Conventional Internet of Things (IoT) ecosystems involve data streaming from sensors, through Fog devices to a centralized Cloud server. Issues that arise include privacy concerns due to third party management of Cloud servers, single points of failure, a bottleneck in data flows and difficulties in regularly updating firmware for millions of smart devices from a point of security and maintenance perspective. Blockchain technologies avoid trusted third parties and safeguard against a single point of failure and other issues. This has inspired researchers to investigate blockchain’s adoption into IoT ecosystem. In this paper, recent state-of-the-arts advances in blockchain for IoT, blockchain for Cloud IoT and blockchain for Fog IoT in the context of eHealth, smart cities, intelligent transport and other applications are analyzed. Obstacles, research gaps and potential solutions are also presented.

A survey on the adoption of blockchain in IoT: challenges and solutions

Blockchain (eg, Bitcoin and Ethereum) has drawn much attention and has been widely-deployed in recent years However, blockchain scalability is emerging as a challenging issue This paper outlines the existing solutions to blockchain scalability, which can be classified into two categories: first layer and second layer solutions First layer solutions propose modifications to the blockchain (ie, changing the blockchain structure, such as block size) while second layer solutions propose mechanisms that are implemented outside of the blockchain In particular, we focus on sharding as a promising first layer solution to the scalability issue; the basic idea behind sharding is to divide the blockchain network into multiple committees, each processing a separate set of transactions More specifically, (a) we propose a taxonomy based on committee formation and intra-committee consensus; and (b) we compare the main existing sharding-based blockchain protocols We also present a performance-based comparative analysis (ie, throughput and latency), of the advantages, and disadvantages in existing scalability solutions

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Scaling Blockchains: A Comprehensive Survey

Blockchain is a revolutionary technology that is making a great impact on modern society due to its transparency, decentralization, and security properties. Blockchain gained considerable attention due to its very first application of Cryptocurrencies e.g., Bitcoin. In the near future, Blockchain technology is determined to transform the way we live, interact, and perform businesses. Recently, academics, industrialists, and researchers are aggressively investigating different aspects of Blockchain as an emerging technology. Unlike other Blockchain surveys focusing on either its applications, challenges, characteristics, or security, we present a comprehensive survey of Blockchain technology’s evolution, architecture, development frameworks, and security issues. We also present a comparative analysis of frameworks, classification of consensus algorithms, and analysis of security risks & cryptographic primitives that have been used in the Blockchain so far. Finally, this paper elaborates on key future directions, novel use cases and open research challenges, which could be explored by researchers to make further advances in this field.

A Survey on Blockchain Technology: Evolution, Architecture and Security

A survey of consensus algorithms in public blockchain systems for crypto-currencies

Wireless resources, such as spectrum, computation, infrastructures and so on, are critical in 6G and beyond. Dynamic Resource Sharing (DRS), which improves the resource utilization compared to the static and fixed resource allocation, thus needs to be further exploited. Blockchain and AI are two promising techniques for DRS in 6G and beyond. In this article, a blockchain and AI-empow-ered DRS architecture is proposed, where block-chain is used to achieve the functionalities in DRS with improved distribution, security and automation, and AI is implemented to improve the performance of pattern recognition and decision-making in DRS. Finally, a case study where dynamic spectrum sharing is implemented within the proposed architecture, and deep reinforcement learning is used and shown to optimize the profit ratio of the users.

Blockchain and Artificial Intelligence for Dynamic Resource Sharing in 6G and Beyond

In recent years, the scalability issue of blockchain protocols has received huge attention. Sharding is one of the most promising solutions to scale blockchain. The basic idea behind sharding is to divide the blockchain network into multiple committees where each committee processes a separate set of transactions. In this paper, we propose a mathematical model to analyze the security of sharding-based blockchain protocols. Moreover, we analyze well-known sharding protocols including RapidChain, OmniLedger, and Zilliga to validate our model. The key contribution of our paper is to bound the failure probability for one committee and so for each epoch using probability bounds for sums of upper-bounded hypergeometric and binomial distributions. In addition, this paper contribution answers the following fundamental question: “how to keep the failure probability, for a given sharding protocol, smaller than a predefined threshold?”. Three probability bounds are used: Chebyshev, Hoeffding, and Chvatal. To illustrate the effectiveness of our proposed model, we conduct a numerical and comparative analysis of the proposed bounds.

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New Mathematical Model to Analyze Security of Sharding-Based Blockchain Protocols

In the context of blockchain protocols, each node stores the entire state of the network and processes all transactions. This ensures high security but limits scalability. Sharding is one of the most promising solutions to scale blockchain. In this paper, we analyze the security of three Sharding-based protocols using tail inequalities. The key contribution of our paper is to upper bound the failure probability for one committee and so for each epoch using tail inequalities for sums of bounded hypergeometric and binomial distributions. Two tail inequalities are used: Hoeffding and Chvatal. The first tail (Hoeffding inequality) is much more precise bound. The second (Chvatal inequality) is an exponential bound; it is simple to compute but weaker bound compared to Hoeffding. Our contribution is an alternative solution when the failure probability simulations are impractical. To show the effectiveness of our analysis, we perform simulations of the exponential bound.

A Methodology for a Probabilistic Security Analysis of Sharding-Based Blockchain Protocols

Cryptocurrencies (e.g., Bitcoin and Ethereum), which promise to become the future of money transactions, are mainly implemented with blockchain technology. However, blockchain suffers from scalability issues. Sharding is the leading solution for blockchain scalability. Sharding splits the blockchain network into sub-chains called shards/committees. Each shard processes a sub-set of transactions, rather than the entire network processing all transactions. This raises security issues for sharding-based blockchain protocols. In this paper, we propose a novel methodology to analyze the security of these protocols (e.g., OmniLedger and RapidChain). In particular, this methodology estimates the failure probability of one sharding round taking into consideration the failure probabilities of all shards. To illustrate the effectiveness of the estimated failure probability, we conduct a numerical analysis of our methodology based on a huge number of trials. Finally, we compute confidence intervals to accurately estimate the failure probability and compare our methodology with existing approaches.

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Mustapha Samih

Papers

Scaling Blockchains: A Comprehensive Survey

New Mathematical Model to Analyze Security of Sharding-Based Blockchain Protocols

A Methodology for a Probabilistic Security Analysis of Sharding-Based Blockchain Protocols

A Novel Methodology-Based Joint Hypergeometric Distribution to Analyze the Security of Sharded Blockchains