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  • 1.
    Arvidsson, Åke
    et al.
    Högskolan Kristianstad, Fakulteten för naturvetenskap, Avdelningen för datavetenskap. Högskolan Kristianstad, Fakulteten för naturvetenskap, Forskningsmiljön för datavetenskap (RECS).
    Ivanovich, Milosh
    Australien.
    Fitzpatrick, Paul
    Australien.
    Modelling user experience of adaptive streaming video over fixed capacity links2021Inngår i: Performance evaluation (Print), ISSN 0166-5316, E-ISSN 1872-745X, Vol. 148, s. 1-12, artikkel-id 102199Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Streaming video continues to experience unprecedented growth. This underscores the need to identify user-centric performance measures and models that will allow operators to satisfy requirements for cost-effective network dimensioning delivered with an acceptable level of user experience. This paper presents an analysis of two novel metrics in the context of fixed capacity links: (i) the average proportion of a video’s playing time during which the quality is reduced and (ii) the average proportion of videos which experience reduced quality at least once during their playing time, based on an M/M/∞ system. Our analysis is shown to hold for the more general M/G/∞ system for metric (i), but not for (ii) and simulation studies show an unexpected form of sensitivity of metric (ii) to the flow duration distribution, contrary to the norm of increasing variance causing worse performance. At typical operational loads these new metrics provide a more sensitive and information rich guide for understanding how user experience degrades, than the widely used average throughput metric does. We further show that only the combined use of this existing and our new metrics can provide a holistic perspective on overall user performance.

    Fulltekst (pdf)
    fulltext
  • 2.
    Bolton, Tom
    et al.
    Storbritannien.
    Dargahi, Tooska
    Storbritannien.
    Belguith, Sana
    Storbritannien.
    Al-Rakhami, Mabrook S.
    Saudiarabien.
    Sodhro, Ali Hassan
    Mittuniversitetet; Kina; Pakistan.
    On the security and privacy challenges of virtual assistants2021Inngår i: Sensors, E-ISSN 1424-8220, Vol. 21, nr 7, s. 1-19, artikkel-id 2312Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Since the purchase of Siri by Apple, and its release with the iPhone 4S in 2011, virtual assistants (VAs) have grown in number and popularity. The sophisticated natural language processing and speech recognition employed by VAs enables users to interact with them conversationally, almost as they would with another human. To service user voice requests, VAs transmit large amounts of data to their vendors; these data are processed and stored in the Cloud. The potential data security and privacy issues involved in this process provided the motivation to examine the current state of the art in VA research. In this study, we identify peer-reviewed literature that focuses on security and privacy concerns surrounding these assistants, including current trends in addressing how voice assistants are vulnerable to malicious attacks and worries that the VA is recording without the user’s knowledge or consent. The findings show that not only are these worries manifold, but there is a gap in the current state of the art, and no current literature reviews on the topic exist. This review sheds light on future research directions, such as providing solutions to perform voice authentication without an external device, and the compliance of VAs with privacy regulations. 

  • 3.
    Huang, Xin
    et al.
    Department of Computer Science, Institute for the Future of Computing/Oxford Martin School, University of Oxford.
    Chen, Bangdao
    Department of Computer Science, University of Oxford.
    Markham, Andrew
    Department of Computer Science, Institute for the Future of Computing/Oxford Martin School, University of Oxford.
    Wang, Qinghua
    Högskolan Kristianstad, Sektionen för hälsa och samhälle, Avdelningen för Design och datavetenskap. Department of Communications and Networking, Aalto University, Espoo.
    Zheng, Yan
    Department of Communications and Networking, Aalto University, Espoo.
    Roscoe, Andrew William
    Department of Computer Science, Institute for the Future of Computing/Oxford Martin School, University of Oxford.
    Human interactive secure key and ID exchange protocols in body sensor networks2013Inngår i: IET Information Security, ISSN 1751-8709, E-ISSN 1751-8717, Vol. 7, nr 1, s. 30-38Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    A body sensor network (BSN) is typically a wearable wireless sensor network. Security protection is critical to BSNs, since they collect sensitive personal information. Generally speaking, security protection of BSN relies on identity (ID) and key distribution protocols. Most existing protocols are designed to run in general wireless sensor networks, and are not suitable for BSNs. After carefully examining the characteristics of BSNs, the authors propose human interactive empirical channel-based security protocols, which include an elliptic curve Diffie–Hellman version of symmetric hash commitment before knowledge protocol and an elliptic curve Diffie–Hellman version of hash commitment before knowledge protocol. Using these protocols, dynamically distributing keys and IDs become possible. As opposite to present solutions, these protocols do not need any pre-deployment of keys or secrets. Therefore compromised and expired keys or IDs can be easily changed. These protocols exploit human users as temporary trusted third parties. The authors, thus, show that the human interactive channels can help them to design secure BSNs.

  • 4.
    Lakhan, Abdullah
    et al.
    Pakistan; Kina.
    Dootio, Mazhar Ali
    Pakistan.
    Groenli, Tor Morten
    Norge.
    Sodhro, Ali Hassan
    Mittuniversitetet; Kina; Pakistan.
    Khokhar, Muhammad Saddam
    Pakistan.
    Multi-layer latency aware workload assignment of E-Transport IoT applications in mobile sensors cloudlet cloud networks2021Inngår i: Electronics, E-ISSN 2079-9292, Vol. 10, nr 14, s. 1-25, artikkel-id 1719Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    These days, with the emerging developments in wireless communication technologies, such as 6G and 5G and the Internet of Things (IoT) sensors, the usage of E-Transport applications has been increasing progressively. These applications are E-Bus, E-Taxi, self-autonomous car, E-Train and E-Ambulance, and latency-sensitive workloads executed in the distributed cloud network. Nonetheless, many delays present in cloudlet-based cloud networks, such as communication delay, round-trip delay and migration during the workload in the cloudlet-based cloud network. However, the distributed execution of workloads at different computing nodes during the assignment is a challenging task. This paper proposes a novel Multi-layer Latency (e.g., communication delay, round-trip delay and migration delay) Aware Workload Assignment Strategy (MLAWAS) to allocate the workload of E-Transport applications into optimal computing nodes. MLAWAS consists of different components, such as the Q-Learning aware assignment and the Iterative method, which distribute workload in a dynamic environment where runtime changes of overloading and overheating remain controlled. The migration of workload and VM migration are also part of MLAWAS. The goal is to minimize the average response time of applications. Simulation results demonstrate that MLAWAS earns the minimum average response time as compared with the two other existing strategies.

  • 5.
    Lakhan, Abdullah
    et al.
    Mobile Technology Lab, Department of Technology, Kristiania University College, Norway.
    Li, Jin
    School of Computer Science, Beijing Jiaotong University, China.
    Groenli, Tor Morten
    Mobile Technology Lab, Department of Technology, Kristiania University College, Norway.
    Hassan Sodhro, Ali
    Högskolan Kristianstad, Fakulteten för naturvetenskap, Avdelningen för datavetenskap. Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China.
    Zardari, Nawaz Ali
    Faculty of Electrical Engineering, University Technology, Malaysia.
    Imran, Ali Shariq
    Department of Computer Science, Norwegian University of Science and Technology, Norway.
    Thinnukool, Orawit
    Research Group of Embedded Systems and Mobile Application in Health Science, College of Arts, Media and Technology, Chiang Mai University, Thailand.
    Khuwuthyakorn, Pattaraporn
    Research Group of Embedded Systems and Mobile Application in Health Science, College of Arts, Media and Technology, Chiang Mai University, Thailand.
    Dynamic application partitioning and task-scheduling secure schemes for biosensor healthcare workload in mobile edge cloud2021Inngår i: Electronics, E-ISSN 2079-9292, Vol. 10, nr 22, s. 1-30, artikkel-id 2797Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Currently, the use of biosensor-enabled mobile healthcare workflow applications in mobile edge-cloud-enabled systems is increasing progressively. These applications are heavyweight and divided between a thin client mobile device and a thick server edge cloud for execution. Application partitioning is a mechanism in which applications are divided based on resource and energy parameters. However, existing application-partitioning schemes widely ignore security aspects for healthcare applications. This study devises a dynamic application-partitioning workload task-scheduling-secure (DAPWTS) algorithm framework that consists of different schemes, such as min-cut algorithm, searching node, energy-enabled scheduling, failure scheduling, and security schemes. The goal is to minimize the energy consumption of nodes and divide the application between local nodes and edge nodes by applying the secure min-cut algorithm. Furthermore, the study devises the secure-min-cut algorithm, which aims to migrate data between nodes in a secure form during application partitioning in the system. After partitioning the applications, the node-search algorithm searches optimally to run applications under their deadlines. The energy and failure schemes maintain the energy consumption of the nodes and the failure of the system. Simulation results show that DAPWTS outperforms existing baseline approaches by 30% in terms of energy consumption, deadline, and failure of applications in the system.

    Fulltekst (pdf)
    fulltext
  • 6.
    Rihm, Sivert
    et al.
    Högskolan Kristianstad, Sektionen för hälsa och samhälle.
    Olsson, Mikael
    Högskolan Kristianstad, Sektionen för hälsa och samhälle.
    Bring Your Own Device: what is it good for2013Independent thesis Basic level (university diploma), 5 poäng / 7,5 hpOppgave
    Abstract [sv]

    Vad är BYOD (Bring Your Own Device)? BYOD är en relativt ny trend som går ut på att anställda på ett företag får möjlighet att ta med sina egna elektroniska produkter såsom smarta telefoner, surfplattor och bärbara datorer. Det dyker upp rubriker om fenomenet BYOD (Bring Your Own Device) i diverse tekniska nättidningar och under utbildningens gång har det funnits lärare som berört ämnet lite löst. Detta väckte en nyfikenhet för att gräva djupare i ämnet, eftersom det verkade vara en trend på uppgång. Detta är en så pass ny företeelse att många företag inte vet hur de ska hantera detta i sitt nätverk. Företagen har också fått omvärdera sina säkerhetspolicys.

    Fulltekst (pdf)
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