SMCP: a Secure Mobile Crowdsensing Protocol for fog-based applications

Concone, Federico; Re, Giuseppe Lo; Morana, Marco

doi:10.1186/s13673-020-00232-y

Cited by 13 publications

(6 citation statements)

References 45 publications

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“…To complement this vulnerability, we proposed an improved protocol that uses LEA for encryption the UE and the SN. In addition, instead of using AES algorithms recommended by existing standards, we speed up the protocol using LEAs that can be implemented in IoT in the future and can provide high speed in cloud environments [22]. In addition, LEA reduce the power consumed, it is efficient to use LEA in encryption and decryption section.…”

Section: Discussionmentioning

confidence: 99%

Implementation of Efficient 5G AKA Protocol for Light-Weight Environment

2021

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There is a critical vulnerability in the 5G AKA protocol of the 3GPP. We propose a protocol that compensates for these vulnerabilities and speed up the existing protocol; and the study implements this protocol to experiment with the vulnerabilities. The protocol uses the Light-weight Encryption Algorithm and is expected to be n3 times faster in than with the application of Advanced Encryption Standard algorithms. By using this algorithm, we improve the protocol efficiently, reduced the power consumed.

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Section: Discussionmentioning

confidence: 99%

Implementation of Efficient 5G AKA Protocol for Light-Weight Environment

2021

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“…Concone et al [32] presented a cloud-sensing scheme, called "secure protocol for mobile crowdsensing (SMCP)", for fog based applications that utilized signatures and did not involve the cloud server until the final update. SMCP is based on ECC, "extended triple Diffie-Hellman key agreement" and "symmetric cryptography".…”

Section: Related Workmentioning

confidence: 99%

Lightweight Failover Authentication Mechanism for IoT-Based Fog Computing Environment

et al. 2021

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Fog computing as an extension to the cloud computing infrastructure has been invaluable in enhancing the applicability of the Internet of Things (IoT) paradigm. IoT based Fog systems magnify the range and minimize the latency of IoT applications. However, as fog nodes are considered transient and they offer authenticated services, when an IoT end device loses connectivity with a fog node, it must authenticate freshly with a secondary fog node. In this work, we present a new security mechanism to leverage the initial authentication to perform fast lightweight secondary authentication to ensure smooth failover among fog nodes. The proposed scheme is secure in the presence of a current de-facto Canetti and Krawczyk (CK)-adversary. We demonstrate the security of the proposed scheme with a detailed security analysis using formal security under the broadly recognized Real-Or-Random (ROR) model, informal security analysis as well as through formal security verification using the broadly-used Automated Validation of Internet Security Protocols and Applications (AVISPA) software tool. A testbed experiment for measuring computational time for different cryptographic primitives using the Multiprecision Integer and Rational Arithmetic Cryptographic Library (MIRACL) has been done. Finally, through comparative analysis with other related schemes, we show how the presented approach is uniquely advantageous over other schemes.

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“…Secure Mobile Crowdsensing Protocol (SMCP) [108] provides a framework to secure data and ensure privacy for crowdsensing applications in the edge. The framework uses a cloud server to act as a registry for fog and edge nodes, using Extended Triple Diffie-Hellman Key Agreement (X3DHKA) and Advanced Encryption Standard (AES) as lightweight algorithms to secure traffic and enable the mutual authentication of nodes.…”

Section: Securitymentioning

confidence: 99%

Enabling and Leveraging AI in the Intelligent Edge: A Review of Current Trends and Future Directions

Goethals¹,

Volckaert

Turck

2021

IEEE Open J. Commun. Soc.

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The use of AI in Smart applications and in the organization of the network edge presents a rapidly advancing research field, with a great variety of challenges and opportunities. This article aims to provide a holistic review of studies from 2019 to 2021 related to the Intelligent Edge, a concept comprising both the use of AI to organize edge networks (Edge Intelligence) and Smart applications in the edge. An introduction is given to the technologies required to understand the state of the art of AI in edge networks, and a taxonomy is provided with "Enabling Technology" for Edge Intelligence, "Organization" of the edge using AI, and AI "Applications" in the edge as its main topics. Research trend data from 2015 to 2020 is presented for various subdivisions of these topics, showing both absolute and relative research interest in each subtopic. The "Organization" aspect, being the main focus of this article, has a more fine-grained subdivision, explaining all contributing factors in detail. The trends indicate an exponential increase in research interest in nearly all subtopics, but significant differences between them. For each subdivision of the taxonomy a number of selected studies from 2019 to 2021 are gathered to form a high-level illustration of the state of the art of Edge Intelligence. From these selected studies and the trend data, a number of short-term challenges and high-level visions for Edge Intelligence are formulated, providing a basis for future work.

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SMCP: a Secure Mobile Crowdsensing Protocol for fog-based applications

Cited by 13 publications

References 45 publications

Implementation of Efficient 5G AKA Protocol for Light-Weight Environment

Implementation of Efficient 5G AKA Protocol for Light-Weight Environment

Lightweight Failover Authentication Mechanism for IoT-Based Fog Computing Environment

Enabling and Leveraging AI in the Intelligent Edge: A Review of Current Trends and Future Directions

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