VBlock: A Blockchain-Based Tamper-Proofing Data Protection Model for Internet of Vehicle Networks

The rapid advancement of the Internet of Vehicles (IoV) has led to a massive growth in data received from IoV networks. The cloud storage has been a timely service that provides a vast range of data storage for IoV networks. However, existing data storage and access models used to manage and protect data in IoV networks have proven to be insufficient. They are centralized and usually accompanied by a lack of trust, transparency, security, immutability, and provenance. In this paper, we propose VBlock, a blockchain-based system that addresses the issues of illegal modification of outsourced vehicular data for smart city management and improvement. We introduce a novel collusion-resistant model for outsourcing data to cloud storage that ensures the network remains tamper-proof, has good data provenance and auditing, and solves the centralized problems prone to the single point of failure. We introduced a key revocation mechanism to secure the network from malicious nodes. We formally define the system model of VBlock in the setting of a consortium blockchain. Our simulation results and security analysis show that the proposed model provides a strong security guarantee with high efficiency and is practicable in the IoV environment

ExCrowd: A Blockchain Framework for Exploration-Based Crowdsourcing

Because of the rise of cryptocurrencies and decentralized apps, blockchain technology has generated a lot of interest. Among these is the emergent blockchain-based crowdsourcing paradigm, which eliminates the centralized conventional mechanism servers in favor of smart contracts for task and reward allocation. However, there are a few crucial challenges that must be resolved properly. For starters, most reputation-based systems favor high-performing employees. Secondly, the crowdsourcing platform’s expensive service charges may obstruct the growth of crowdsourcing. Finally, unequal evaluation and reward allocation might lead to job dissatisfaction. As a result, the aforementioned issues will substantially impede the development of blockchain-based crowdsourcing systems. In this study, we introduce ExCrowd, a blockchain-based crowdsourcing system that employs a smart contract as a trustworthy authority to properly select workers, assess inputs, and award incentives while maintaining user privacy. Exploration-based crowdsourcing employs the hyperbolic learning curve model based on the conduct of workers and analyzes worker performance patterns using a decision tree technique. We specifically present the architecture of our framework, on which we establish a concrete scheme. Using a real-world dataset, we implement our model on the Ethereum public test network leveraging its reliability, adaptability, scalability, and rich statefulness. The results of our experiments demonstrate the efficiency, usefulness, and adaptability of our proposed system

Everyday resilience: Supporting resilient strategies among low socioeconomic status communities

People experiencing financial hardship often possess resilient and resourceful behaviors when handling their day-to-day activities. Understanding how these individuals manifest resilience during adversity could provide insights into how technologies can support their existing efforts. In a partnership with an Australian community care center, we identified resilient practices of people with low socioeconomic status. Following a strength-based approach, we collected data via home visits and semi-structured interviews involving 14 participants, and observed activities at the care center over 8 months. Our participants exhibited three key facets of resilience: (1) resilience as an integral part of their everyday lives, (2) a spirited phenomenon, and (3) a social and care-focused process. We contribute empirical insights into our participants' situated resilience and articulate ways through which design can support their existing social and collaborative practices. We compare and contrast our findings within and outside CSCW literature and advocate for a strength-based approach