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R. Roman, J. Lopez, and M. Mambo, "Mobile edge computing, Fog et al.: A survey and analysis of security threats and challenges",
Future Generation Computer Systems, vol. 78, issue 1, Elsevier, pp. 680-698, 01/2018. DOI (I.F.: 5.768)More..

Abstract

For various reasons, the cloud computing paradigm is unable to meet certain requirements (e.g. low latency and jitter, context awareness, mobility support) that are crucial for several applications (e.g. vehicular networks, augmented reality). To fulfil these requirements, various paradigms, such as fog computing, mobile edge computing, and mobile cloud computing, have emerged in recent years. While these edge paradigms share several features, most of the existing research is compartmentalised; no synergies have been explored. This is especially true in the field of security, where most analyses focus only on one edge paradigm, while ignoring the others. The main goal of this study is to holistically analyse the security threats, challenges, and mechanisms inherent in all edge paradigms, while highlighting potential synergies and venues of collaboration. In our results, we will show that all edge paradigms should consider the advances in other paradigms.

Impact Factor: 5.768
Journal Citation Reports® Science Edition (Thomson Reuters, 2018)

PDF icon RomanFog16.pdf (775.54 KB)
A. Nieto, and J. Lopez, "A Model for the Analysis of QoS and Security Tradeoff in Mobile Platforms",
Mobile Networks and Applications (MONET) Journal, vol. 19, issue 1, Springer US, pp. 64-78, 02/2014. DOI (I.F.: 1.045)More..

Abstract

Today, mobile platforms are multimedia devices that provide different types of traffic with the consequent particular performance demands and, besides, security concerns (e.g. privacy). However, Security and QoS requirements quite often conflict to a large degree; the mobility and heterogeneous paradigm of the Future Internet makes coexistence even more difficult, posing new challenges to overcome. Probably, one of the main challenges is to identify the specific reasons why Security and QoS mechanisms are so related to each other. In this paper, we present a Parametric Relationship Model (PRM) to identify the Security and QoS dependencies, and to elaborate on the Security and QoS tradeoff. In particular, we perform an analysis that focus on the mobile platform environment and, consequently, also considers subjective parameters such user’s experience, that is crucial for increasing the usability of new solutions in the Future Internet. The final aim of our contribution is to facilitate the development of secure and efficient services for mobile platforms.

Impact Factor: 1.045
Journal Citation Reports® Science Edition (Thomson Reuters, 2014)

PDF icon nieto2013mone.pdf (666.18 KB)
D. Ferraris, C. Fernandez-Gago, and J. Lopez, "A model-driven approach to ensure trust in the IoT",
Human-centric Computing and Information Sciences, vol. 10, no. 50, Springer, 12/2020. DOI (I.F.: 5.9)More..

Abstract

The Internet of Things (IoT) is a paradigm that permits smart entities to be interconnected anywhere and anyhow. IoT opens new opportunities but also rises new issues.
In this dynamic environment, trust is useful to mitigate these issues. In fact, it is important that the smart entities could know and trust the other smart entities in order to collaborate with them.
So far, there is a lack of research when considering trust through the whole System Development Life Cycle (SDLC) of a smart IoT entity.
In this paper, we suggest a new approach that considers trust not only at the end of the SDLC but also at the start of it. More precisely, we explore the modeling phase proposing a model-driven approach extending UML and SysML considering trust and its related domains, such as security and privacy.
We propose stereotypes for each diagram in order to give developers a way to represent trust elements in an effective way.
Moreover, we propose two new diagrams that are very important for the IoT: a traceability diagram and a context diagram.
This model-driven approach will help developers to model the smart IoT entities according to the requirements elicited in the previous phases of the SDLC.
These models will be a fundamental input for the following and final phases of the SDLC.

Impact Factor: 5.9
Journal Citation Reports® Science Edition (Thomson Reuters, 2020)

PDF icon ferraris2020b.pdf (2.11 MB)