common. The list of use-cases for IoT is getting longer and longer, but some examples are smart home appliances and wireless sensor networks. When IoT devices are deployed and used over an extended time, it is not guaranteed that one owner will control the IoT devices over their entire lifetime. If the ownership of an IoT system shall be transferred between two entities, secure ownership transfer arises. In this paper we propose a protocol that enables secure ownership transfer of constrained IoT devices. The protocol is resource-efficient and only rely on symmetric cryptography for the IoT devices. The protocol has been rigorously analyzed to prove the state security requirements. The security analysis has been done partially using formal protocol verification tools, particularly Tamarin Prover. To show our proposed protocol’s resource efficiency, we have done a proof of concept implementation. This implementation, for constrained IoT devices, has been used to verify the efficiency of the protocol. 

The Constrained Application Protocol (CoAP) is a major application-layer protocol for the Internet of Things (IoT). The recently standardized security protocol Object Security for Constrained RESTful Environments (OSCORE) efficiently provides end-to-end security of CoAP messages at the application layer, also in the presence of untrusted intermediaries. At the same time, CoAP supports one-to-many communication, targeting use cases such as smart lighting and building automation, firmware update, or emergency broadcast. Securing group communication for CoAP has additional challenges. It can be done using the novel Group Object Security for Constrained RESTful Environments (Group OSCORE) security protocol, which fulfills the same security requirements of OSCORE in group communication environments. While evaluations of OSCORE are available, no studies exist on the performance of Group OSCORE on resource-constrained IoT devices.This article presents the results of our extensive performance evaluation of Group OSCORE over two popular constrained IoT platforms, namely Zolertia Zoul and TI Simplelink. We have implemented Group OSCORE for the Contiki-NG operating system and made our implementation available as open source software. We compared Group OSCORE against unprotected CoAP as well as OSCORE. To the best of our knowledge, this is the first comprehensive and experimental evaluation of Group OSCORE over real constrained IoT devices. © 2022 Copyright held by the owner/author(s).

Traffic safety applications and other communication systems for vehicles together with data collection sensors have the potential to improve road safety. For this to be viable however, it is important that the data collection and communication can be trusted so that erroneous or malicious data does not impact the use cases of the applications. This paper studies current and upcoming solutions to such problems and how they can be modified and applied to meet both technical requirements as well as the needs of relevant stakeholders. The paper defines the TruVeLedger framework using technology from the fields of distributed ledgers and vehicular ad hoc networks (VANETs) to create a trusted platform. The paper considers the viability of different approaches to such a platform as well as defining a verifiable trusted communication protocol for vehicular networks. 

With their inherent convenience factor, Internet of Things (IoT) devices have exploded in numbers during the last decade, but at the cost of security. Machine learning (ML) based intrusion detection systems (IDS) are increasingly proving necessary tools for attack detection, but requirements such as extensive data collection and model training make these systems computationally heavy for resource-limited IoT hardware. This paper’s main contribution to the cyber security research field is a demonstration of how a dynamic user-level scheduler can improve the performance of IDS suited for lightweight and data-driven ML algorithms towards IoT. The dynamic user-level scheduler allows for more advanced computations, not intended to be executed on resource-limited IoT units, by enabling parallel model retraining locally on the IoT device without halting the IDS. It eliminates the need for any cloud resources as computations are kept locally at the edge. The experiments showed that the dynamic user-level scheduler provides several advantages compared to a previously developed baseline system. Mainly by substantially increasing the system’s throughput, which reduces the time until attacks are detected, as well as dynamically allocating resources based on attack suspicion.

The IoT comprises billions of intelligent devices that interact, gather, and share data via sensors and actuators. The Industrial IoT (IIoT), specifically used in industry and production, is used in automation and rapid production of goods based on machine learning techniques. Similarly, Cyber-Physical System (CPS) plays a vital role in the next-generation industry. The CPSs are intelligent systems that interconnect the physical world through embedded systems, sensors, actuators with the cyberworld. We require a communication backbone for interconnecting and information processing, which 6G networks can fulfill. The 6G has a higher capacity and improved characteristics than previous cellular networks, accelerating the applications and deployments of 6G-based IIoT networks in industry platforms. This chapter discusses how the 6G networks can help interconnect the CPS and IIoT through smart connection, digital twinning, and immersive technology.

Car manufacturers are noticing and encouraging a trend away from individual mobility, where a vehicle is owned and driven by one or only a few other persons, and towards shared-mobility concepts. That means that many different people use and have access to the same vehicle. An attacker disguised as a regular short-time user can use the additional attack vectors (s)he gets by having physical access to tamper the vehicle's software. The software takes a continuously more crucial role in cars for autonomous driving, and manipulations can have catastrophic consequences for the persons on board. Currently, there is no mechanism available to the vehicle owner to detect such manipulations in the vehicle done by the attacker (short-time user). In this work, a novel vehicle attestation scheme called Vehicular Soft Integrity Preservation Scheme (VeSIPreS) is proposed to detect tampering in the software stack of a vehicle and guarantee the upcoming driver that the previous user has not changed the software of the vehicle. The solution consists of a software module in the vehicle and a mobile-based user application for the vehicle owner to monitor the vehicle's soft integrity. Inside the vehicle, the software module is implemented in the central gateway, which acts as the primary security component. VeSIPreS uses Trusted Platform Module (TPM) in the central gateway, which anchors trust in our proposed solution. This paper also provides a proof-of-concept implementation with a TPM, demonstrating its application and deployment feasibility and presentig a security analysis to show the security of VeSIPreS.