Empirical Evaluation of Privacy Efficiency in Blockchain Networks: Review and Open Challenges

With the widespread of blockchain technology, preserving the anonymity and confidentiality of transactions have become crucial. An enormous portion of blockchain research is dedicated to the design and development of privacy protocols but not much has been achieved for proper assessment of these solutions. To mitigate the gap, we have first comprehensively classified the existing solutions based on blockchain fundamental building blocks (i.e., smart contracts, cryptography, and hashing). Next, we investigated the evaluation criteria used for validating these techniques. The findings depict that the majority of privacy solutions are validated based on computing resources i.e., memory, time, storage, throughput, etc., only, which is not sufficient. Hence, we have additionally identified and presented various other factors that strengthen or weaken blockchain privacy. Based on those factors, we have formulated an evaluation framework to analyze the efficiency of blockchain privacy solutions. Further, we have introduced a concept of privacy precision that is a quantifiable measure to empirically assess privacy efficiency in blockchains. The calculation of privacy precision will be based on the effectiveness and strength of various privacy protecting attributes of a solution and the associated risks. Finally, we conclude the paper with some open research challenges and future directions. Our study can serve as a benchmark for empirical assessment of blockchain privacy.

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Rational Protocols and Attacks in Blockchain System

Security and Communication Networks ◽

10.1155/2020/8839047 ◽

2020 ◽

Vol 2020 ◽

pp. 1-11

Author(s):

Tao Li ◽

Yuling Chen ◽

Yanli Wang ◽

Yilei Wang ◽

Minghao Zhao ◽

...

Keyword(s):

Game Theory ◽

Internet Of Things ◽

Building Blocks ◽

Emerging Technology ◽

Economic Incentives ◽

Research Progress ◽

Smart Contracts ◽

Future Directions ◽

Smart Contract ◽

Game Theoretic

Blockchain has been an emerging technology, which comprises lots of fields such as distributed systems and Internet of Things (IoT). As is well known, blockchain is the underlying technology of bitcoin, whose initial motivation is derived from economic incentives. Therefore, lots of components of blockchain (e.g., consensus mechanism) can be constructed toward the view of game theory. In this paper, we highlight the combination of game theory and blockchain, including rational smart contracts, game theoretic attacks, and rational mining strategies. When put differently, the rational parties, who manage to maximize their utilities, involved in blockchain chose their strategies according to the economic incentives. Consequently, we focus on the influence of rational parties with respect to building blocks. More specifically, we investigate the research progress from the aspects of smart contract, rational attacks, and consensus mechanism, respectively. Finally, we present some future directions based on the brief survey with respect to game theory and blockchain.

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Bone Age Assessment Empowered with Deep Learning: A Survey, Open Research Challenges and Future Directions

Diagnostics ◽

10.3390/diagnostics10100781 ◽

2020 ◽

Vol 10 (10) ◽

pp. 781

Author(s):

Muhammad Waqas Nadeem ◽

Hock Guan Goh ◽

Abid Ali ◽

Muzammil Hussain ◽

Muhammad Adnan Khan ◽

...

Keyword(s):

Deep Learning ◽

Medical Images ◽

Bone Age ◽

Learning Models ◽

Age Assessment ◽

Future Directions ◽

Research Challenges ◽

Open Research ◽

Wide Range ◽

Bone Age Assessment

Deep learning is a quite useful and proliferating technique of machine learning. Various applications, such as medical images analysis, medical images processing, text understanding, and speech recognition, have been using deep learning, and it has been providing rather promising results. Both supervised and unsupervised approaches are being used to extract and learn features as well as for the multi-level representation of pattern recognition and classification. Hence, the way of prediction, recognition, and diagnosis in various domains of healthcare including the abdomen, lung cancer, brain tumor, skeletal bone age assessment, and so on, have been transformed and improved significantly by deep learning. By considering a wide range of deep-learning applications, the main aim of this paper is to present a detailed survey on emerging research of deep-learning models for bone age assessment (e.g., segmentation, prediction, and classification). An enormous number of scientific research publications related to bone age assessment using deep learning are explored, studied, and presented in this survey. Furthermore, the emerging trends of this research domain have been analyzed and discussed. Finally, a critical discussion section on the limitations of deep-learning models has been presented. Open research challenges and future directions in this promising area have been included as well.

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Data Protection in AI Services

ACM Computing Surveys ◽

10.1145/3440754 ◽

2021 ◽

Vol 54 (2) ◽

pp. 1-38

Author(s):

Christian Meurisch ◽

Max Mühlhäuser

Keyword(s):

Artificial Intelligence ◽

Data Protection ◽

Interdisciplinary Research ◽

Management System ◽

Cutting Edge ◽

Future Directions ◽

Research Challenges ◽

Open Research ◽

User Data ◽

Different Levels

Advances in artificial intelligence (AI) have shaped today’s user services, enabling enhanced personalization and better support. As such AI-based services inevitably require user data, the resulting privacy implications are de facto the unacceptable face of this technology. In this article, we categorize and survey the cutting-edge research on privacy and data protection in the context of personalized AI services. We further review the different protection approaches at three different levels, namely, the management, system, and AI levels—showing that (i) not all of them meet our identified requirements of evolving AI services and that (ii) many challenges are addressed separately or fragmentarily by different research communities. Finally, we highlight open research challenges and future directions in data protection research, especially that comprehensive protection requires more interdisciplinary research and a combination of approaches at different levels.

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Blockchain Technology, Its Applications and Open Research Challenges

Journal of Physics Conference Series ◽

10.1088/1742-6596/1950/1/012030 ◽

2021 ◽

Vol 1950 (1) ◽

pp. 012030

Author(s):

Rajesh Kumar Kaushal ◽

Naveen Kumar ◽

Surya Narayan Panda

Keyword(s):

Blockchain Technology ◽

Research Challenges ◽

Open Research

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A Fuzzy Multi-Criteria Evaluation Framework for Urban Sustainable Development

Mathematics ◽

10.3390/math8030330 ◽

2020 ◽

Vol 8 (3) ◽

pp. 330 ◽

Cited By ~ 5

Author(s):

Wei-Ming Wang ◽

Hsiao-Han Peng

Keyword(s):

Sustainable Development ◽

Policy Development ◽

Fuzzy Ahp ◽

Empirical Evaluation ◽

Evaluation Criteria ◽

Evaluation Framework ◽

Current Status ◽

Impact Factors ◽

Urban Sustainable Development ◽

Fuzzy Delphi

With the rapid transformations of living environments, urban sustainable development has become an important global issue for urban growth and management. In order to effectively implement urban sustainable development, it is necessary to establish an operational action model based on its nature. This study first clarifies the core value of urban quality of life (QOL), and proposes the corresponding concept of Life–City. A variety of factors may affect the content of Life–City, and when assessing the objectives of sustainable development, there are uncertain properties and value judgments. Therefore, Life–City evaluation is a fuzzy multi-criteria decision analysis (FMCDA) problem. This study constructs the dimensions and the possible impact factors for urban QOL development. The fuzzy Delphi method (FDM) is employed to screen evaluation criteria and develop the overall evaluation framework. In order to effectively convert the subjective and perceptual issues in the framework into objective and quantitative processing, this study adopts the extent analysis method on fuzzy AHP (EAFAHP) to aggregate experts’ comments as empirical evaluation. The research results can convert the abstract concept of sustainability to the evaluation of Life–City specific operation, and serve as guidance for self-examination of current status and future policy development.

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Big Data in Internet of Things: Architecture and Open Research Challenges

2020 IEEE 23rd International Multitopic Conference (INMIC) ◽

10.1109/inmic50486.2020.9318203 ◽

2020 ◽

Author(s):

Iram Haider ◽

Muhammad Arslan Haider ◽

Arshad Saeed

Keyword(s):

Big Data ◽

Internet Of Things ◽

Research Challenges ◽

Open Research

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Third Party Certification of Agri-Food Supply Chain Using Smart Contracts and Blockchain Tokens

Sensors ◽

10.3390/s21165307 ◽

2021 ◽

Vol 21 (16) ◽

pp. 5307

Author(s):

Ricardo Borges dos Santos ◽

Nunzio Marco Torrisi ◽

Rodrigo Palucci Pantoni

Keyword(s):

Supply Chain ◽

Mobile Application ◽

Consumer Behaviour ◽

Economic Incentives ◽

Third Party ◽

Smart Contracts ◽

Proof Of Concept ◽

Socially Responsible ◽

The Public ◽

Blockchain Technology

Every consumer’s buying decision at the supermarket influences food brands to make first party claims of sustainability and socially responsible farming methods on their agro-product labels. Fine wines are often subject to counterfeit along the supply chain to the consumer. This paper presents a method for efficient unrestricted publicity to third party certification (TPC) of plant agricultural products, starting at harvest, using smart contracts and blockchain tokens. The method is capable of providing economic incentives to the actors along the supply chain. A proof-of-concept using a modified Ethereum IGR token set of smart contracts using the ERC-1155 standard NFTs was deployed on the Rinkeby test net and evaluated. The main findings include (a) allowing immediate access to TPC by the public for any desired authority by using token smart contracts. (b) Food safety can be enhanced through TPC visible to consumers through mobile application and blockchain technology, thus reducing counterfeiting and green washing. (c) The framework is structured and maintained because participants obtain economical incentives thus leveraging it´s practical usage. In summary, this implementation of TPC broadcasting through tokens can improve transparency and sustainable conscientious consumer behaviour, thus enabling a more trustworthy supply chain transparency.

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A survey of phishing attack techniques, defence mechanisms and open research challenges

Enterprise Information Systems ◽

10.1080/17517575.2021.1896786 ◽

2021 ◽

pp. 1-39

Author(s):

Ankit Kumar Jain ◽

B. B. Gupta

Keyword(s):

Defence Mechanisms ◽

Research Challenges ◽

Open Research

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Ontologies for information entities: State of the art and open challenges

Applied Ontology ◽

10.3233/ao-210246 ◽

2021 ◽

Vol 16 (2) ◽

pp. 111-135

Author(s):

Emilio M. Sanfilippo

Keyword(s):

State Of The Art ◽

The State ◽

Literary Studies ◽

Health Records ◽

Research Challenges ◽

Open Research ◽

Applied Ontology ◽

Nature Of Information ◽

Technical Specifications

Information entities are used in ontologies to represent engineering technical specifications, health records, pictures or librarian data about, e.g., narrative fictions, among others. The literature in applied ontology lacks a comparison of the state of the art, and foundational questions on the nature of information entities remain open for research. The purpose of the paper is twofold. First, to compare existing ontologies with both each other and theories proposed in philosophy, semiotics, librarianship, and literary studies in order to understand how the ontologies conceive and model information entities. Second, to discuss some open research challenges that can lead to principled approaches for the treatment of information entities, possibly by getting into account the variety of information entity types found in the literature.

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