Privacy Preservation in Resource-Constrained IoT Devices Using Blockchain—A Survey

Iftikhar, Zainab; Javed, Yasir; Zaidi, Syed Yawar Abbas; Shah, Munam Ali; Khan, Zafar Iqbal; Mussadiq, Shafaq; Abbasi, Kamran

doi:10.3390/electronics10141732

Cited by 28 publications

(14 citation statements)

References 138 publications

(154 reference statements)

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“…Big data is therefore a vast amount of rapidly changing data with mixed data types. According to [16], IoT deployments in many industries meet the privacy challenges faced by IoT in resource-constrained devices. It provides an opportunity to address some of the uses of blockchain in various fields and IoT privacy concerns.…”

Section: Literature Surveymentioning

confidence: 99%

Implementation of Big Data Privacy Preservation Technique for Electronic Health Records in Multivendor Environment

Puri¹,

Haritha²

2023

IJACSA

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Various diagnostic health data formats and standards include both structured and unstructured data. Sensitive information contained in such metadata requires the development of specific approaches that can combine methods and techniques that can extract and reconcile the information hidden in such data. However, when this data needs to be processed and used for other reasons, there are still many obstacles and concerns to overcome. Modern approaches based on machine learning including big data analytics, assist in the information refinement process for later use of clinical evidence. These strategies consist of transforming various data into standard formats in specific scenarios. In fact, in order to conform to these rules, only de-identified diagnostic and personal data may be handled for secondary analysis, especially when information is distributed or transferred across institutions. This paper proposes big data privacy preservation techniques using various privacy functions. This research focused on secure data distribution as well as security access control to revoke the malicious activity or similarity attacks from end-user. The various privacy preservation techniques such as data anonymization, generalization, random permutation, kanonymity, bucketization, l-diversity with slicing approach have been proposed during the data distribution. The efficiency of system has been evaluated in Hadoop distributed file system (HDFS) with numerous experiments. The results obtained from different experiments show that the computation should be changed when changing k-anonymity and l-diversity. As a result, the proposed system offers greater efficiency in Hadoop environments by reducing execution time by 15% to 18% and provides a higher level of access control security than other security algorithms.

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Section: Literature Surveymentioning

confidence: 99%

Implementation of Big Data Privacy Preservation Technique for Electronic Health Records in Multivendor Environment

Puri¹,

Haritha²

2023

IJACSA

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“…These methods can facilitate trade between entities with high levels of trust, thereby eliminating the possibility of dealing with dishonest sellers in smart marketplace context. These techniques frequently result in risky double-spending and require substantial computational resources 45 – 47 . When clusters are formed based on the similarity of their members' profiles, uniformity is not guaranteed 41 .…”

Section: Related Workmentioning

confidence: 99%

MarketTrust: blockchain-based trust evaluation model for SIoT-based smart marketplaces

Latif

Yakubu

Saba

2023

Sci Rep

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Due to the significance of trust in Social Internet of Things (SIoT)-based smart marketplaces, several research have focused on trust-related challenges. Trust is necessary for a smooth connection, secure systems, and dependable services during trade operations. Recent SIoT-based trust assessment approaches attempt to solve smart marketplace trust evaluation difficulties by using a variety of direct and indirect trust evaluation techniques and other local trust rating procedures. Nevertheless, these methodologies render trust assessment very sensitive to seller dishonesty, and a dishonest seller may influence local trust scores and at the same time pose a significant trust related threats in the system. In this article, a MarketTrust model is introduced, which is a blockchain-based method for assessing trust in an IoT-based smart marketplace. It has three parts: familiarity, personal interactions, and public perception. A conceptual model, assessment technique, and a global trust evaluation system for merging the three components of a trust value are presented and discussed. Several experiments were conducted to assess the model's security, viability, and efficacy. According to results, the MarketTrust model scored a 21.99% higher trust score and a 47.698% lower average latency than both benchmark models. Therefore, this illustrates that using the proposed framework, a potential buyer can efficiently choose a competent and trustworthy resource seller in a smart marketplace and significantly reduce malicious behavior.

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“…This study researched prior Blockchain scalability research, such as those mentioned in current surveys on Blockchain scalability and the fundamental scalability principles accessible in contemporary literature [ 93 ]. As a result, this section analyses and specifies significant characteristics that may be used to characterize a Blockchain system’s scalability.…”

Section: Background Knowledgementioning

confidence: 99%

A Systematic Literature Review and Meta-Analysis on Scalable Blockchain-Based Electronic Voting Systems

Jafar

Aziz

Shukur

et al. 2022

Sensors

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Electronic voting systems must find solutions to various issues with authentication, data privacy and integrity, transparency, and verifiability. On the other hand, Blockchain technology offers an innovative solution to many of these problems. The scalability of Blockchain has arisen as a fundamental barrier to realizing the promise of this technology, especially in electronic voting. This study seeks to highlight the solutions regarding scalable Blockchain-based electronic voting systems and the issues linked with them while also attempting to foresee future developments. A systematic literature review (SLR) was used to complete the task, leading to the selection of 76 articles in the English language from 01.01.2017 to 31.03.2022 from the famous databases. This SLR was conducted to identify well-known proposals, their implementations, verification methods, various cryptographic solutions in previous research to evaluate cost and time. It also identifies performance parameters, the primary advantages and obstacles presented by different systems, and the most common approaches for Blockchain scalability. In addition, it outlines several possible research avenues for developing a scalable electronic voting system based on Blockchain technology. This research helps future research before proposing or developing any solutions to keep in mind all the voting requirements, merits, and demerits of the proposed solutions and provides further guidelines for scalable voting solutions.

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Privacy Preservation in Resource-Constrained IoT Devices Using Blockchain—A Survey

Cited by 28 publications

References 138 publications

Implementation of Big Data Privacy Preservation Technique for Electronic Health Records in Multivendor Environment

Implementation of Big Data Privacy Preservation Technique for Electronic Health Records in Multivendor Environment

MarketTrust: blockchain-based trust evaluation model for SIoT-based smart marketplaces

A Systematic Literature Review and Meta-Analysis on Scalable Blockchain-Based Electronic Voting Systems

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