The Bitcoin cryptocurrency records its transactions in a public log called the blockchain. Its security rests critically on the distributed protocol that maintains the blockchain, run by participants called miners. Conventional wisdom asserts that the protocol is incentive-compatible and secure against colluding minority groups, i.e., it incentivizes miners to follow the protocol as prescribed. We show that the Bitcoin protocol is not incentive-compatible. We present an attack with which colluding miners obtain a revenue larger than their fair share. This attack can have significant consequences for Bitcoin: Rational miners will prefer to join the selfish miners, and the colluding group will increase in size until it becomes a majority. At this point, the Bitcoin system ceases to be a decentralized currency. Selfish mining is feasible for any group size of colluding miners. We propose a practical modification to the Bitcoin protocol that protects against selfish mining pools that command less than 1 4 of the resources. This threshold is lower than the wrongly assumed 1 2 bound, but better than the current reality where a group of any size can compromise the system.
Decentralized digital currencies have been proposed before Bitcoin, starting with @cite_21 and followed by peer-to-peer currencies, e.g. @cite_13 @cite_15 ; see @cite_22 @cite_6 for short surveys. None of these are centered around a global log; therefore, their techniques and challenges are unrelated to this work.
@cite_22 @cite_21 @cite_6 @cite_15 @cite_13
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Bitcoin is the world's first decentralized digital currency. Its main technical innovation is the use of a blockchain and hash-based proof of work to synchronize transactions and prevent double-spending the currency. While the qualitative nature of this system is well understood, there is widespread confusion about its quantitative aspects and how they relate to attack vectors and their countermeasures. In this paper we take a look at the stochastic processes underlying typical attacks and their resulting probabilities of success. Bitcoin, a peer-to-peer payment system and digital currency, is often involved in illicit activities such as scamming, ransomware attacks, illegal goods trading, and thievery. At the time of writing, the Bitcoin ecosystem has not yet been mapped and as such there is no estimate of the share of illicit activities. This paper provides the first estimation of the portion of cyber-criminal entities in the Bitcoin ecosystem. Our dataset consists of 854 observations categorised into 12 classes (out of which 5 are cybercrime-related) and a total of 100,000 uncategorised observations. The dataset was obtained from the data provider who applied three types of clustering of Bitcoin transactions to categorise entities: co-spend, intelligence-based, and behaviour-based. Thirteen supervised learning classifiers were then tested, of which four prevailed with a cross-validation accuracy of 77.38 , 76.47 , 78.46 , 80.76 respectively. From the top four classifiers, Bagging and Gradient Boosting classifiers were selected based on their weighted average and per class precision on the cybercrime-related categories. Both models were used to classify 100,000 uncategorised entities, showing that the share of cybercrime-related is 29.81 according to Bagging, and 10.95 according to Gradient Boosting with number of entities as the metric. With regard to the number of addresses and current coins held by this type of entities, the results are: 5.79 and 10.02 according to Bagging; and 3.16 and 1.45 according to Gradient Boosting. Bitcoin cryptocurrency demonstrated the utility of global consensus across thousands of nodes, changing the world of digital transactions forever. In the early days of Bitcoin, the performance of its probabilistic proof-of-work (PoW) based consensus fabric, also known as blockchain, was not a major issue. Bitcoin became a success story, despite its consensus latencies on the order of an hour and the theoretical peak throughput of only up to 7 transactions per second. Bitcoin was recently introduced as a peer-to-peer electronic currency in order to facilitate transactions outside the traditional financial system. The core of Bitcoin, the Blockchain, is the history of the transactions in the system maintained by all miners as a distributed shared register. New blocks in the Blockchain contain the last transactions in the system and are added by miners after a block mining process that consists in solving a resource consuming proof-of-work (cryptographic puzzle). The reward is a motivation for mining process but also could be an incentive for attacks such as selfish mining. In this paper we propose a solution for one of the major problems in Bitcoin : selfish mining or block-withholding attack. This attack is conducted by adversarial or selfish miners in order to either earn undue rewards or waste the computational power of honest miners. Contrary to recent solutions, our solution, ZeroBlock, prevents block-withholding using a technique free of timestamp that can be forged. Moreover, we show that our solution is compliant with nodes churn.