Biblio

The term cryptocurrency refers to a digital currency based on cryptographic concepts that have become popular in recent years. Bitcoin is a decentralized cryptocurrency that uses the distributed append-only public database known as blockchain to record every transaction. The incentive-compatible Proof-of-Work (PoW)-centered decentralized consensus procedure, which is upheld by the network's nodes known as miners, is essential to the safety of bitcoin. Interest in Bitcoin appears to be growing as the market continues to rise. Bitcoins and Blockchains have identical fundamental ideas, which are briefly discussed in this paper. Various studies discuss blockchain as a revolutionary innovation that has various applications, spanning from bitcoins to smart contracts, and also about it being a solution to many issues. Furthermore, many papers are reviewed here that not only look at Bitcoin’s fundamental underpinning technologies, such as Mixing and the Bitcoin Wallets but also at the flaws in it.

Bitcoin is a famously decentralized cryptocurrency. Bitcoin is excellent because it is a digital currency that provides convenience and security in transactions. Transaction security in Bitcoin uses a consensus involving a distributed system, the security of this system generates a hash sequence with a Proof of Work (PoW) mechanism. However, in its implementation, various attacks appear that are used to generate profits from the existing system. Attackers can use various types of methods to get an unfair portion of the mining income. Such attacks are commonly referred to as Mining attacks. Among which the famous is the Selfish Mining attack. In this study, we simulate the effect of changing decision matrix, attacker region, attacker hash rate on selfish miner attacks by using the opensource NS3 platform. The experiment aims to see the effect of using 1%, 10%, and 20% decision matrices with different attacker regions and different attacker hash rates on Bitcoin selfish mining income. The result of this study shows that regional North America and Europe have the advantage in doing selfish mining attacks. This advantage is also supported by increasing the decision matrix from 1%, 10%, 20%. The highest attacker income, when using decision matrix 20% in North America using 16 nodes on 0.3 hash rate with income 129 BTC. For the hash rate, the best result for a selfish mining attack is between 27% to 30% hash rate.

The architecture and functioning of the electricity markets are rapidly evolving in favour of solutions based on real-time data sharing and decentralised, distributed, renewable energy generation. Peer-to-peer (P2P) energy markets allow two individuals to transact with one another without the need of intermediaries, reducing the load on the power grid during peak hours. However, such a P2P energy market is prone to various cyber attacks. Blockchain technology has been proposed to implement P2P energy trading to support this change. One of the most crucial components of blockchain technology in energy trading is the consensus mechanism. It determines the effectiveness and security of the blockchain for energy trading. However, most of the consensus used in energy trading today are traditional consensus such as Proof-of-Work (PoW) and Practical Byzantine Fault Tolerance (PBFT). These traditional mechanisms cannot be directly adopted in P2P energy trading due to their huge computational power, low throughput, and high latency. Therefore, we propose the Block Alliance Consensus (BAC) mechanism based on Hashgraph. In a massive P2P energy trading network, BAC can keep Hashgraph's throughput while resisting Sybil attacks and supporting the addition and deletion of energy participants. The high efficiency and security of BAC and the blockchain-based energy trading platform are verified through experiments: our improved BAC has an average throughput that is 2.56 times more than regular BFT, 5 times greater than PoW, and 30% greater than the original BAC. The improved BAC has an average latency that is 41% less than BAC and 81% less than original BFT. Our energy trading blockchain (ETB)'s READ performance can achieve the most outstanding throughput of 1192 tps at a workload of 1200 tps, while WRITE can achieve 682 tps at a workload of 800 tps with a success rate of 95% and 0.18 seconds of latency.

Storing information in Blockchain has become in vogue in the Technical and Communication Industry with many major players jumping into the bandwagon. Two of the most prominent enablers for Blockchain are “Proof of Work” and “Proof of Stake”. Proof of work includes the members solving the complex problem without having a particular need for the solution (except as evidence, of course), which absorbs a large number of resources in turn. The proof of stake doesn’t require as many resources to enable Blockchain secure information store. Both methodologies have their advantages and their shortcomings. The article attempts to review the current literature and collate the results of the study to measure the performance of both the methodologies and to arrive at a consensus regarding either or both methodologies to implement Blockchain to store data. Post reviewing the performance aspects and security features of both Proofs of Stake and Proof of Work the reviewer attempts to arrive at a secure and better performing blended Blockchain methodology that has wide industry practical application.

Blockchain technology relies on a growing number of globally distributed ledgers known as blockchain. This technology was used for the creation of the cryptocurrency known as bitcoin that allows transactions to be carried out quickly and easily, without the need to use an intermediary "financial institution". The information is sent trough the protocols known as: PoW (Proof of Work) and PoS (Proof of Stake), which must guarantee confidentiality, integrity and availability of the information. The present work shows the result of a bibliographic review on the evolution of the blockchain, the PoW and PoS protocols; as well as the application of these within the framework of Ecuadorian legislation with emphasis on the evolution of risks of the PoW protocol.

A blockchain is a distributed ledger forming a distributed consensus on a history of transactions, and is the underlying technology for the Bitcoin cryptocurrency. However, its applications are far beyond the financial sector. The transaction verification process for cryptocurrencies is much slower than traditional digital transaction systems. One approach to increase transaction speed and scalability is to identify a solution that offers faster Proof of Work. In this paper, we propose a method for accelerating the process of Proof of Work based on parallel mining rather than solo mining. The goal is to ensure that no more than two or more miners put the same effort into solving a specific block. The proposed method includes a process for selection of a manager, distribution of work and a reward system. This method has been implemented in a test environment that contains all the characteristics needed to perform Proof of Work for Bitcoin and has been tested, using a variety of case scenarios, by varying the difficulty level and number of validators. Preliminary results show improvement in the scalability of Proof of Work up to 34% compared to the current system.

Proof-of-work (PoW) is an algorithmic tool used to secure networks by imposing a computational cost on participating devices. Unfortunately, traditional PoW schemes require that correct devices perform computational work perpetually, even when the system is not under attack. We address this issue by designing a general PoW protocol that ensures two properties. First, the network stays secure. In particular, the fraction of identities in the system that are controlled by an attacker is always less than 1/2. Second, our protocol's computational cost is commensurate with the cost of an attacker. That is, the total computational cost of correct devices is a linear function of the attacker's computational cost plus the number of correct devices that have joined the system. Consequently, if the network is attacked, we ensure security, with cost that grows linearly with the attacker's cost; and, in the absence of attack, our computational cost is small. We prove similar guarantees for bandwidth cost. Our results hold in a dynamic, decentralized system where participants join and depart over time, and where the total computational power of the attacker is up to a constant fraction of the total computational power of correct devices. We show how to leverage our results to address important security problems in distributed computing including: Sybil attacks, Byzantine Consensus, and Committee Election.