Malmö University Publications
Change search
Refine search result
1 - 7 of 7
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Andersson, Robin
    Malmö University, Faculty of Technology and Society (TS).
    Combining Anomaly- and Signaturebased Algorithms for IntrusionDetection in CAN-bus: A suggested approach for building precise and adaptiveintrusion detection systems to controller area networks2021Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    With the digitalization and the ever more computerization of personal vehicles, new attack surfaces are introduced, challenging the security of the in-vehicle network. There is never such a thing as fully securing any computer system, nor learning all the methods of attack in order to prevent a break-in into a system. Instead, with sophisticated methods, we can focus on detecting and preventing attacks from being performed inside a system. The current state of the art of such methods, named intrusion detection systems (IDS), is divided into two main approaches. One approach makes its models very confident of detecting malicious activity, however only on activities that has been previously learned by this model. The second approach is very good at constructing models for detecting any type of malicious activity, even if never studied by the model before, but with less confidence. In this thesis, a new approach is suggested with a redesigned architecture for an intrusion detection system called Multi-mixed IDS. Where we take a middle ground between the two standardized approaches, trying to find a combination of both sides strengths and eliminating its weaknesses. This thesis aims to deliver a proof of concept for a new approach in the current state of the art in the CAN-bus security research field. This thesis also brings up some background knowledge about CAN and intrusion detection systems, discussing their strengths and weaknesses in further detail. Additionally, a brief overview from a handpick of research contributions from the field are discussed. Further, a simple architecture is suggested, three individual detection models are trained and combined to be tested against a CAN-bus dataset. Finally, the results are examined and evaluated. The results from the suggested approach shows somewhat poor results compared to other suggested algorithms within the field. However, it also shows some good potential, if better decision methods between the individual algorithms that constructs the model can be found. 

    Download full text (pdf)
    fulltext
  • 2.
    Ashouri, Majid
    et al.
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT). Malmö University, Internet of Things and People (IOTAP).
    Davidsson, Paul
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT). Malmö University, Internet of Things and People (IOTAP).
    Spalazzese, Romina
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT). Malmö University, Internet of Things and People (IOTAP).
    Quality attributes in edge computing for the Internet of Things: A systematic mapping study2021In: Internet of Things: Engineering Cyber Physical Human Systems, E-ISSN 2542-6605, Vol. 13, article id 100346Article in journal (Refereed)
    Abstract [en]

    Many Internet of Things (IoT) systems generate a massive amount of data needing to be processed and stored efficiently. Cloud computing solutions are often used to handle these tasks. However, the increasing availability of computational resources close to the edge has prompted the idea of using these for distributed computing and storage. Edge computing may help to improve IoT systems regarding important quality attributes like latency, energy consumption, privacy, and bandwidth utilization. However, deciding where to deploy the various application components is not a straightforward task. This is largely due to the trade-offs between the quality attributes relevant for the application. We have performed a systematic mapping study of 98 articles to investigate which quality attributes have been used in the literature for assessing IoT systems using edge computing. The analysis shows that time behavior and resource utilization are the most frequently used quality attributes; further, response time, turnaround time, and energy consumption are the most used metrics for quantifying these quality attributes. Moreover, simulation is the main tool used for the assessments, and the studied trade-offs are mainly between only two qualities. Finally, we identified a number of research gaps that need further study.

    Download full text (pdf)
    fulltext
  • 3.
    Ashouri, Majid
    et al.
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
    Lorig, Fabian
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
    Davidsson, Paul
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
    Spalazzese, Romina
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
    Edge Computing Simulators for IoT System Design: An Analysis of Qualities and Metrics2019In: Future Internet, E-ISSN 1999-5903, Vol. 11, no 11, p. 235-246Article in journal (Refereed)
    Abstract [en]

    The deployment of Internet of Things (IoT) applications is complex since many quality characteristics should be taken into account, for example, performance, reliability, and security. In this study, we investigate to what extent the current edge computing simulators support the analysis of qualities that are relevant to IoT architects who are designing an IoT system. We first identify the quality characteristics and metrics that can be evaluated through simulation. Then, we study the available simulators in order to assess which of the identified qualities they support. The results show that while several simulation tools for edge computing have been proposed, they focus on a few qualities, such as time behavior and resource utilization. Most of the identified qualities are not considered and we suggest future directions for further investigation to provide appropriate support for IoT architects.

    Download full text (pdf)
    fulltext
  • 4.
    Mörk, Linnéa
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
    Exploring true random number generators Build on commercial-off-the-shelve Components2023Independent thesis Basic level (university diploma), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Generating random numbers can be accomplished through various methods, with the primary distinction lying between pseudo-random number generators (PRNGs), which are commonly used for applications that require a large amount of random data, and true random number generators (TRNGs), which are commonly used for applications that need security and unpredictability. This thesis explores the feasibility of harnessing frequency variations in the electrical grid as a source of entropy for a TRNG. By employing an iterative approach, the study has substantiated the likelihood that frequency fluctuations can serve as a reliable source of ran-domness for a TRNG. This assertion is supported by statistical testing using the comprehensive RNG testing suite known as DieHarder, where the final implementation of the TRNG yielded favourable outcomes. Nevertheless, it is worth noting that the artefact exhibited weaker resultson three specific tests within the suite, which can likely be attributed to a limited amount of generated data. Despite these limitations, the findings are undeniably promising, and futurere search endeavours should focus primarily on enhancing the generation speed of the TRNG. By doing so, it is anticipated that improved performance on the DieHarder suite and similar RNG testing suites can be achieved.

    Download full text (pdf)
    fulltext
  • 5.
    Nowell, Thomas
    et al.
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
    Kollin, Viktor
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
    Battery Powered Adaptive Grow Light System Aiming at Minimizing Cost and Environmental Impact from Electricity Use2022Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    With increasing popularity of indoor farming, more and more home growers are faced

    with sub-optimal lighting conditions in northern countries or poorly lit windows.

    We have designed and built a proof-of-concept system capable of reducing electricity

    cost and CO2 footprint of the electricity used for consumer grade grow lights without

    adversely impacting the grow cycle of the plant. Our system provides optimal grow light

    conditions for a given plant while using forecasts and live grid data from the ENTSO-E

    transparency platform to automatically use or store electricity during low-cost hours and

    avoid using grid electricity during high-cost hours, but can also be configured to prioritize

    electricity use when the available grid power’s carbon intensity is low.

    The system, consisting of a server and an embedded control unit, was designed and

    implemented according to Nunamaker and Chen’s five-step iterative systems development

    research method and later evaluated by simulating the system for 14 days using real world

    sunlight and grid data.

    The results of the simulation show a significant reduction in both spending and carbon

    emissions related to electricity use, with figures of 73% and 28%, respectively. However,

    when accounting for life-cycle cost and emissions from the battery, the prototype in its

    current configuration is neither profitable nor a net positive for the environment. With

    changes to battery type and taking advantage of economies of scale, a future version

    could be economically viable, but to be environmentally sustainable, further advances in

    eco-friendly battery production are needed.

    Download full text (pdf)
    fulltext
  • 6.
    Ouhaichi, Hamza
    et al.
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
    Olsson, Helena Holmström
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
    Bosch, Jan
    Chalmers University of TechnologyGothenburgSweden.
    Dynamic Data Management for Machine Learning in Embedded Systems: A Case Study2019In: Software Business: 10th International Conference, ICSOB 2019, Jyväskylä, Finland, November 18–20, 2019, Proceedings / [ed] Sami Hyrynsalmi; Mari Suoranta; Anh Nguyen-Duc; Pasi Tyrväinen; Pekka Abrahamsson, Springer, 2019Conference paper (Refereed)
    Abstract [en]

    Dynamic data and continuously evolving sets of records are essential for a wide variety of today’s data management applications. Such applications range from large, social, content-driven Internet applications, to highly focused data processing verticals like data intensive science, telecommunications and intelligence applications. However, the dynamic and multimodal nature of data makes it challenging to transform it into machine-readable and machine-interpretable forms. In this paper, we report on an action research study that we conducted in collaboration with a multinational company in the embedded systems domain. In our study, and in the context of a real-world industrial application of dynamic data management, we provide insights to data science community and research to guide discussions and future research into dynamic data management in embedded systems. Our study identifies the key challenges in the phases of data collection, data storage and data cleaning that can significantly impact the overall performance of the system.

  • 7.
    Rumar, Tove
    et al.
    Malmö University, Faculty of Technology and Society (TS).
    Juelsson Larsen, Ludvig
    Malmö University, Faculty of Technology and Society (TS).
    Towards an improvement of BLE Direction Finding accuracyusing Dead Reckoning with inertial sensors2021Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Whilst GPS positioning has been a well used technology for many years in outdoor environments,a ubiquitous solution for indoor positioning is yet to be found, as GPS positioning is unreliableindoors. This thesis focuses on the combination of Inertial Sensor Dead Reckoning and positionsobtained from the Bluetooth Low Energy (BLE) Direction Finding technique. The main objectiveis to reduce the error rate and size of a BLE Direction Finding system. The positioned object is aMicro-Electrical Mechanical System (MEMS) with an accelerometer and a gyroscope, placed on atrolley. The accelerometer and gyroscope are used to obtain an orientation, velocity vector, andin turn a position which is combined with the BLE Direction Finding position. To further reducethe error rate of the system, a Stationary Detection functionality is implemented. Because of thetrolley movement pattern causing noise in the sensor signals, and the limited sensor setup, it is notpossible to increase the accuracy of the system using the proposed method. However, the StationaryDetection is able to correctly determine a stationary state and thus decreasing error rate and powerconsumption.

    Download full text (pdf)
    fulltext
1 - 7 of 7
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf