Smart Homes (SHs), as subsets of the Internet of Things (IoT), make use of Machine Learning and Arti cial Intelligence tools to provide technology-enabled solutions which assist their occupants and users with their Activities of Daily Living (ADL). Some SH provide always-present, health management support and care services. Having these services provided at home enables SH occupants such as the elderly and disabled to continue to live in their own homes and localities thus aiding Ageing In Place goals and eliminating the need for them to be relocated in order to be able to continue receiving the same support and services. Introducing and interconnecting smart, autonomous systems in homes to enable these service provisions and Assistance Technologies (AT) requires that certain interfaces in, and connections to, SH are exposed to the Internet, among other public-facing networks. This introduces the potential for cyber-physical attacks to be perpetrated through, from and against SH. Apart from the actual threats posed by these attacks to SH occupants and their homes, the potential that these attacks might occur can adversely a ect the adoption or uptake of SH solutions. This thesis identi es key attributes of the di erent elements (things or nodes and rooms or zones) in SHs and the relationships that exist between these elements. These relationships can be used to build SH security baselines for SHs such that any deviations from this baseline is described as anomalous. The thesis demonstrates the application of these relationships to Anomaly Detection (AD) through the analysis of several hypothetical scenarios and the decisions reached about whether they are normal or anomalous. This thesis also proposes an Internet of Things Digital Forensics Framework (IDFF), a Forensics Edge Management System (FEMS), a FEMS Decision-Making Algorithm (FDMA) and an IoT Incident Response plan. These tools can be combined to provide proactive (autonomous and human-led) Digital Forensics services within cyber-physical environments like the Smart Home.

Background. With the rise of Internet of Things and Internet connected devices many things become convenient and efficient but these products also carry risks. Even though a lot of people own devices like this not so many think of the consequences if these devices aren't secure. Objectives. Given this our thesis aims to discover the implications of vulnerable devices and also at what rate there are insecure, unpatched devices compared to the patched, secure counterpart. Methods. The approach implemented uses Shodan to find these devices on the internet and also to find version information about each device. After the devices are found the objective is to calculate a CVSS score on the vulnerabilities and the exploit that can abuse the vulnerability, if there exists any. Results. What we found was that 71.85% of a smart home server brand was running an insecure version. As to the consequences of having an insecure device, it can be severe.Conclusions. We found that, for instance, an attacker can without much difficulty shut off alarms in your smart home and then proceed to break into your house. Keywords: Vulnerability; Shodan; Internet of Things (IoT); Patching

The Internet-of-Things (IoT) is a network of interconnected devices with sensing, monitoring and processing functionalities that work in a cooperative way to offer services. Smart buildings, self-driving cars, house monitoring and management, city electricity and pollution monitoring are some examples where IoT systems have been already deployed. Amongst different kinds of devices in IoT, cameras play a vital role, since they can capture rich and resourceful content. However, since multiple IoT devices share the same gateway, the data that is produced from high definition cameras congest the network and deplete the available computational resources resulting in Quality-of-Service degradation corresponding to the visual content. In this thesis, we present an edge-based resource management framework for serving video processing applications in an Internet-of-Things (IoT) environment. In order to support the computational demands of latency-sensitive video applications and utilize effectively the available network resources, we employ edge-based resource management policy. We evaluate our proposed framework with a face recognition use case.

The Internet of Things (IoT) technology is undergoing expansion into different aspects of our life, changing the way businesses operate and bringing in efficiency and reliability of digital controls on various levels. Processing large amount of data from connected sensor networks becomes a challenging task. Specific part of it related to fleet management requires processing of the data on boards of vehicles equipped with multiple electronic devices and sensors for maintenance and operation of such vehicles. Herewith the efficiency of various configurations of employing Kalman filter algorithm for on-the-fly pre-processing of the sensory network originated data streams in IoT systems is investigated. Contextual grouping of the data streams for pre-processing by specialized Kalman filter units is found to be able to satisfy the logistics of IoT system operations. It is demonstrated that interconnection of the elementary Kalman filters into an organized network, the compositional Kalman filter, allows to take advantage of the redundancy of data streams to accomplish IoT pre-processing of the raw data. This includes intermittent data imputation, missing data replacement, lost data recovery, as well as error events detection and correction. Architectures are proposed and tested for the interaction of elementary Kalman filters in detection of GPS outage events and their compensation via data replacement procedure, as well as GPS offset occurrence detection and its compensation via data correction routine. Demonstrated is the efficiency of the suggested compositional designs of elementary Kalman filter networks for the purpose of data pre-processing in IoT systems.

One application of the Internet of Things that is currently developed is the collection of data from district heating systems. This development leads to the problem of how the collected data should be used to operate the systems in a manner that reduces the dependency on fossil fuels. This thesis proposes a characterization of this problem into visualization tasks and requirements, as well as a visualization application, based on the tool Power BI, for gaining insight into how to operate a district heating system. The tasks and requirements were elicited during collaborative meetings and prototyping together with district heating experts. The perceived effectiveness of the visualization application was validated with a usability evaluation, including the usability metric for user experience questionnaire, with four district heating experts. The perceived efficiency was, however, found to be lacking compared to the other usability aspects. A redesign of one of the Power BI components, which according to the evaluation should improve the application, is also suggested.

AF’s office in Karlstad currently offer consultation regarding Internet of Things but are looking to expand into development of services. They have requested that an end-to-end solution is developed in order to demonstrate the technology to potential clients. This thesis describes the work performed to realize an end-to-end solution for connecting sensors and actuators to the cloud. It also describes the problems experienced while working with Microsofts platform for cloud services, Azure. / Företaget ÅFs Karlstadkontor bistår i dagsläget med konsultering gällande Internet of Things men vill även börja utveckla och sälja tjänster. För att kunna demonstrera teknologin för potentiella kunder har de begärt att en end-to-end-lösning utvecklas. Den här uppsatsen beskriver det arbete som har utförts för att realisera en end-to-end-lösning för att koppla sensorer och ställdon till molnet. Den redogör även för de svårigheter som upplevdes gällande Microsofts plattform för molntjänster, Azure.

With the development of the Internet-of-Things, more and more IoT platforms come up with different structures and characteristics. Making balance of their advantages and disadvantages, we should choose the suitable platform in differ- ent scenarios. For this project, I make comparison of a cloud-based centralized platform, Microsoft Azure IoT hub and a fully distributed platform, Sensi- bleThings. Quantitative comparison is made for performance by 2 scenarios, messages sending speed adds up, devices lie in different location. General com- parison is made for security, utilization and the storage. Finally I draw the con- clusion that SensibleThings performs more stable when a lot of messages push- es to the platform. Microsoft Azure has better geographic expansion. For gener- al comparison, Microsoft Azure IoT hub has better security. The requirement of local device for Microsoft Azure IoT hub is lower than SensibleThings. The SensibleThings are open source and free while Microsoft Azure follow the con- cept “pay as you go” with many throttling limitations for different editions. Microsoft is more user-friendly.

TCP/IP protocol gradually exposes many shortcomings such as poor scalability and mobility. Content-Centric Networking is a new architecture which cares about the content itself rather than its source. Therefore, this paper proposes a novel IoV architecture which based on Content-Centric Networking and tests its transmission interference time, transmission delay, and throughout in network layer. The experimental results show that the novel architecture is superior to the current IoV in the communication performance.

Electronic Product Code (EPC) refers to a numbering standard developed to uniquely identify physical objects, loads, locations, assets and other entities which are to be tracked or otherwise identified. The tracking technology consists of assigning Radio Frequency Identification (RFID) tags, holding universally unique EPC codes, to the entities to be identified. While the EPC-RFID technology is used to identify and capture data about the physical objects to be tracked in a supply chain, the EPCglobal Network ensures the exchange of the captured data between supply chain stakeholders. Such a real-time data exchange increases visibility and efficiency throughout the supply chain, and thus it increases both company profitability and customer satisfaction. The EPCglobal Network can be regarded as the backbone for the future Internet of Things (IoT). We focus our work in this thesis on Discovery Services (DS); a suite of network lookup services enabling users to retrieve all relevant information sources with regards to a given EPC. They can be viewed as search engines for the future business infrastructure deployed in the IoT. Motivated by the unprecedented and incessantly growing amount of EPC data, the expected epidemic growth in the solicitation frequency of the lookup service, and also the foreseen exceptionally large flow of highly sensitive EPC information, we focus on proposing solutions to problems pertaining to two main challenges; architecture design of Discovery Services and their security. On the architecture design level, we propose novel DS architectures with focus directed towards meeting four major requirements; network scalability, query responsiveness, service extensibility and acceptance. On the security level, we propose probabilistic security schemes aiming at securing even further Discovery Services in the IoT in general, and in the EPCglobal network in particular.

The aim of this masters thesis is to identify, in which phase of adoption of Internet of Things (IoT) application areas of concept Smart City are nowadays Czech regional cities, what is their outlook to 2025 and also identify in which dimensions of concept Smart city, supported by IoT technologies, perceive Czech regional cities the greatest potential. Based on information obtained from the studied materials, the concept of Internet of Things (IoT) is described, along with a detailed description of one of its application area, namely Smart City. This area is further divided into specific dimensions, that cover specific application areas which can, through internet technology, support things in a special way. With these insights, the questionnaire (built on identified IoT application areas of smart city) was developed. Thesis should be beneficial for all towns in the Czech Republic, because it provides a comprehensive view of individual IoT application areas of concept Smart City including information on which of these IoT application areas are currently focusing regional cities, and on which they want to focus to the future. On the other hand, the survey results could also be beneficial for commercial entities, which focus on IoT implementation in cities. These entities will be able to recognise which IoT products are currently best for cities.