2,589 research outputs found
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
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