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  • 1.
    Amadeo, Marcia
    et al.
    Universita Mediterranea di Reggio Calabria.
    Campolo, Claudia
    Universita Mediterranea di Reggio Calabria. Telecommunications.
    Quevedo, Jose
    Universidade de Aveiro, Inst Telecomunicacoes.
    Corujo, Daniel
    Universidade de Aveiro, Inst Telecomunicacoes.
    Molinaro, Antonella
    Universita Mediterranea di Reggio Calabria. Telecommunications.
    Iera, Antonio
    Universita Mediterranea di Reggio Calabria.
    Aguiar, Rui L.
    Universidade de Aveiro, Inst Telecomunicacoes.
    Vasilakos, Athanasios
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Information-Centric Networking for the Internet of Things: Challenges and Opportunities2016Ingår i: IEEE Network, ISSN 0890-8044, E-ISSN 1558-156X, Vol. 30, nr 2, s. 92-100, artikel-id 7437030Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In view of evolving the Internet infrastructure, ICN is promoting a communication model that is fundamentally different from the traditional IP address-centric model. The ICN approach consists of the retrieval of content by (unique) names, regardless of origin server location (i.e., IP address), application, and distribution channel, thus enabling in-network caching/replication and content-based security. The expected benefits in terms of improved data dissemination efficiency and robustness in challenging communication scenarios indicate the high potential of ICN as an innovative networking paradigm in the IoT domain. IoT is a challenging environment, mainly due to the high number of heterogeneous and potentially constrained networked devices, and unique and heavy traffic patterns. The application of ICN principles in such a context opens new opportunities, while requiring careful design choices. This article critically discusses potential ways toward this goal by surveying the current literature after presenting several possible motivations for the introduction of ICN in the context of IoT. Major challenges and opportunities are also highlighted, serving as guidelines for progress beyond the state of the art in this timely and increasingly relevant topic.

  • 2.
    Lyamin, Nikita
    et al.
    Halmstad University, Sweden.
    Kleyko, Denis
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.
    Delooz, Quentin
    University of Liège, Belgium.
    Vinel, Alexey
    Halmstad University, Sweden.
    AI-Based Malicious Network Traffic Detection in VANETs2018Ingår i: IEEE Network, ISSN 0890-8044, E-ISSN 1558-156X, Vol. 32, nr 6, s. 15-21Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Inherent unreliability of wireless communications may have crucial consequences when safety-critical C-ITS applications enabled by VANETs are concerned. Although natural sources of packet losses in VANETs such as network traffic congestion are handled by decentralized congestion control (DCC), losses caused by malicious interference need to be controlled too. For example, jamming DoS attacks on CAMs may endanger vehicular safety, and first and foremost are to be detected in real time. Our first goal is to discuss key literature on jamming modeling in VANETs and revisit some existing detection methods. Our second goal is to present and evaluate our own recent results on how to address the real-time jamming detection problem in V2X safety-critical scenarios with the use of AI. We conclude that our hybrid jamming detector, which combines statistical network traffic analysis with data mining methods, allows the achievement of acceptable performance even when random jitter accompanies the generation of CAMs, which complicates the analysis of the reasons for their losses in VANETs. The use case of the study is a challenging platooning C-ITS application, where V2X-enabled vehicles move together at highway speeds with short inter-vehicle gaps.

  • 3.
    Wang, You
    et al.
    Institute for Network Sciences and Cyberspace, Tsinghua University.
    Bi, Jun
    Institute for Network Sciences and Cyberspace, Tsinghua University.
    Vasilakos, Athanasios
    University of Western Macedonia.
    An Identifier-Based Approach to Internet Mobility: A Survey2016Ingår i: IEEE Network, ISSN 0890-8044, E-ISSN 1558-156X, Vol. 30, nr 1, s. 72-79Artikel i tidskrift (Refereegranskat)
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