A Private Bitcoin Payment Network with Reduced Transaction Fees and Confirmation Times

Since its introduction, Bitcoin cryptocurrency has revolutionized the way payment systems can be designed in a purely distributed manner through its novel Blockchain data structure. While Bitcoin has opened new opportunities, it has been long criticized for its slow transaction confirmation times and high transaction fees. To address this issue, one of the recently emerging solutions is to build a payment channel network (PCN) on top of Bitcoin where the transactions can be made without writing to blockchain. Specifically, a PCN is a network where the users connect either directly or indirectly to send payments to each other in a trustless way. Being backed by the blockchain technology, PCNs satisfy a robust and flexible medium where the exchange of assets become frictionless and thus enable faster transactions with negligible fees. For example, Lightning Network, a second layer network built on top of the Bitcoin network, is being actively developed and it makes Bitcoin possible to be used for micro-payments. However, PCNs including LN bring new challenges on centralization, robustness and privacy as they accept more users. Such problems threaten the very idea of decentralization that comes with blockchain. Therefore, in this dissertation we target the problem of PCN topology formation that will come with ideal features and continue to grow without violating such characteristics. Specifically, we focused on the design of methods for obtaining peer-to-peer (P2P) decentralized PCN topologies. Inspiring from the multi-commodity flow problem, we first developed an optimal solution to establish the perfect PCN topology by utilizing mixed-integer programming. We solve this problem for the required capacities within the network for uninterrupted operation. Second, as mixed integer programming is proved to be NP-compete in complexity, we developed a heuristic optimization approach to take the solution into the polynomial-time domain. Third, to further enable scalability, we developed a new sub-optimal heuristic algorithm using the Dijkstra\u27s shortest path algorithm. Finally, we turned our attention to privacy preservation problem for transactions and augmented each of the proposed approaches with privacy guarantees. Evaluation results indicate that our proposed approaches can enable desirable PCN topology features while respecting the privacy requirements

Deanonymizing tor hidden service users through bitcoin transactions analysis

With the rapid increase of threats on the Internet, people are continuously seeking privacy and anonymity. Services such as Bitcoin and Tor were introduced to provide anonymity for online transactions and Web browsing. Due to its pseudonymity model, Bitcoin lacks retroactive operational security, which means historical pieces of information could be used to identify a certain user. We investigate the feasibility of deanonymizing users of Tor hidden services who rely on Bitcoin as a method of payment. In particular, we correlate the public Bitcoin addresses of users and services with their corresponding transactions in the Blockchain. In other words, we establish a provable link between a Tor hidden service and its user by simply showing a transaction between their two corresponding addresses. This subtle information leakage breaks the anonymity of users and may have serious privacy consequences, depending on the sensitivity of the use case. To demonstrate how an adversary can deanonymize hidden service users by exploiting leaked information from Bitcoin over Tor, we carried out a real-world experiment as a proof-of-concept. First, we collected public Bitcoin addresses of Tor hidden services from their .onion landing pages. Out of 1.5K hidden services we crawled, we found 88 unique Bitcoin addresses that have a healthy economic activity in 2017. Next, we collected public Bitcoin addresses from two channels of online social networks, namely, Twitter and the BitcoinTalk forum. Out of 5B tweets and 1M forum pages, we found 4.2K and 41K unique online identities, respectively, along with their public personal information and Bitcoin addresses. We then expanded the lists of Bitcoin addresses using closure analysis, where a Bitcoin address is used to identify a set of other addresses that are highly likely to be controlled by the same user. This allowed us to collect thousands more Bitcoin addresses for the users. By analyzing the transactions in the Blockchain, we were able to link up to 125 unique users to various hidden services, including sensitive ones, such as The Pirate Bay, Silk Road, and WikiLeaks. Finally, we traced concrete case studies to demonstrate the privacy implications of information leakage and user deanonymization. In particular, we show that Bitcoin addresses should always be assumed as compromised and can be used to deanonymize users

Investigating transactions in cryptocurrencies

This thesis presents techniques to investigate transactions in uncharted cryptocur- rencies and services. Cryptocurrencies are used to securely send payments on- line. Payments via the first cryptocurrency, Bitcoin, use pseudonymous addresses that have limited privacy and anonymity guarantees. Research has shown that this pseudonymity can be broken, allowing users to be tracked using clustering and tag- ging heuristics. Such tracking allows crimes to be investigated. If a user has coins stolen, investigators can track addresses to identify the destination of the coins. This, combined with an explosion in the popularity of blockchain, has led to a vast increase in new coins and services. These offer new features ranging from coins focused on increased anonymity to scams shrouded as smart contracts. In this study, we investigated the extent to which transaction privacy has improved and whether users can still be tracked in these new ecosystems. We began by analysing the privacy-focused coin Zcash, a Bitcoin-forked cryptocurrency, that is consid- ered to have strong anonymity properties due to its background in cryptographic research. We revealed that the user anonymity set can be considerably reduced using heuristics based on usage patterns. Next, we analysed cross-chain transac- tions collected from the exchange ShapeShift, revealing that users can be tracked as they move across different ledgers. Finally, we present a measurement study on the smart-contract pyramid scheme Forsage, a scam that cycled $267 million USD (of Ethereum) within its first year, showing that at least 88% of the participants in the scheme suffered a loss. The significance of this study is the revelation that users can be tracked in newer cryptocurrencies and services by using our new heuristics, which informs those conducting investigations and developing these technologies

A Survey on Consensus Mechanisms and Mining Strategy Management in Blockchain Networks

© 2013 IEEE. The past decade has witnessed the rapid evolution in blockchain technologies, which has attracted tremendous interests from both the research communities and industries. The blockchain network was originated from the Internet financial sector as a decentralized, immutable ledger system for transactional data ordering. Nowadays, it is envisioned as a powerful backbone/framework for decentralized data processing and data-driven self-organization in flat, open-access networks. In particular, the plausible characteristics of decentralization, immutability, and self-organization are primarily owing to the unique decentralized consensus mechanisms introduced by blockchain networks. This survey is motivated by the lack of a comprehensive literature review on the development of decentralized consensus mechanisms in blockchain networks. In this paper, we provide a systematic vision of the organization of blockchain networks. By emphasizing the unique characteristics of decentralized consensus in blockchain networks, our in-depth review of the state-of-the-art consensus protocols is focused on both the perspective of distributed consensus system design and the perspective of incentive mechanism design. From a game-theoretic point of view, we also provide a thorough review of the strategy adopted for self-organization by the individual nodes in the blockchain backbone networks. Consequently, we provide a comprehensive survey of the emerging applications of blockchain networks in a broad area of telecommunication. We highlight our special interest in how the consensus mechanisms impact these applications. Finally, we discuss several open issues in the protocol design for blockchain consensus and the related potential research directions

Blockchain analysis of the Bitcoin market

In this paper, we provide detailed analyses of the Bitcoin network and its main participants. We build a novel database using a large number of public and proprietary sources to link Bitcoin addresses to real entities and develop an extensive suite of algorithms to extract information about the behavior of the main market participants. We conduct three major pieces of analysis of the Bitcoin eco-system. First, we analyze the transaction volume and network structure of the main participants on the blockchain. Second, we document the concentration and regional composition of the miners which are the backbone of the verification protocol and ensure the integrity of the blockchain ledger. Finally, we analyze the ownership concentration of the largest holders of Bitcoin