FogAuthChain: A secure location-based authentication scheme in fog computing environments using Blockchain

Patwary, Abdullah Al-Noman; Fu, Anmin; Battula, Sudheer Kumar; Naha, Ranesh Kumar; Garg, Saurabh; Mahanti, Anirban

doi:10.1016/j.comcom.2020.08.021

Cited by 59 publications

(56 citation statements)

References 14 publications

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“…Most related works propose preemptive access control [29] and authentication schemes [30] for data mashup privacy preservation in fog computing environments. However, the utility of the published data is lesser in such approaches because they are limited by design to expose publicly available data only.…”

Section: Discussionmentioning

confidence: 99%

“…Most works on privacy preservation in distributed data environments propose a preemptive approach, defining who has access to private data attributes and resources by defining user profiles [29]. Access control techniques and authentication-based schemes [30] explicitly grant and revoke data access to parties. The larger the number of sensitive attributes in an access-controlled dataset, the greater the loss of analytical utility if exposing only publicly available data attributes.…”

Section: Related Workmentioning

confidence: 99%

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Privacy Preservation and Analytical Utility of E-Learning Data Mashups in the Web of Data

2021

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Virtual learning environments contain valuable data about students that can be correlated and analyzed to optimize learning. Modern learning environments based on data mashups that collect and integrate data from multiple sources are relevant for learning analytics systems because they provide insights into students’ learning. However, data sets involved in mashups may contain personal information of sensitive nature that raises legitimate privacy concerns. Average privacy preservation methods are based on preemptive approaches that limit the published data in a mashup based on access control and authentication schemes. Such limitations may reduce the analytical utility of the data exposed to gain students’ learning insights. In order to reconcile utility and privacy preservation of published data, this research proposes a new data mashup protocol capable of merging and k-anonymizing data sets in cloud-based learning environments without jeopardizing the analytical utility of the information. The implementation of the protocol is based on linked data so that data sets involved in the mashups are semantically described, thereby enabling their combination with relevant educational data sources. The k-anonymized data sets returned by the protocol still retain essential information for supporting general data exploration and statistical analysis tasks. The analytical and empirical evaluation shows that the proposed protocol prevents individuals’ sensitive information from re-identifying.

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Privacy Preservation and Analytical Utility of E-Learning Data Mashups in the Web of Data

2021

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“…A typical BC and smart contract implementation also illustrated in Figure 1. The data sent from IoT devices to the Fog node for data aggregation and further analysis [22]. Fog nodes enforce predefined security policies to manage connected IoT devices and services and also play an intermediate role of interaction between the Cloud and the public BC which enable indexing of authentication for data query [23].…”

Section: Fog Computing Backgroundmentioning

confidence: 99%

Fog computing security and privacy issues, open challenges, and blockchain solution: An overview

Alzoubi

Al‐Ahmad

Jaradat

2021

IJECE

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<span lang="EN-US">Due to the expansion growth of the IoT devices, Fog computing was proposed to enhance the low latency IoT applications and meet the distribution nature of these devices. However, Fog computing was criticized for several privacy and security vulnerabilities. This paper aims to identify and discuss the security challenges for Fog computing. It also discusses blockchain technology as a complementary mechanism associated with Fog computing to mitigate the impact of these issues. The findings of this paper reveal that blockchain can meet the privacy and security requirements of fog computing; however, there are several limitations of blockchain that should be further investigated in the context of Fog computing.</span>

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“…Users should first conduct identity authentication for cloud data users and then obtain the required services from the Cloud [140]. And in 2020, the research on authentication has expanded to multiple aspects such as mutual authentication [89], authentication scheme [141] and fog computing [142]. The research on it has continued from the third period to the fourth period and has gradually matured.…”

Section: ) Cloudmentioning

confidence: 99%

Bibliometric Analysis of the Blockchain Scientific Evolution: 2014–2020

Luo

Bai

2021

IEEE Access

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As one of the disruptive technologies in the fourth industrial revolution, Blockchain has irrevocably changed how people live and work. Many scholars have studied the Blockchain, and the number of related publications has increased over time. Bibliometrics is an excellent method to study the development trend of a specific field. However, few scholars have used bibliometrics to research Blockchain; the inheritance and evolution among its different research themes have not yet been fully understood. This study emphasizes the scientific evolution and research focus of Blockchain through bibliometric analysis. We analyzed 2993 publications from 2014 to 2020 using co-word analysis and cluster analysis with bibliometric tools such as the SciMAT. The most productive author, country, institutions and leading research areas were identified, outlining the Blockchain field's fundamental developments. The results show the changes in keywords regarding Blockchain summarize the research hotspots in different periods. The study discusses the evolution process of various themes in each period, providing a meaningful reference for scholars to identify research hotspots and future research directions in the Blockchain field.

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FogAuthChain: A secure location-based authentication scheme in fog computing environments using Blockchain

Cited by 59 publications

References 14 publications

Privacy Preservation and Analytical Utility of E-Learning Data Mashups in the Web of Data

Privacy Preservation and Analytical Utility of E-Learning Data Mashups in the Web of Data

Fog computing security and privacy issues, open challenges, and blockchain solution: An overview

Bibliometric Analysis of the Blockchain Scientific Evolution: 2014–2020

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