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  • 1.
    Carlsson, Anders
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
    Kuzminykh, Ievgeniia
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
    Gustavsson, Rune
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
    Virtual Security Labs Supporting Distance Education in ReSeLa Framework2019In: Advances in Intelligent Systems and Computing / [ed] Auer M.E.,Tsiatsos T., Springer Verlag , 2019, Vol. 917, p. 577-587Conference paper (Refereed)
    Abstract [en]

    To meet the high demand of educating the next generation of MSc students in Cyber security, we propose a well-composed curriculum and a configurable cloud based learning support environment ReSeLa. The proposed system is a result of the EU TEMPUS project ENGENSEC and has been extensively validated and tested. © 2019, Springer Nature Switzerland AG.

  • 2.
    Kuzminykh, Ievgeniia
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Avatar Conception for “Thing” Representation in Internet of Things2018In: Proccedings of SNCNW 2018, Karlskrona, May 31 - June 1, 2018, 2018, p. 46-49Conference paper (Refereed)
    Abstract [en]

    The complexity of ensuring IoT security is that the system is heterogeneous, consists of many assets on each of the architecture layer. Many experts in IoT security focus on threat analysis  and risk assessments to estimate the impact if a security incident or a breach occurs.

    In order to provide the general security requirements for the IoT system using threat risk modelling, the first thing to do is to identify the main security stakeholders, security assets, possible attacks, and, finally, threats for the IoT system. Using this general IoT threat model as a basis you can create a specific set of security objectives for a specific IoT application domain.

    In this paper we will try to highlight the assets that necessary for further analysis of the treat model for Internet of Things. We will also specify the stakeholders who are the connecting link between IoT devices, services and customers, as well as link between transfer and displaying the client commands onto smart things.

    For describing the model of component interaction in IoT system we will use the avatar-oriented approach since it allows us to merge objects into a system of objects. IoT Service has a more complex structure than a single entity. The application can use several services to display all information to end user, can aggregate data from several devices.

    To manipulate data objects the avatar representation approach is most appropriate, then you can easily connect or disconnect microservices, data from things, visual representation of data.

  • 3.
    Kuzminykh, Ievgeniia
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Carlsson, Anders
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Analysis of Assets for Threat Risk Model in Avatar-Oriented IoT Architecture2018In: Internet of Things, Smart Spaces, and Next Generation Networks and Systems. NEW2AN 2018, ruSMART 2018. Lecture Notes in Computer Science, vol 11118 / [ed] Galinina O., Andreev S., Balandin S., Koucheryavy Y. (eds), Springer, 2018, Vol. 11118, p. 52-63Conference paper (Refereed)
    Abstract [en]

    This paper represents new functional architecture for the Internet of Things systems that use an avatar concept in displaying interaction between components of the architecture. Object-oriented representation of “thing” in the avatar concept allows simplify building and deployment of IoT systems over the web network and bind “things” to such application protocols as HTTP, CoAP, and WebSockets mechanism. The assets and stakeholders for ensuring security in IoT were specified. These assets are needed to isolate the risks associated with each of assets of IoT system. Example of Thing Instance’s description and its functionality using JSON format is shown also in the paper.

  • 4.
    Kuzminykh, Ievgeniia
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Carlsson, Anders
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Franksson, Robin
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Liljegren, Alexander
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Measuring a LoRa Network: Performance, Possibilities and Limitations2018In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) / [ed] Galinina O., Andreev S., Balandin S., Koucheryavy Y., Springer, 2018, Vol. 11118, p. 116-128Conference paper (Refereed)
    Abstract [en]

    Low power wide area (LPWA) technologies becomes popular for IoT use cases because LPWA is enable the broad range communications and allows to transmit small amounts of information in a long distance. Among LPWA technologies there are LTE-M, SigFox, LoRa, Symphony Link, Ingenu RPMA, Weightless, and NB-IoT. Currently all these technologies suffer from lack of documentation about deployment recommendation, have non-investigated limitations that can affect implementations and products using such technologies. This paper is focused on the testing of LPWAN LoRa technology to learn how a LoRa network gets affected by different environmental attributes such as distance, height and surrounding area by measuring the signal strength, signal to noise ratio and any resulting packet loss. The series of experiments for various use cases are conducted using a fully deployed LoRa network made up of a gateway and sensor available through the public network. The results will show the LoRa network limitation for such use cases as forest, city, open space. These results allow to give the recommendation for companies during early analysis and design stages of network life circle, and help to choose properly technology for deployment an IoT application.

  • 5.
    Popov, Oleksii Yu
    et al.
    Taras Shevchenko National University of Kyiv, UKR.
    Kuzminykh, Ievgeniia
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Analysis of methods for reducing topology in wireless sensor networks2018In: 14th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering, TCSET 2018 - Proceedings, Institute of Electrical and Electronics Engineers Inc. , 2018, p. 529-532Conference paper (Refereed)
    Abstract [en]

    This paper describes the phases of deployment of wireless sensor networks, and more attention is given to the phase of reducing topology and to methods by which this can be achieved. A comparison of hierarchy-based topology construction algorithms is presented. Algorithms use a simple, distributed and energy efficient topology mechanism that discovers a optimal connected dominant set (CDS) to disable unnecessary nodes, providing important wireless sensor network characteristics such as full coverage and connectivity. © 2018 IEEE.

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