A cryptocurrency is a decentralized digital currency that is designed for secure and private asset transfer and storage. As a currency, it should be difficult to counterfeit and double-spend. In this paper, we review and analyze the major security and privacy issues of Bitcoin. In particular, we focus on its underlying foundation, blockchain technology. First, we present a comprehensive background of Bitcoin and the preliminary on security. Second, the major security threats and countermeasures of Bitcoin are investigated. We analyze the risk of double-spending attacks, evaluate the probability of success in performing the attacks and derive the profitability for the attacker to perform such attacks. Third, we analyze the underlying Bitcoin peer-to-peer network security risks and Bitcoin storage security. We compare three types of Bitcoin wallets in terms of security, type of services and their trade-offs. Finally, we discuss the security and privacy features of alternative cryptocurrencies and present an overview of emerging technologies today. Our results can help Bitcoin users to determine a trade-off between the risk of double-spending attempts and the transaction time delay or confidence before accepting transactions. These results can also assist miners to develop suitable strategies to get involved in the mining process and maximize their profits.
In early 2000, Digital Gold Currency (DGC), a currency backed by gold, gained some popularity. DGC is considered to be a second-generation digital currency. It is issued by some companies that enable users to pay each other in units similar to those of gold bullion. Examples include iGolder, gbullion, and e-Gold. Although DGC seemed to have a bright future, it lost popularity due to its centralized structure. Politics may have also played a role in its declining popularity. Companies that provided DGC were forced to shut down by the federal government due to their inability to comply with the government regulations @cite_41 .
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This comprehensive source of information about financial fraud delivers a mature approach to fraud detection and prevention. It brings together all important aspect of analytics used in investigating modern crime in financial markets and uses R for its statistical examples. It focuses on crime in financial markets as opposed to the financial industry, and it highlights technical aspects of crime detection and prevention as opposed to their qualitative aspects. For those with strong analytic skills, this book unleashes the usefulness of powerful predictive and prescriptive analytics in predicting and preventing modern crime in financial markets. Interviews and case studies provide context and depth to examples Case studies use R, the powerful statistical freeware tool Useful in classroom and professional contexts