Improving Security on IoT Applications Based on the FIWARE Platform

Oliveira, Caio Thomas; Moreira, Rodrigo; Silva, Flávio de Oliveira; Miani, Rodrigo Sanches; Rosa, Pedro Frosi

doi:10.1109/aina.2018.00104

Cited by 4 publications

(5 citation statements)

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“…7. As this is crossvalidation, for each K, we obtained average accuracies for ten (10) different executions, and according to Fig. 7 with K = 4, we obtained the best accuracy of the model, with an average of 0.895.…”

Section: ) Datasetmentioning

confidence: 97%

“…These resources are currently available on specialized and independent experimental networks, and SFI2 groups them in a structured way. At this point, it is important to remark that the SFI2 deployment focus is the set of experimental networks currently available in Brazil: FIBRE-NG [7], CloudNEXT [9], FUTEBOL [8], FIWARE [10], 5GINFIRE [11], and NECOS [12].…”

Section: The Sfi2 Network Slicing Architecturementioning

confidence: 99%

“…The Slicing Future Internet Infrastructures (SFI2) 1 research project [6] leading technical and innovative emphasis is to develop a network slicing solution that provides orchestration and allocation of resources for multi-domain experimentation network infrastructures. The experimentation testbeds FIBRE-NG [7], FUTEBOL [8], CloudNEXT [9], FIWARE [10], 5GINFIRE [11], and NECOS [12], are the main targets of the SFI2 project. In this context, the SFI2 project aims to integrate resources and services from the legacy experimental infrastructures mentioned above by defining a reference architecture and functionalities, allowing its instantiation and deployment on distinct domains.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Enhancing Network Slicing Architectures With Machine Learning, Security, Sustainability and Experimental Networks Integration

Martins

Carvalho²,

Moreira³

et al. 2023

IEEE Access

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Network Slicing (NS) is an essential technique extensively used in 5G networks computing strategies, mobile edge computing, mobile cloud computing, and verticals like the Internet of Vehicles and industrial IoT, among others. NS is foreseen as one of the leading enablers for 6G futuristic and highly demanding applications since it allows the optimization and customization of scarce and disputed resources among dynamic, demanding clients with highly distinct application requirements. Various standardization organizations, like 3GPP's proposal for new generation networks and state-of-the-art 5G/6G research projects, are proposing new NS architectures. However, new NS architectures have to deal with an extensive range of requirements that inherently result in having NS architecture proposals typically fulfilling the needs of specific sets of domains with commonalities. The Slicing Future Internet Infrastructures (SFI2) architecture proposal explores the gap resulting from the diversity of NS architectures target domains by proposing a new NS reference architecture with a defined focus on integrating experimental networks and enhancing the NS architecture with Machine Learning (ML) native optimizations, energy-efficient slicing, and slicing-tailored security functionalities. The SFI2 architectural main contribution includes the utilization of the slice-as-a-service paradigm for endto-end orchestration of resources across multi-domains and multi-technology experimental networks. In addition, the SFI2 reference architecture instantiations will enhance the multi-domain and multi-technology integrated experimental network deployment with native ML optimization, energy-efficient aware slicing, and slicing-tailored security functionalities for the practical domain.

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Section: ) Datasetmentioning

confidence: 97%

Section: The Sfi2 Network Slicing Architecturementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Enhancing Network Slicing Architectures With Machine Learning, Security, Sustainability and Experimental Networks Integration

Martins

Carvalho²,

Moreira³

et al. 2023

IEEE Access

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show abstract

“…Furthermore, the TLS/DTLS handshake to establish secure communications and encrypting data transmission consumes several resources that are not supported in most of the constrained devices. Some works aim to solve this issue by using a gateway for delegating the initial handshake [41,42] or for performing a unique handshake and maintain the secured socket open [43]. The latter is feasible if deployed on trusted networks or if lightweight and secure encryption are implemented between devices and gateways [21,25].…”

Section: Oauth20 Over Iot Protocolsmentioning

confidence: 99%

“…The gateway source code is written in Node.js and relies on https, node-coap and node-dtls libraries to provide either CoAPs and HTTPs requests. Particularly, for the CoAPs case, the secured DTLS socket used in the communication remains open similarly to [43].…”

Section: Gatewaymentioning

confidence: 99%

Contribution to the Design and Integration of Identity Management and Access Control Mechanisms for Smart Environments

Huertas¹

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Identity Management and Access Control mechanisms are present in practically every digital application. Companies, public administrations or universities have deployed these mechanisms to ensure that appropriate users access to the services that are entitled to them. The main objective of this integration is to protect private personal and professional information from malicious actors.Digital services have grown exponentially, forcing Identity Management models to move from a centralised to a federated approach to improve the user experience and bridge some security loopholes. Nowadays, federated identity management systems are still in use but giving users a little more control over their data. Their design and implementation poses a number of challenges that depend on the characteristics of each environment and the privacy's level required. However, people still have little control over their identity and how their information is shared between organizations. In recent years, a new paradigm in identity management has been emerging to give people autonomy over their digital identities: Self Sovereign Identity. It is at an early stage and opens up a number of opportunities and challenges.Nowadays, an increasing number of businesses are exploiting data obtained from a variety of sources. In this sense, due to the Industry 4.0 paradigm new spaces are emerging for data sharing between companies to improve production chains, and with it, new ways of controlling access to data. Traditional access control mechanisms does not fulfil the trust, governance and usage requirements that these cases need, giving rise to new challenges to be addressed. This thesis proposes a set of architectures, models and mechanisms to address the challenges identified in the scope of identity and access management and contribute to improve the security and privacy of that field. The starting point of the thesis is the design and evaluation of delegated authentication systems for non-interface and resource-constrained devices. These systems aim to improve the security of devices in these contexts and even improve their efficiency. The next step is to implement an Industry 4.0 standard for data sharing between organizations which allows to guarantee trust, data governance and secure data exchange. In this context, a model for enabling data usage control is presented. This model allows the management and definition of both access and usage control policies.Subsequently, a number of contributions are proposed in relation with European electronic IDentification and the eIDAS regulation. They enrich and simplify the authentication process for service providers and citizens. The first one extends the number of attributes of the eIDAS profile. The second extends the eIDAS basic architecture to obtain these attributes. Finally, another architecture is proposed for facilitating the integration of service providers into the eIDAS infrastructure.Finally, the new Self Sovereign Identity paradigm is approached. A study of opportunities and challenges is...

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Design, code generation and simulation of IoT environments with mobility devices by using model-driven development: SimulateIoT-Mobile

Barriga

Clemente

Pérez-Toledano

et al. 2023

Pervasive and Mobile Computing

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Improving Security on IoT Applications Based on the FIWARE Platform

Cited by 4 publications

References 10 publications

Enhancing Network Slicing Architectures With Machine Learning, Security, Sustainability and Experimental Networks Integration

Enhancing Network Slicing Architectures With Machine Learning, Security, Sustainability and Experimental Networks Integration

Contribution to the Design and Integration of Identity Management and Access Control Mechanisms for Smart Environments

Design, code generation and simulation of IoT environments with mobility devices by using model-driven development: SimulateIoT-Mobile

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