A key management scheme based on hypergraph for fog computing

Li, Zhi; Liu, Yanzhu; Liu, Di; Li, Chunyang; Cui, Wei; Hu, Guanglin

doi:10.1109/cc.2018.8543057

Cited by 13 publications

(9 citation statements)

References 10 publications

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“…Furthermore, the privacy-preserving techniques must have several means to validate the communications created within the Cloud network, as well as a variety of key functions to assure maximum privacy. 57 To establish which kinds of attacks put Cloud storage in jeopardy and which types of attacks the technique can counter, privacy issues must be thoroughly investigated. The test environment should be flexible and consistent with the established technique, such as the use of suitable hardware and software, adequate programming language expertise, and selection of the right Cloud server.…”

Section: Discussionmentioning

confidence: 99%

“…Random and big keys, on the other hand, may take a long time to analyze and decrypt, but they can provide good protection of data. Furthermore, the privacy‐preserving techniques must have several means to validate the communications created within the Cloud network, as well as a variety of key functions to assure maximum privacy 57 …”

Section: Discussionmentioning

confidence: 99%

“…All available databases, including Science Direct, IEEE, Springer, Wiley, Google Scholar, and MDPI, were used to identify studies that discussed privacy‐preserving in Cloud data storage. Several search phrases were used to find related studies, including “privacy,” “privacy‐preserving,” “Cloud,” “CC,” “Cloud storage,” and “Cloud data storage,” with the Booleans “OR” and “AND.” The following are the studies that were used to create the set of privacy‐preserving attributes 6,9–14,16,26,29,36–63 …”

Section: The Taxonomy Of Privacy‐preserving Attributes For the Cloud ...mentioning

confidence: 99%

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Enhancing privacy‐preserving mechanisms in Cloud storage: A novel conceptual framework

Mishra,

Jabar,

Alzoubi

et al. 2023

Concurrency and Computation

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SummaryData privacy is critical for users who want to use Cloud storage services. There is a significant focus on Cloud service providers to address this need. However, in the evolving dynamic cyber‐space, privacy infractions are rising and pose threats to Cloud storage infrastructures. Several studies developed various models and techniques to ensure the privacy of Cloud storage contents. However, these models came with several shortages in the privacy‐preserving attributes they cover. Thus, this article identified a comprehensive set of Cloud data storage privacy‐preserving attributes to propose a flexible and efficient framework to handle the privacy problem. This framework uses a multi‐layer encryption storage structure and a one‐time password authentication technique. The findings of this article intend to help future communities to enhance existing techniques or develop new research‐based practical alternatives. Since Cloud computing is a rapidly growing technology, new privacy vulnerabilities emerge daily. Future research might confirm the findings of this article and test the suggested framework in different contexts.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: The Taxonomy Of Privacy‐preserving Attributes For the Cloud ...mentioning

confidence: 99%

See 1 more Smart Citation

Enhancing privacy‐preserving mechanisms in Cloud storage: A novel conceptual framework

Mishra,

Jabar,

Alzoubi

et al. 2023

Concurrency and Computation

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“…Many experts and scholars have carried out research on the architecture of fog computing [39]. Existing fog computing architecture research can generally be divided into two categories: cloud-fog-terminal three-level architecture and fog-terminal two-level architecture [40]. The former consists of a cloud layer, a fog layer and a terminal layer.…”

Section: The Architecture Of Vehicular Fog Computingmentioning

confidence: 99%

Vehicle Cooperative Network Model Based on Hypergraph in Vehicular Fog Computing

Ran

Bai

2020

Sensors

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In this paper, we propose an optimization framework of vehicular fog computing and a cooperation vehicular network model. We aim to improve the performance of vehicular fog computing and solve the problem that the data of the vehicle collaborative network is difficult to obtain. This paper applies the hypergraph theory to study the underlying structure, considering the social characteristics of the vehicles and vehicle communication. Since the vehicles join the network in accordance with the Poisson process law, the model is analyzed by using Poisson stochastic process and mean field theory. This paper uses MATLAB to simulate the evolution process of cooperative networks. The results show that the vehicle's super-degree in vehicular fog computing has scale-free characteristics. Through this model, the vehicle cooperation situation can be analyzed, and the vehicle dynamics can be accurately predicted to further improve the performance of vehicular fog computing. The model can be transformed into some complex network models by adjusting the parameters. It has strong universality and has certain reference significance for the research on the related characteristics of VANETs and the theoretical research of the cooperative network.2 of 17 to higher network delays. For vehicles that are using autonomous driving in the Internet of Vehicles, high latency is likely to cause serious traffic accidents. Cellular network can provide limited enhanced communication, mainly controlled by network operators, which is inefficient from the application point of view [8]. Mobile cloud computing can bring rich computing resources to mobile users [9], but it is costly and time consuming to upload real-time information [10].Fog computing can effectively solve the above problems, by deploying a fog server with storage and computing near the user to receive and process user data [11]. The deployment location of the fog server is closer to the user, which can save a lot of data transmission time. The deployment of fog computing nodes in the connected vehicle network has become a popular trend in the research of VANETs. We finally proposed a novel concept of vehicular fog computing (VFC), which uses vehicles as infrastructure to make full use of vehicular communication and computing resources. Specifically, VFC is an architecture that has cloud-based features and provides data, computing, storage and application services to end users. VFC is also differentiated from other existing technologies by being close to end users, and having dense geographical distribution and support for mobility; its bottom layer consists of cooperative vehicles, so that the vehicle is both a fog computing provider and a vehicular fog computing user. It can use computing resources nearby and reduce the use of communication resources. In the fog computing architecture, vehicles and mobile devices are end users, and there is a fog server layer between these edge users and the cloud. The low-level equipment of vehicular fog computing vehicles has high-speed moving ch...

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“…Furthermore, our proposal can prevent collusion attacks, ensure forward/backward security. However, Scheme [55] and Scheme [54] only protect forward/backward security. Although GKMSFC and Scheme [45,46] have the same computational cost, GKMSFC has less network load and message costs.…”

Section: Rekeying Efficiencymentioning

confidence: 99%

Group Key Management Scheme for Multicast Communication Fog Computing Networks

Dong

2020

Processes

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In group key management, the implementation of encryption often fails because multicast communication does not provide reliable linkage. In this paper, a new group key management scheme is proposed for multicast communication in fog computing networks. In the proposed scheme, any legal fog user belonging to a fog node will be able to decrypt a ciphertext encrypted by a secret shared key. The shared secret key is divided into key segments. In the rekeying operation process, each key segment is split into two factors with its shared production mechanism. The key updates are required to belong to the fog provider or the group management device. Fog users will have independent key segments unchanged. Then, the cost, the message of rekeying, and the dependence on credible channels will be decreased. This method can resist collusion attacks and ensure backward security and forward security, even if the number of users leaving is larger than the threshold value. Our scheme is also suitable for untrusted affiliate networks.

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A key management scheme based on hypergraph for fog computing

Cited by 13 publications

References 10 publications

Enhancing privacy‐preserving mechanisms in Cloud storage: A novel conceptual framework

Enhancing privacy‐preserving mechanisms in Cloud storage: A novel conceptual framework

Vehicle Cooperative Network Model Based on Hypergraph in Vehicular Fog Computing

Group Key Management Scheme for Multicast Communication Fog Computing Networks

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