In this paper, we propose a blockchain-based solution and framework for document sharing and version control to facilitate multiuser collaboration and track changes in a trusted, secure, and decentralized manner, with no involvement of a centralized trusted entity or third party. This solution is based on utilizing Ethereum smart contracts to govern and regulate the document version control functions among the creators and developers of the document and its validators. Moreover, our solution leverages the benefits of IPFS (InterPlanetary File System) to store documents on a decentralized file system. The proposed solution automates necessary interactions among multiple actors comprising developers and approvers. Smart contracts have been developed using Solidity language, and their functionalities were tested using the Remix IDE (Integrated Development Environment). The paper demonstrates that our smart contract code is free of commonly known security vulnerabilities and attacks. The code has been made publically available at Github.

No abstract

No abstract

COVID-19 has emerged as a highly contagious disease which has caused a devastating impact across the world with a very large number of infections and deaths. Timely and accurate testing is paramount to an effective response to this pandemic as it helps identify infections and therefore mitigate (isolate/cure) them. In this paper, we investigate this challenge and contribute by presenting a blockchain-based solution that incorporates self-sovereign identity, re-encryption proxies, and decentralized storage, such as the interplanetary file systems (IPFS). Our solution implements digital medical passports (DMP) and immunity certificates for COVID-19 test-takers. We present smart contracts based on the Ethereum blockchain written and tested successfully to maintain a digital medical identity for test-takers that help in a prompt trusted response directly by the relevant medical authorities. We reduce the response time of the medical facilities, alleviate the spread of false information by using immutable trusted blockchain, and curb the spread of the disease through DMP. We present a detailed description of the system design, development, and evaluation (cost and security analysis) for the proposed solution. Since our code leverages the use of the on-chain events, the cost of our design is almost negligible. We have made our smart contract codes publicly available on Github.

Voting is one of the fundamental pillars of modern democracy. Continuous efforts have been made to strengthen the processes and methods involved to achieve verifiable, transparent voting systems. In recent years, blockchain has been increasingly used to address multi-dimensional challenges across widespread application domains including healthcare, finance and e-voting. However, achieving an efficient solution via use of blockchain requires consideration of a range of factors such as block generation rate, transaction speed, and block size which have a profound role in determining the overall performance of the solution. Current research into this aspect of blockchain is focused on Bitcoin with the objective to achieve comparable performance as of existing online payment systems such as VISA. However, there exists a gap in literature with respect to investigating performance constraints for wider application domains. In this paper, we present our efforts to address this gap by presenting a detailed study into performance and scalability constraints for an e-voting system. Specifically, we conducted rigorous experimentation with permissioned and permissionless blockchain settings across different scenarios with respect to voting population, block size, block generation rate and transaction speed. The experiments highlighted interesting observations with respect to the impact of these parameters on the overall efficiency and scalability of the e-voting model including trade-offs between different parameters as well as security and performance.

Today's smartphones are equipped with a large number of powerful value-added sensors and features such as a low power Bluetooth sensor, powerful embedded sensors such as the digital compass, accelerometer, GPS sensors, Wi-Fi capabilities, microphone, humidity sensors, health tracking sensors, and a camera, etc. These value-added sensors have revolutionized the lives of the human being in many ways such, as tracking the health of the patients and movement of doctors, tracking employees movement in large manufacturing units, and monitoring the environment, etc. These embedded sensors could also be used for large-scale personal, group, and community sensing applications especially tracing the spread of certain diseases. Governments and regulators are turning to use these features to trace the people thought to have symptoms of certain diseases or virus e.g. COVID-19. The outbreak of COVID-19 in December 2019, has seen a surge of the mobile applications for tracing, tracking and isolating the persons showing COVID-19 symptoms to limit the spread of disease to the larger community. The use of embedded sensors could disclose private information of the users thus potentially bring threat to the privacy and security of users. In this paper, we analyzed a large set of smartphone applications that have been designed to contain the spread of the COVID-19 virus and bring the people back to normal life. Specifically, we have analyzed what type of permission these smartphone apps require, whether these permissions are necessary for the track and trace, how data from the user devices is transported to the analytic center, and analyzing the security measures these apps have deployed to ensure the privacy and security of users.

Internet of Things (IoT) represent a network of resource-constrained sensor devices connected through the open Internet which are susceptible to misuse by intruders. Proliferation of IoT across diverse application domains renders their security critical to ensure normal service delivery by such infrastructures. Traditional standalone intrusion detection systems are tasked with monitoring device behaviours to identify malicious activities. These systems not only require extensive network and system resources but also cause delays in detecting a malicious actor due to unavailability of a comprehensive view of the intruder's activities. Collaboration among IoT devices enables considering knowledge from a collection of host and network devices to achieve improved detection accuracy in a timely manner. However, collaboration introduces the challenge of energy efficiency and event processing which is particularly significant for resource-constrained devices. In this paper, we present an intrusion detection framework for IoT (COLIDE) that leverages collaboration among resource-constrained sensor devices and border nodes for effective and timely detection of intruders. The paper presents a detailed description of the proposed framework along with its formal description and analysis to assess its effectiveness for a typical IoT system. We implemented the COLIDE framework with Contiki OS and conducted thorough experimentation to evaluate its performance. This evaluation demonstrates efficiency of COLIDE framework with respect to energy and processing overheads achieving effectiveness within an IoT system.

No abstract