Tree-Chain: A Fast Lightweight Consensus Algorithm for IoT Applications

Blockchain has received tremendous attention in non-monetary applications including the Internet of Things (IoT) due to its salient features including decentralization, security, auditability, and anonymity. Most conventional blockchains rely on computationally expensive consensus algorithms, have limited throughput, and high transaction delays. In this paper, we propose tree-chain a scalable fast blockchain instantiation that introduces two levels of randomization among the validators: i) transaction level where the validator of each transaction is selected randomly based on the most significant characters of the hash function output (known as consensus code), and ii) blockchain level where validator is randomly allocated to a particular consensus code based on the hash of their public key. Tree-chain introduces parallel chain branches where each validator commits the corresponding transactions in a unique ledger. Implementation results show that tree-chain is runnable on low resource devices and incurs low processing overhead, achieving near real-time transaction settlement

MOF-BC: A Memory Optimized and Flexible BlockChain for Large Scale Networks

BlockChain (BC) immutability ensures BC resilience against modification or removal of the stored data. In large scale networks like the Internet of Things (IoT), however, this feature significantly increases BC storage size and raises privacy challenges. In this paper, we propose a Memory Optimized and Flexible BC (MOF-BC) that enables the IoT users and service providers to remove or summarize their transactions and age their data and to exercise the "right to be forgotten". To increase privacy, a user may employ multiple keys for different transactions. To allow for the removal of stored transactions, all keys would need to be stored which complicates key management and storage. MOF-BC introduces the notion of a Generator Verifier (GV) which is a signed hash of a Generator Verifier Secret (GVS). The GV changes for each transaction to provide privacy yet is signed by a unique key, thus minimizing the information that needs to be stored. A flexible transaction fee model and a reward mechanism is proposed to incentivize users to participate in optimizing memory consumption. Qualitative security and privacy analysis demonstrates that MOF-BC is resilient against several security attacks. Evaluation results show that MOF-BC decreases BC memory consumption by up to 25\% and the user cost by more than two orders of magnitude compared to conventional BC instantiations

On the Activity Privacy of Blockchain for IoT

Security is one of the fundamental challenges in the Internet of Things (IoT) due to the heterogeneity and resource constraints of the IoT devices. Device classification methods are employed to enhance the security of IoT by detecting unregistered devices or traffic patterns. In recent years, blockchain has received tremendous attention as a distributed trustless platform to enhance the security of IoT. Conventional device identification methods are not directly applicable in blockchain-based IoT as network layer packets are not stored in the blockchain. Moreover, the transactions are broadcast and thus have no destination IP address and contain a public key as the user identity, and are stored permanently in blockchain which can be read by any entity in the network. We show that device identification in blockchain introduces privacy risks as the malicious nodes can identify users' activity pattern by analyzing the temporal pattern of their transactions in the blockchain. We study the likelihood of classifying IoT devices by analyzing their information stored in the blockchain, which to the best of our knowledge, is the first work of its kind. We use a smart home as a representative IoT scenario. First, a blockchain is populated according to a real-world smart home traffic dataset. We then apply machine learning algorithms on the data stored in the blockchain to analyze the success rate of device classification, modeling both an informed and a blind attacker. Our results demonstrate success rates over 90\% in classifying devices. We propose three timestamp obfuscation methods, namely combining multiple packets into a single transaction, merging ledgers of multiple devices, and randomly delaying transactions, to reduce the success rate in classifying devices. The proposed timestamp obfuscation methods can reduce the classification success rates to as low as 20%

Lightweight Blockchain Framework for Location-aware Peer-to-Peer Energy Trading

Peer-to-Peer (P2P) energy trading can facilitate integration of a large number of small-scale producers and consumers into energy markets. Decentralized management of these new market participants is challenging in terms of market settlement, participant reputation and consideration of grid constraints. This paper proposes a blockchain-enabled framework for P2P energy trading among producer and consumer agents in a smart grid. A fully decentralized market settlement mechanism is designed, which does not rely on a centralized entity to settle the market and encourages producers and consumers to negotiate on energy trading with their nearby agents truthfully. To this end, the electrical distance of agents is considered in the pricing mechanism to encourage agents to trade with their neighboring agents. In addition, a reputation factor is considered for each agent, reflecting its past performance in delivering the committed energy. Before starting the negotiation, agents select their trading partners based on their preferences over the reputation and proximity of the trading partners. An Anonymous Proof of Location (A-PoL) algorithm is proposed that allows agents to prove their location without revealing their real identity. The practicality of the proposed framework is illustrated through several case studies, and its security and privacy are analyzed in detail

BlockChain: A distributed solution to automotive security and privacy

Interconnected smart vehicles offer a range of sophisticated services that benefit the vehicle owners, transport authorities, car manufacturers and other service providers. This potentially exposes smart vehicles to a range of security and privacy threats such as location tracking or remote hijacking of the vehicle. In this article, we argue that BlockChain (BC), a disruptive technology that has found many applications from cryptocurrencies to smart contracts, is a potential solution to these challenges. We propose a BC-based architecture to protect the privacy of the users and to increase the security of the vehicular ecosystem. Wireless remote software updates and other emerging services such as dynamic vehicle insurance fees, are used to illustrate the efficacy of the proposed security architecture. We also qualitatively argue the resilience of the architecture against common security attacks

Sleep Patterns among University Students and Insomnia Management in Primary Care Settings in Qatar: A Two-Phase Investigation

Insomnia is a public health concern that affects approximately a third of adult population worldwide. The aim of this research was to investigate insomnia and its management among university students and primary care centers in Qatar using quantitative and qualitative methods, respectively. The first phase of this research consisted of a cross-sectional quantitative survey to explore the pattern and quality of sleep among Qatar University (QU) students using the Pittsburgh Sleep Quality Index and the Sleep Hygiene Index. In the second phase, qualitative interviews were used to explore the perspectives of healthcare providers (HCPs) working at primary health care centers (PHCCs) regarding insomnia and its management. Approximately 70% of QU students reported scores consistent with poor sleep quality and 79% reported poor sleep hygiene. Students with good sleep hygiene compared to those with poor sleep hygiene were about four times more likely to have good sleep quality (OR= 3.66, 95% CI= 2.8 4.8, p < 0.001). The interviews with 19 HCPs generated five themes, including general perspectives on insomnia, view of primary healthcare as the setting for insomnia management, current practices for insomnia management at PHCCs, HCPs’ role perception, and challenges facing insomnia management at PHCCs. The findings from this two-phase investigation revealed that insomnia is common among university students in Qatar and that it is associated with poor sleeping habits. HCPs at PHCCs expressed awareness of the magnitude of insomnia as a problem of public health significance but appeared to find its management challenging

Coronavirus disease 2019 (COVID-19): challenges and management of aerosol-generating procedures in dentistry

Embargo removed due to subject matter