Digital Inheritance in Web3: A Case Study of Soulbound Tokens and the Social Recovery Pallet within the Polkadot and Kusama Ecosystems

• URL: http://arxiv.org/abs/2301.11074v3
• Date: Thu, 6 Jun 2024 21:30:09 GMT
• Title: Digital Inheritance in Web3: A Case Study of Soulbound Tokens and the Social Recovery Pallet within the Polkadot and Kusama Ecosystems
• Authors: Justin Goldston, Tomer Jordi Chaffer, Justyna Osowska, Charles von Goins II,
• Abstract summary: This study proposes a framework for digital inheritance using soulbound tokens and the social recovery pallet. The findings suggest that while soulbound tokens and the social recovery pallet offer a promising solution for creating a digital inheritance plan the findings also raise important considerations for testators digital executors and developers.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In recent years discussions centered around digital inheritance have increased among social media users and across blockchain ecosystems. As a result digital assets such as social media content cryptocurrencies and non-fungible tokens have become increasingly valuable and widespread, leading to the need for clear and secure mechanisms for transferring these assets upon the testators death or incapacitation. This study proposes a framework for digital inheritance using soulbound tokens and the social recovery pallet as a use case in the Polkadot and Kusama blockchain networks. The findings discussed within this study suggest that while soulbound tokens and the social recovery pallet offer a promising solution for creating a digital inheritance plan the findings also raise important considerations for testators digital executors and developers. While further research is needed to fully understand the potential impacts and risks of other technologies such as artificial intelligence and quantum computing this study provides a primer for users to begin planning a digital inheritance strategy and for developers to develop a more intuitive solution.

Related papers

• On Replacing Cryptopuzzles with Useful Computation in Blockchain Proof-of-Work Protocols [0.12289361708127873]
  Researchers have been pursuing the idea of replacing cryptopuzzles with useful computing tasks for over a decade. We provide insight into the effect of introducing "usefulness" and of transitioning to task classes other than cryptopuzzles. We discuss pertinent techniques and present research gaps in the current state-of-the-art.
  arXiv  Detail & Related papers  (2024-04-24T08:49:41Z)
• Enhancing Trust and Privacy in Distributed Networks: A Comprehensive Survey on Blockchain-based Federated Learning [51.13534069758711]
  Decentralized approaches like blockchain offer a compelling solution by implementing a consensus mechanism among multiple entities. Federated Learning (FL) enables participants to collaboratively train models while safeguarding data privacy. This paper investigates the synergy between blockchain's security features and FL's privacy-preserving model training capabilities.
  arXiv  Detail & Related papers  (2024-03-28T07:08:26Z)
• Generative AI-enabled Blockchain Networks: Fundamentals, Applications, and Case Study [73.87110604150315]
  Generative Artificial Intelligence (GAI) has emerged as a promising solution to address challenges of blockchain technology. In this paper, we first introduce GAI techniques, outline their applications, and discuss existing solutions for integrating GAI into blockchains.
  arXiv  Detail & Related papers  (2024-01-28T10:46:17Z)
• Decentralized Deepfake Detection Blockchain Network using Dynamic Algorithm management [0.0]
  This paper presents a comprehensive framework for a blockchain-based decentralized system to tackle the challenge of digital content integrity. The proposed system integrates advanced deep learning algorithms with the immutable and transparent nature of blockchain technology to create a trustless environment. The decentralized architecture of the system democratizes the process of verifying digital content and introduces a novel approach to combat deepfakes.
  arXiv  Detail & Related papers  (2023-11-30T13:27:00Z)
• Evaluation of Non-Fungible Token (NFT) [0.0]
  The derivative of token standard of blockchain, termed as Non Fungible Token is distinguishable token. These tokens are bound with digital properties that provide them unique identification. This paper is an attempt to squeeze the NFT developments systematically.
  arXiv  Detail & Related papers  (2023-08-28T08:12:32Z)
• Brain-Inspired Computational Intelligence via Predictive Coding [89.6335791546526]
  Predictive coding (PC) has shown promising performance in machine intelligence tasks. PC can model information processing in different brain areas, can be used in cognitive control and robotics.
  arXiv  Detail & Related papers  (2023-08-15T16:37:16Z)
• Challenges of Blockchain Applications in Digital Health: A Systematic Review [0.0]
  This systematic literature review aims to explore the challenges of blockchain applications in digital health. Key issues identified include regulatory compliance, energy consumption, network effects, data standards, and the accessibility of the technology to stakeholders.
  arXiv  Detail & Related papers  (2023-04-08T20:50:20Z)
• Combining Blockchain and Biometrics: A Survey on Technical Aspects and a First Legal Analysis [2.9023633922848586]
  This paper provides a survey of technical literature research on the combination of blockchain and biometrics. It includes a first legal analysis of this integration to shed light on challenges and potentials.
  arXiv  Detail & Related papers  (2023-02-21T18:58:32Z)
• When Quantum Information Technologies Meet Blockchain in Web 3.0 [86.91054991998273]
  We introduce a quantum blockchain-driven Web 3.0 framework that provides information-theoretic security for decentralized data transferring and payment transactions. We discuss the potential applications and challenges of implementing quantum blockchain in Web 3.0.
  arXiv  Detail & Related papers  (2022-11-29T05:38:42Z)
• Efficiency in Digital Economies -- A Primer on Tokenomics [55.41644538483948]
  cryptographic tokens are a new digital paradigm that can facilitate the establishment of economic incentives in digital ecoystems. We show how certain principles and values that arise from the evolutionary process of digital cooperation can lead to a market economy characterized by economic efficiency of both individuals and the tokenized ecosystem as a whole.
  arXiv  Detail & Related papers  (2020-08-06T09:31:56Z)
• Deep Learning for Community Detection: Progress, Challenges and Opportunities [79.26787486888549]
  Article summarizes the contributions of the various frameworks, models, and algorithms in deep neural networks. This article summarizes the contributions of the various frameworks, models, and algorithms in deep neural networks.
  arXiv  Detail & Related papers  (2020-05-17T11:22:11Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.