Biblio

There are some registry agreements that may be appropriate for the Internet of Things (IoT), including Bitcoin, Hyperledger Fabric and IOTA. This article presents quickly and examines them in terms of the progress of Internet applications. Block-dependent IoT applications can consolidate the chain's rationale (smart contracts) and front-end, portable or front-end web applications. We present three possible designs for BC IoT front-end applications. They vary depending on the Bitcoin block chain customer (neighborhood gadget, remote server) and the key location needed to manage active exchanges. The vital requirements of these projects, which use Bitcoin to organize constructive exchanges, are the volumes of information, the area and time of the complete block and block block, and the entry of the Bitcoin store. The implications of these surveys show that it is unlikely that a full Bitcoin distributor will continue to operate reliably with a mandatory IoT gadget. Then, designing with remote Bitcoin customers is, in all respects, a suitable methodology in which there are two minor alternatives and vary in key storage / management. Similarly, we recommend using the design with a unique match between the IoT gadget and the remote blockchain client to reduce system activity and improve security. We hope you also have the ability to operate with versatile verses with low control and low productivity. Our review eliminates the contradictions between synthesis methodologies, but the final choice for a particular registration agreement and the original technique completely depends on the proposed use case.

Bitcoin is a decentralized digital currency whose transactions are recorded in a common ledger, so called blockchain. Due to the anonymity and lack of law enforcement, Bitcoin has been misused in darknet markets which deal with illegal products, such as drugs and weapons. Therefore from the security forensics aspect, it is demanded to establish an approach to identify newly emerged darknet markets' transactions and addresses. In this paper, we thoroughly analyze Bitcoin transactions and addresses related to darknet markets and propose a novel identification method of darknet markets' addresses. To improve the identification performance, we propose a voting based method which decides the labels of multiple addresses controlled by the same user based on the number of the majority label. Through the computer simulation with more than 200K Bitcoin addresses, it was shown that our voting based method outperforms the nonvoting based one in terms of precision, recal, and F1 score. We also found that DNM's addresses pay higher fees than others, which significantly improves the classification.

Bitcoin [1] as a popular digital currency has been a target of theft and other illegal activities. Key to the forensic investigation is to identify bitcoin addresses involved in bitcoin transfers. This paper presents a framework, FABT, for forensic analysis of bitcoin transactions by identifying suspicious bitcoin addresses. It formalizes the clues of a given case as transaction patterns defined over a comprehensive set of features. FABT converts the bitcoin transaction data into a formal model, called Bitcoin Transaction Net (BTN). The traverse of all bitcoin transactions in the order of their occurrences is captured by the firing sequence of all transitions in the BTN. We have applied FABT to identify suspicious addresses in the Mt.Gox case. A subgroup of the suspicious addresses has been found to share many characteristics about the received/transferred amount, number of transactions, and time intervals.

The anonymity and decentralization of Bitcoin make it widely accepted in illegal transactions, such as money laundering, drug and weapon trafficking, gambling, to name a few, which has already caused significant security risk all around the world. The obvious de-anonymity approach that matches transaction addresses and users is not possible in practice due to limited annotated data set. In this paper, we divide addresses into four types, exchange, gambling, service, and general, and propose targeted addresses identification algorithms with high fault tolerance which may be employed in a wide range of applications. We use network representation learning to extract features and train imbalanced multi-classifiers. Experimental results validated the effectiveness of the proposed method.

Bitcoin is a cryptocurrency which acts as an application protocol that works on top of the IP protocol. This paper focuses on distinct Bitcoin security features, including security services, mechanisms, and algorithms. Further, we propose a well-defined security functional architecture to minimize security risks. The security features and requirements of Bitcoin have been structured in layers.

A threshold signature scheme enables distributed signing among n players such that any subgroup of size \$t+1\$ can sign, whereas any group with t or fewer players cannot. While there exist previous threshold schemes for the ECDSA signature scheme, we are the first protocol that supports multiparty signatures for any \$t łeq n\$ with an efficient dealerless key generation. Our protocol is faster than previous solutions and significantly reduces the communication complexity as well. We prove our scheme secure against malicious adversaries with a dishonest majority. We implemented our protocol, demonstrating its efficiency and suitability to be deployed in practice.

This workshop aims to develop an agenda within the CHI community to address the emergence of blockchain, or distributed ledger technologies (DLTs). As blockchains emerge as a general purpose technology, with applications well beyond cryptocurrencies, DLTs present exciting challenges and opportunities for developing new ways for people and things to transact, collaborate, organize and identify themselves. Requiring interdisciplinary skills and thinking, the field of HCI is well placed to contribute to the research and development of this technology. This workshop will build a community for human-centred researchers and practitioners to present studies, critiques, design-led work, and visions of blockchain applications.

Bitcoin provides only pseudo-anonymous transactions, which can be exploited to link payers and payees – defeating the goal of anonymous payments. To thwart such attacks, several Bitcoin mixers have been proposed, with the objective of providing unlinkability between payers and payees. However, existing Bitcoin mixers can be regarded as either insecure or inefficient. We present Obscuro, a highly efficient and secure Bitcoin mixer that utilizes trusted execution environments (TEEs). With the TEE's confidentiality and integrity guarantees for code and data, our mixer design ensures the correct mixing operations and the protection of sensitive data (i.e., private keys and mixing logs), ruling out coin theft and address linking attacks by a malicious service provider. Yet, the TEE-based implementation does not prevent the manipulation of inputs (e.g., deposit submissions, blockchain feeds) to the mixer, hence Obscuro is designed to overcome such limitations: it (1) offers an indirect deposit mechanism to prevent a malicious service provider from rejecting benign user deposits; and (2) scrutinizes blockchain feeds to prevent deposits from being mixed more than once (thus degrading anonymity) while being eclipsed from the main blockchain branch. In addition, Obscuro provides several unique anonymity features (e.g., minimum mixing set size guarantee, resistant to dropping user deposits) that are not available in existing centralized and decentralized mixers. Our prototype of Obscuro is built using Intel SGX and we demonstrate its effectiveness in Bitcoin Testnet. Our implementation mixes 1000 inputs in just 6.49 seconds, which vastly outperforms all of the existing decentralized mixers.

Bitcoin mixing services improve anonymity by breaking the connection between Bitcoin addresses. In the darkweb environment, many illegal trades, such as in drugs or child pornography, avoid their transactions being traced by exploiting mixing services. Therefore, de-mixing algorithms are needed to identify illegal financial flows and to reduce criminal activity. Unfortunately, to the best of our knowledge, few studies on analyzing mixing services and de-anonymizing transactions have been proposed. In this paper, we conduct an in-depth analysis of real-world mixing services, and propose a de-mixing algorithm for Helix, one of the most widely used Bitcoin mixing services. The proposed algorithm de-anonymizes the relationship between the input and output addresses of mixing services by exploiting the static and dynamic parameters of mixing services. Our experiment showed that, we could identify the relationships between the input and output addresses of the Helix mixing service with a 99.14% accuracy rate.

Selfish mining is a well-known mining attack strategy discovered by Eyal and Sirer in 2014. After that, the attackers' strategy has been further discussed by many other works, which analyze the strategy and behavior of a single attacker. The extension of the strategy research is greatly restricted by the assumption that there is only one attacker in the blockchain network, since, in many cases, a proof of work blockchain has multiple attackers. The attackers can be independent of others instead of sharing information and attacking the blockchain as a whole. In this paper, we will establish a new model to analyze the miners' behavior in a proof of work blockchain with multiple attackers. Based on our model, we extend the attackers' strategy by proposing a new strategy set publish-n. Meanwhile, we will also review other attacking strategies such as selfish mining and stubborn mining in our model to explore whether these strategies work or not when there are multiple attackers. The performances of different strategies are compared using relative stale block rate of the attackers. In a proof of work blockchain model with two attackers, strategy publish-n can beat selfish mining by up to 26.3%.

Known for powering cryptocurrencies such as Bitcoin and Ethereum, blockchain is seen as a disruptive technology capable of revolutionizing a wide variety of domains, ranging from finance to governance, by offering superior security, reliability, and transparency founded upon a decentralized and democratic computational model. In this tutorial, we first present the original Bitcoin design, along with Ethereum and Hyperledger, and reflect on their design choices through the academic lens. We further provide an overview of potential applications and associated research challenges, as well as a survey of ongoing research directions related to byzantine fault-tolerance consensus protocols. We highlight the new opportunities blockchain creates for building the next generation of secure middleware platforms and explore the possible interplay between AI and blockchains, or more specifically, how blockchain technology can enable the notion of "decentralized intelligence." We conclude with a walkthrough demonstrating the process of developing a decentralized application using a popular Smart Contract language (Solidity) over the Ethereum platform

Bitcoin exchanges rely heavily on traditional intrusion detection system to secure their system. However, this reliance has proven to be high risk, since Bitcoin and other blockchain-based transactions are not easily reversible. Many of the attacks have shown that the traditional intrusion detection system is not enough to safeguard against all possible attacks, and most importantly, in some cases, it takes a long time to assess the damage. In this paper, we first describe three types of intrusion models in Bitcoin exchanges and propose a detection and mitigation system using blockchain analysis for each. The proposed detection and mitigation system exploit the decentralized and public nature of Bitcoin blockchain to complement the existing traditional intrusion detection system as a fail-safe. The proposed method provides real-time intrusion detection capability that the existing work cannot provide. Although the proposed method is specifically for Bitcoin blockchain, similar ideas can be extended to other proof-of-work based blockchain cryptocurrencies.

Despite the very high volatility of the cryptocurrency markets, the interest in the development and adaptation of existing cryptocurrencies such as Bitcoin as well as new distributed ledger technologies is increasing. Therefore, understanding the security and vulnerability issues of such blockchain systems plays a critical role. In this work, we propose a configurable distributed simulation framework for analyzing Bitcoin-like blockchain systems which are based on Proof-of-Work protocols. The simulator facilitates investigating security properties of blockchain systems by enabling users to configure several characteristics of the blockchain network and executing different attack scenarios, such as double-spending attacks and flood attacks and observing the effects of the attacks on the blockchain network.

Blockchain networks have been claimed to have the potential of fundamentally changing the way humans perform economic transactions with each other. In such networks, trust-enabling agents and activities, that were traditionally arranged in a centralized fashion, are replaced by a network of nodes which collectively yet independently witness and establish the non-repudiability of transactions. Most often, a proof-of-work (PoW) requirement ensures that participants invest resources for joining the network, incentivizing conformance to the network rules, while making it highly infeasible for malicious agents to construct an alternative version of the transaction history. While research on security and efficiency aspects of blockchain networks is already being conducted, there is still work to be done to understand how different external and internal conditions guarantee or threaten their sustainability, i.e., their continuous operation. Focusing on public PoW-based blockchain platforms, in this paper we sketch an abstract model that is aimed at supporting comprehension and qualitative reasoning about the factors that affect sustainability of a blockchain network.

We introduce BitML, a domain-specific language for specifying contracts that regulate transfers of bitcoins among participants, without relying on trusted intermediaries. We define a symbolic and a computational model for reasoning about BitML security. In the symbolic model, participants act according to the semantics of BitML, while in the computational model they exchange bitstrings, and read/append transactions on the Bitcoin blockchain. A compiler is provided to translate contracts into standard Bitcoin transactions. Participants can execute a contract by appending these transactions on the Bitcoin blockchain, according to their strategies. We prove the correctness of our compiler, showing that computational attacks on compiled contracts are also observable in the symbolic model.

Bitcoin is the most famous cryptocurrency currently operating with a total marketcap of almost 7 billion USD. This innovation stands strong on the feature of pseudo anonymity and strives on its innovative de-centralized architecture based on the Blockchain. The Blockchain is a distributed ledger that keeps a public record of all the transactions processed on the bitcoin protocol network in full transparency without revealing the identity of the sender and the receiver. Over the course of 2016, cryptocurrencies have shown some instances of abuse by criminals in their activities due to its interesting nature. Darknet marketplaces are increasing the volume of their businesses in illicit and illegal trades but also cryptocurrencies have been used in cases of extortion, ransom and as part of sophisticated malware modus operandi. We tackle these challenges by developing an analytical capability that allows us to map relationships on the blockchain and filter crime instances in order to investigate the abuse in law enforcement local environment. We propose a practical bitcoin analytical process and an analyzing system that stands alone and manages all data on the blockchain in real-time with tracing and visualizing techniques rendering transactions decipherable and useful for law enforcement investigation and training. Our system adopts combination of analyzing methods that provides statistics of address, graphical transaction relation, discovery of paths and clustering of already known addresses. We evaluated our system in the three criminal cases includes marketplace, ransomware and DDoS extortion. These are practical training in law enforcement, then we determined whether our system could help investigation process and training.

As the most successful cryptocurrency to date, Bitcoin constitutes a target of choice for attackers. While many attack vectors have already been uncovered, one important vector has been left out though: attacking the currency via the Internet routing infrastructure itself. Indeed, by manipulating routing advertisements (BGP hijacks) or by naturally intercepting traffic, Autonomous Systems (ASes) can intercept and manipulate a large fraction of Bitcoin traffic. This paper presents the first taxonomy of routing attacks and their impact on Bitcoin, considering both small-scale attacks, targeting individual nodes, and large-scale attacks, targeting the network as a whole. While challenging, we show that two key properties make routing attacks practical: (i) the efficiency of routing manipulation; and (ii) the significant centralization of Bitcoin in terms of mining and routing. Specifically, we find that any network attacker can hijack few (\textbackslashtextless;100) BGP prefixes to isolate 50% of the mining power-even when considering that mining pools are heavily multi-homed. We also show that on-path network attackers can considerably slow down block propagation by interfering with few key Bitcoin messages. We demonstrate the feasibility of each attack against the deployed Bitcoin software. We also quantify their effectiveness on the current Bitcoin topology using data collected from a Bitcoin supernode combined with BGP routing data. The potential damage to Bitcoin is worrying. By isolating parts of the network or delaying block propagation, attackers can cause a significant amount of mining power to be wasted, leading to revenue losses and enabling a wide range of exploits such as double spending. To prevent such effects in practice, we provide both short and long-term countermeasures, some of which can be deployed immediately.

We present cryptocurrency-based lottery protocols that do not require any collateral from the players. Previous protocols for this task required a security deposit that is O(N2) times larger than the bet amount, where N is the number of players. Our protocols are based on a tournament bracket construction, and require only O(logN) rounds. Our lottery protocols thus represent a significant improvement, both because they allow players with little money to participate, and because of the time value of money. The Ethereum-based implementation of our lottery is highly efficient. The Bitcoin implementation requires an O(2N) off-chain setup phase, which demonstrates that the expressive power of the scripting language can have important implications. We also describe a minimal modification to the Bitcoin protocol that would eliminate the exponential blowup.

This paper identifies trust factor and rewarding nature of bitcoin system, and analyzes bitcoin features which may facilitate bitcoin to emerge as a universal currency. Paper presents the gap between proposed theoretical-architecture and current practical-implementation of bitcoin system in terms of achieving decentralization, anonymity of users, and consensus. Paper presents three different ways in which a user can manage bitcoins. We attempt to identify the security risk and feasible attacks on these configurations of bitcoin management. We have shown that not all bitcoin wallets are safe against all possible types of attacks. Bitcoin core is only safest mode of operating bitcoin till date as it is secure against all feasible attacks, and is vulnerable only against block-chain rewriting.

When Bitcoin was first introduced to the world in 2008 by an enigmatic programmer going by the pseudonym Satoshi Nakamoto, it was billed as the world's first decentralized virtual currency. Offering the first credible incarnation of a digital currency, Bitcoin was based on the principal of peer to peer transactions involving a complex public address and a private key that only the owner of the coin would know. This paper will seek to investigate how the usage and value of Bitcoin is affected by current events in the cyber environment. Is an advancement in the digital security of Bitcoin reflected by the value of the currency and conversely does a major security breech have a negative effect? By analyzing statistical data of the market value of Bitcoin at specific points where the currency has fluctuated dramatically, it is believed that trends can be found. This paper proposes that based on the data analyzed, the current integrity of the Bitcoin security is trusted by general users and the value and usage of the currency is growing. All the major fluctuations of the currency can be linked to significant events within the digital security environment however these fluctuations are beginning to decrease in frequency and severity. Bitcoin is still a volatile currency but this paper concludes that this is a result of security flaws in Bitcoin services as opposed to the Bitcoin protocol itself.

With the accelerated iteration of technological innovation, blockchain has rapidly become one of the hottest Internet technologies in recent years. As a decentralized and distributed data management solution, blockchain has restored the definition of trust by the embedded cryptography and consensus mechanism, thus providing security, anonymity and data integrity without the need of any third party. But there still exists some technical challenges and limitations in blockchain. This paper has conducted a systematic research on current blockchain application in cybersecurity. In order to solve the security issues, the paper analyzes the advantages that blockchain has brought to cybersecurity and summarizes current research and application of blockchain in cybersecurity related areas. Through in-depth analysis and summary of the existing work, the paper summarizes four major security issues of blockchain and performs a more granular analysis of each problem. Adopting an attribute-based encryption method, the paper also puts forward an enhanced access control strategy.

Bitcoin, one major virtual currency, attracts users' attention by its novel mode in recent years. With blockchain as its basic technique, Bitcoin possesses strong security features which anonymizes user's identity to protect their private information. However, some criminals utilize Bitcoin to do several illegal activities bringing in great security threat to the society. Therefore, it is necessary to get knowledge of the current trend of Bitcoin and make effort to de-anonymize. In this paper, we put forward and realize a system to analyze Bitcoin from two aspects: blockchain data and network traffic data. We resolve the blockchain data to analyze Bitcoin from the point of Bitcoin address while simulate Bitcoin P2P protocol to evaluate Bitcoin from the point of IP address. At last, with our system, we finish analyzing its current trends and tracing its transactions by putting some statistics on Bitcoin transactions and addresses, tracing the transaction flow and de-anonymizing some Bitcoin addresses to IPs.

Bitcoin has not only attracted many users but also been considered as a technical breakthrough by academia. However, the expanding potential of Bitcoin is largely untapped due to its limited throughput. The Bitcoin community is now facing its biggest crisis in history as the community splits on how to increase the throughput. Among various proposals, Bitcoin Unlimited recently became the most popular candidate, as it allows miners to collectively decide the block size limit according to the real network capacity. However, the security of BU is heatedly debated and no consensus has been reached as the issue is discussed in different miner incentive models. In this paper, we systematically evaluate BU's security with three incentive models via testing the two major arguments of BU supporters: the block validity consensus is not necessary for BU's security; such consensus would emerge in BU out of economic incentives. Our results invalidate both arguments and therefore disprove BU's security claims. Our paper further contributes to the field by addressing the necessity of a prescribed block validity consensus for cryptocurrencies.

Bitcoin owes its success to the fact that transactions are transparently recorded in the blockchain, a global public ledger that removes the need for trusted parties. Unfortunately, recording every transaction in the blockchain causes privacy, latency, and scalability issues. Building on recent proposals for "micropayment channels" — two party associations that use the ledger only for dispute resolution — we introduce techniques for constructing anonymous payment channels. Our proposals allow for secure, instantaneous and private payments that substantially reduce the storage burden on the payment network. Specifically, we introduce three channel proposals, including a technique that allows payments via untrusted intermediaries. We build a concrete implementation of our scheme and show that it can be deployed via a soft fork to existing anonymous currencies such as ZCash.

With the increasing popularity of virtual currencies, it has become more important to have highly secure devices in which to store private-key information. Furthermore, ARM has made available an extension of processors architectures, designated TrustZone, which allows for the separation of trusted and non-trusted environments, while ensuring the integrity of the OS code. In this paper, we propose the exploitation of this technology to implement a flexible and reliable bitcoin wallet that is more resilient to dictionary and side-channel attacks. Making use of the TrustZone comes with the downside that writing and reading operations become slower, due to the encrypted storage, but we show that cryptographic operations can in fact be executed more efficiently as a result of platform-specific optimizations.