Civic Blockchain: Making blockchains accessible for social collaborative economies

Viano, Cristina; Avanzo, Sowelu; Boella, Guido; Schifanella, Claudio; Giorgino, Vincenzo Mario Bruno

doi:10.1016/j.jrt.2023.100066

Cited by 11 publications

(5 citation statements)

References 30 publications

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“…However, Web3's true revolutionary potential extends beyond blockchain [23,25]. It gives birth to DAOs, autonomous entities governed by code and consensus, where decisions are made collectively by stakeholders rather than dictated by corporate hierarchies [22,28].…”

Section: Emerging and Decentralized Web3 Technologies: A Paradigm Shiftmentioning

confidence: 99%

“…Emerging digital citizenship regimes play a central role in reshaping the data landscape, with evolving regulatory frameworks and initiatives promoting responsible and sustainable data practices [9,10]. The article explores emancipatory datafication strategies, including (i) blockchain-based decentralized data architectures [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25], (ii) decentralized autonomous organizations (DAOs) [26][27][28][29][30][31][32][33], and (iii) data cooperatives [34][35][36][37], as means to empower individuals and communities in reclaiming control over their data. In conclusion, the article explores a paradigm shift in data governance [38][39][40][41][42], calling for collective efforts to build more equitable and sustainable data spaces and ecosystems, with a focus on prioritizing data sovereignty and achieving digital self-determination [43][44][45][46].…”

Section: Introduction: the Big (Tech) Problem Of Data-opoliesmentioning

confidence: 99%

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Democratic Erosion of Data-Opolies: Decentralized Web3 Technological Paradigm Shift Amidst AI Disruption

Calzada

2024

BDCC

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This article investigates the intricate dynamics of data monopolies, referred to as “data-opolies”, and their implications for democratic erosion. Data-opolies, typically embodied by large technology corporations, accumulate extensive datasets, affording them significant influence. The sustainability of such data practices is critically examined within the context of decentralized Web3 technologies amidst Artificial Intelligence (AI) disruption. Additionally, the article explores emancipatory datafication strategies to counterbalance the dominance of data-opolies. It presents an in-depth analysis of two emergent phenomena within the decentralized Web3 emerging landscape: People-Centered Smart Cities and Datafied Network States. The article investigates a paradigm shift in data governance and advocates for joint efforts to establish equitable data ecosystems, with an emphasis on prioritizing data sovereignty and achieving digital self-governance. It elucidates the remarkable roles of (i) blockchain, (ii) decentralized autonomous organizations (DAOs), and (iii) data cooperatives in empowering citizens to have control over their personal data. In conclusion, the article introduces a forward-looking examination of Web3 decentralized technologies, outlining a timely path toward a more transparent, inclusive, and emancipatory data-driven democracy. This approach challenges the prevailing dominance of data-opolies and offers a framework for regenerating datafied democracies through decentralized and emerging Web3 technologies.

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Section: Emerging and Decentralized Web3 Technologies: A Paradigm Shiftmentioning

confidence: 99%

Section: Introduction: the Big (Tech) Problem Of Data-opoliesmentioning

confidence: 99%

Democratic Erosion of Data-Opolies: Decentralized Web3 Technological Paradigm Shift Amidst AI Disruption

Calzada

2024

BDCC

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“…(i) Blockchain technology offers secure and transparent decentralized systems, enabling efficient and trustworthy transactions (Inwood & Zappavigna, 2021;Rennie et al, 2022). In the context of diaspora engagement, blockchain can facilitate secure cross-border remittances, reducing costs and improving transparency in financial transactions (Viano et al, 2023). It also empowers diaspora communities to create and manage digital identities, establish property rights, and maintain immutable records for various purposes (Al-Saqaf & Seidler, 2017;Atzori, 2017;Buterin, 2022;De Filippi et al, 2020;Finck, 2018;Kondova & Erbguth, 2020).…”

Section: Literature Review: E-diasporas Alongside Five Disruptive Tec...mentioning

confidence: 99%

“…3. Lack of scalability: Current limitations in blockchain technology regarding scalability and speed may restrict its utility in certain contexts, especially when large-scale transactions or high-speed data processing are necessary (Hughes et al, 2019;Viano et al, 2023). 4.…”

Section: Blockchainmentioning

confidence: 99%

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Disruptive Technologies for e-Diasporas: Blockchain, DAOs, Data Cooperatives, Metaverse, and ChatGPT

Calzada

2023

SSRN Journal

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Suspicious transaction alert and blocking system for cryptocurrency exchanges in metaverse’s social media universes: RG-guard

Gürfidan

2024

Neural Comput & Applic

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In this study, we propose an effective system called RG-Guard that detects potential risks and threats in the use of cryptocurrencies in the metaverse ecosystem. In order for the RG-Guard engine to detect suspicious transactions, Ethereum network transaction information and phishing wallet addresses were collected, and a unique dataset was created after the data preprocessing process. During the data preprocessing process, we manually distinguished the features within the original dataset that contained potential risk indicators. The learning process of the RG-Guard engine in risk classification was achieved by developing a deep learning model based on LSTM + Softmax. In the training process of the model, RG-Guard was optimised for maximum accuracy, and optimum hyperparameters were obtained. The reliability and dataset performance of the preferred LSTM + Softmax model were verified by comparing it with algorithms used in risk classification and detection applications in the literature (Decision tree, XG boost, Random forest and light gradient boosting machine). Accordingly, among the trained models, LSTM + Softmax has the highest accuracy with an F1-score of 0.9950. When a cryptocurrency transaction occurs, RG-Guard extracts the feature vectors of the transaction and assigns a risk level between 1 and 5 to the parameter named βrisk. Since transactions with βrisk > = 3 are labelled as suspicious transactions, RG-Guard blocks this transaction. Thus, thanks to the use of the RG-Guard engine in metaverse applications, it is aimed to easily distinguish potential suspicious transactions from instant transactions. As a result, it is aimed to detect and prevent instant potential suspicious transactions with the RG-Guard engine in money transfers, which have the greatest risk in cryptocurrency transactions and are the target of fraud. The original dataset prepared in the proposed study and the hybrid LSTM + Softmax model developed specifically for the model are expected to contribute to the development of such studies.

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Civic Blockchain: Making blockchains accessible for social collaborative economies

Cited by 11 publications

References 30 publications

Democratic Erosion of Data-Opolies: Decentralized Web3 Technological Paradigm Shift Amidst AI Disruption

Democratic Erosion of Data-Opolies: Decentralized Web3 Technological Paradigm Shift Amidst AI Disruption

Disruptive Technologies for e-Diasporas: Blockchain, DAOs, Data Cooperatives, Metaverse, and ChatGPT

Suspicious transaction alert and blocking system for cryptocurrency exchanges in metaverse’s social media universes: RG-guard

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