Blockchain Mutability: Challenges and Proposed Solutions

Πολίτου, Ευγενία; Casino, Fran; Alepis, Efthimios; Patsakis, Constantinos

doi:10.48550/arxiv.1907.07099

Cited by 3 publications

(5 citation statements)

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“…We note that promising research on redactable blockchains has been conducted by Deuber et al [70], and also [71][72][73]. We envision a system where it is cheaper for a majority to delete undesirable content than for a minority to keep re-introducing it.…”

Section: Ethical Considerationsmentioning

confidence: 98%

Toward Uncensorable, Anonymous and Private Access Over Satoshi Blockchains

Recabarren¹,

Cărbunar²

2021

Preprint

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Providing unrestricted access to sensitive content such as news and software is difficult in the presence of adaptive and resourceful surveillance and censoring adversaries. In this paper we leverage the distributed and resilient nature of commercial Satoshi blockchains to develop the first provably secure, censorship resistant, cost-efficient storage system with anonymous and private access, built on top of commercial cryptocurrency transactions. We introduce max-rate transactions, a practical construct to persist data of arbitrary size entirely in a Satoshi blockchain. We leverage max-rate transactions to develop UWeb, a blockchain-based storage system that charges publishers to self-sustain its decentralized infrastructure. UWeb organizes blockchainstored content for easy retrieval, and enables clients to store and access content with provable anonymity, privacy and censorship resistance properties. We present results from UWeb experiments with writing 268.21 MB of data into the live Litecoin blockchain, including 4.5 months of live-feed BBC articles, and 41 censorship resistant tools. The max-rate writing throughput (183 KB/s) and blockchain utilization (88%) exceed those of state-of-the-art solutions by 2-3 orders of magnitude and broke Litecoin's record of the daily average block size. Our simulations with up to 3,000 concurrent UWeb writers confirm that UWeb does not impact the confirmation delays of financial transactions.

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Section: Ethical Considerationsmentioning

confidence: 98%

Toward Uncensorable, Anonymous and Private Access Over Satoshi Blockchains

Recabarren¹,

Cărbunar²

2021

Preprint

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“…Trust, security and privacy concerns USA, China, Taiwan, Sweden, [32], [33] Openness to change Saudi Arabia, Brazil [34], [35] Individual's willingness USA, Dutch, Europe, Asia, Australia [32], [36], [37] Information Technology & social media China, Canada & Australia, Iran, Taiwan, Hong Kong [38]- [43] Resource constraints Australia, Sub-Saharan Africa [44]- [46] cultural norms, Organisational culture Finland, Saudi Arabia [34], [47] Top management Italy [25], [48] organizational commitment…”

Section: Country Authormentioning

confidence: 99%

“…Top Management Support (TM) is meant by the degree to which an organisation's leaders are behind the initiative to embrace innovation and give it the resources it needs to succeed [7]. Top executives are taking their important role from being the ones who are in charge of making critical decisions [43]. A recent study identified senior management's acceptance and understanding of new technology as a critical factor influencing adoption intentions [44].…”

Section: ) the Organisational Context A Top Management Supportmentioning

confidence: 99%

“…The lack of technological expertise among decision-makers exacerbates the resistance to changes towards up-taking technology like cloud computing [19]. Some studies suggest that the absence of technical expertise among top executives regarding cloud computing impedes adoption [43]. In contrast, top managers' familiarity with the technical aspects of cloud computing can help them see the potential advantages of making the switch [7].…”

Section: B Prior Experiencesmentioning

confidence: 99%

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Position Papers of the 18th Conference on Computer Science and Intelligence Systems

2023

Annals of Computer Science and Information Systems

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Position papers comprise two categories of contributions -challenge papers and emerging research papers. Challenge papers propose and describe research challenges in theory, or practice, of computer science and intelligence systems. Papers in this category are based on deep understanding of existing research or industrial problems. Based on such understanding and experience, they define new exciting research directions and show why these directions are crucial to the society at large. Emerging research papers present preliminary research results from work-in-progress, based on sound scientific approach but presenting work not completely validated as yet. They describe precisely the research problem and its rationale. They also define the intended future work including the expected benefits from solution to the tackled problem. Subsequently, they may be more conceptual than experimental.FedCSIS 2023 was chaired by Jarosław Arabas and Sławomir Zadrożny, while Przemysław Biecek acted as the Chair of the Organizing Committee. This year, FedCSIS was organized by Polish Information Processing Society (Mazovia Chapter),

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“…At this point, blockchain technology would be avoided. This is due to transactional time limitations and legal requirements, such as the right to erasure outlined in the General Data Protection Regulation (GDPR), where only some research idea results are available [43], which…”

Section: Fl-dtmentioning

confidence: 99%

Federated Learning for Data Trust in Logistics

Koch,

Kober,

Straburzynski

et al. 2023

Position Papers of the 18th Conference on Computer Science and Intelligence Systems

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In the field of logistics, there is a significant shortage of qualified employees. Artificial Intelligence (AI) can help solve that problem supporting existing employees and reducing their workload. However, large amounts of data to train AI models are required and, in most cases, due to lack of trust between companies, model training is based solely on locally stored data from logistics providers and some publicly available datasets. To address this data scarcity issue, a proposed solution is to employ federated learning (FL), in the context of data trust (DT) by training AI models across multiple companies, based on both centralized data, within the DT platform and decentralized data from logistics providers data silos, while ensuring data sharing access at the attribute level. This paper proposes this approach and points out the importance of data sharing for effective model training for solving workforce challenges in logistics.

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Blockchain Mutability: Challenges and Proposed Solutions

Cited by 3 publications

References 0 publications

Toward Uncensorable, Anonymous and Private Access Over Satoshi Blockchains

Toward Uncensorable, Anonymous and Private Access Over Satoshi Blockchains

Position Papers of the 18th Conference on Computer Science and Intelligence Systems

Federated Learning for Data Trust in Logistics

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