The Urban CryptographerIn this book I want to bring cryptography into mainstream thinking about cities. Cryptography supports data security and privacy online and serves as a remedy against cybercrime and information leakage.Cryptography also supports cryptocurrencies, the blockchain, non-fungible tokens (NFTs), smart contracts, and other digital innovations that permeate the so-called "smart city."Cryptographic methods and technologies at times appear exotic and external to the concerns of those of us interested in the history, design, and shaping of cities, but in what follows I will demonstrate that cities are already invested in cryptographic ideas and practices.At the very least, cities and cryptography have concepts and procedures in common.Without cryptography, communications among people and digital devices would be exposed for anyone to see, hack, and misdirect.Facilities for securing transactions are critical elements in city infrastructures.Cryptography applies procedures and algorithms to transform texts, pictures, audio, files, and information flows so they can be read only by a targeted recipient, a designated receiver.Cryptography is not new to the city.As long as cities have existed, communications would circulate, often in full sight, but with their messages hidden.I wish to claim cryptography as a major component in the perennial life of any city.Formal and informal secret signals, sometimes described simply as "codes," flourish in urban contexts.Think of a knock at the door, the subtle inflection of which is known only to the conspirators, partygoers, or lovers on either side.I think also of how people exchange cryptic text messages, or the coded calls to children and pets that dinner is ready.The urban lifeworld is infused with abstruse acoustic signals that strengthen invisible connections and define spaces.
Mining attacks allow adversaries to obtain a disproportionate share of the mining reward by deviating from the honest mining strategy in the Bitcoin system. Among them, the most well-known are selfish mining (SM), block withholding (BWH), fork after withholding (FAW) and bribery mining. In this paper, we propose two novel mining attacks: bribery semi-selfish mining (BSSM) and bribery stubborn mining (BSM). Both of them can increase the relative extra reward of the adversary and will make the target bribery miners suffer from the bribery miner dilemma. All targets earn less under the Nash equilibrium. For each target, their local optimal strategy is to accept the bribes. However, they will suffer losses, comparing with denying the bribes. Furthermore, for all targets, their global optimal strategy is to deny the bribes. Quantitative analysis and simulation have been verified our theoretical analysis. We propose practical measures to mitigate more advanced mining attack strategies based on bribery mining, and provide new ideas for addressing bribery mining attacks in the future. However, how to completely and effectively prevent these attacks is still needed on further research.
Abstract With the high-speed development of decentralized applications, account-based blockchain platforms have become a hotbed of various financial scams and hacks due to their anonymity and high financial value. Financial security has become a top priority with the sustainable development of blockchain-based platforms because of an increasing number of cyber attacks, which have resulted in a huge loss of crypto assets in recent years. Therefore, it is imperative to study the real-time detection of cyber attacks to facilitate effective supervision and regulation. To this end, this paper proposes the weighted and extended isolation forest algorithms and designs a novel framework for the real-time detection of cyber-attack transactions by thoroughly studying and summarizing real-world examples. Furthermore, this study develops a new detection approach for locating the compromised address of a cyber attack to resolve the data scarcity of hack addresses and reduce time consumption. Moreover, three experiments are carried out not only to apply on different types of cyber attacks but also to compare the proposed approach with the widely used existing methods. The results demonstrate the high efficiency and generality of the proposed approach. Finally, the lower time consumption and robustness of our method were validated through additional experiments. In conclusion, the proposed blockchain-oriented approach in this study can handle real-time detection of cyber attacks and has significant scope for applications.
Blockchain systems often rely on rationality assumptions for their security, expecting that nodes are motivated to maximize their profits. These systems thus design their protocols to incentivize nodes to execute the honest protocol but fail to consider out-of-band collusion. Existing works analyzing rationality assumptions are limited in their scope, either by focusing on a specific protocol or relying on non-existing financial instruments. We propose a general rational attack on rationality by leveraging an external channel that incentivizes nodes to collude against the honest protocol. Our approach involves an attacker creating an out-of-band bribery smart contract to motivate nodes to double-spend their transactions in exchange for shares in the attacker's profits. We provide a game theory model to prove that any rational node is incentivized to follow the malicious protocol. We discuss our approach to attacking the Bitcoin and Ethereum blockchains, demonstrating that irrational behavior can be rational in real-world blockchain systems when analyzing rationality in a larger ecosystem. We conclude that rational assumptions only appear to make the system more secure and offer a false sense of security under the flawed analysis.
In August of 2022, the United States Department of Treasury sanctioned the virtual currency mixer Tornado Cash, an open-source and fully decentralised piece of software running on the Ethereum blockchain, subsequently leading to the arrest of one of its developers in the Netherlands. Not only was this the first time the Office of Foreign Assets Control (OFAC) extended its authority to sanction a foreign ‘person’ to software, but the decentralised nature of the software and global usage highlight the challenge of establishing jurisdiction over decentralised software and its global user base. The government claims jurisdiction over citizens, residents, and any assets that pass through the country’s territory. As a global financial center with most large tech companies, this often facilitates the establishment of jurisdiction over global conduct that passes through US servers. However, decentralised programs on blockchains with nodes located around the world challenge this traditional approach as either nearly all countries can claim jurisdiction over users, subjecting users to criminal laws in countries with which they have no true interaction, or they limit jurisdiction, thereby risking abuse by bad actors. This article takes a comparative approach to examine the challenges to establishing criminal jurisdiction on cryptocurrency-related crimes.
This research paper provides an in-depth analysis of cryptocurrency exchanges by examining their types, regulatory environment, challenges, and user behavior. We conducted a comparative study of ten popular cryptocurrency exchanges and collected data on user behavior and preferences through surveys, interviews, and website analysis. Our findings reveal that crypto exchanges face numerous challenges such as security, liquidity, and regulatory compliance. We also found that users prefer exchanges that offer a wide range of cryptocurrencies, high liquidity, low fees, and strong security measures. This research contributes to the understanding of the cryptocurrency industry and provides insights for policymakers, investors, and users. Keywords : Cryptocurrency Exchanges, Bitcoin, Trading, Portability and Vulnerability
I combine Thorstein Veblen’s “diagnostic” approach with John R. Commons’ “remedial” approach to analyze virtual property. I focus my analysis on public blockchain based discreet assets. I conclude that the failure to fulfill two of the libertarian promises (namely, decentralized and trustless finance) does not discredit blockchain technology as such. Permissioned blockchain has promising applications. However, virtual property that is based on public blockchain facilitates extraction of value that must be politically and juridically regulated together with empowering citizens.
This paper investigates the evolution of cryptocurrencies. By nature and essence, Bitcoin challenged and implicitly threatened central bank money and its role in the monetary system. Meanwhile, central banks have been studying cryptocurrencies and launched pilot projects on their own digital currency, the Central Bank Digital Currency. Until recently, most economists considered Bitcoin merely as a speculative asset; however, the El Salvador decision in 2021 to establish it as a legal tender (through the Bitcoin Law) questions the status quo perception of Bitcoin. Given El Salvador’s legal obligation by law of their acceptance, allowing tax payments to the government and debts to be settled using Bitcoin, the Bitcoin Law challenges the boundaries of money. In light of the El Salvador experience, we consider different perspectives on the nature of money, allowing us to reject or include Bitcoin inside the money spectrum.
This paper evaluated Bitcoin financial and economic behaviour by using the econometric model on Bitcoin rate of returns compared to the alternatives assets like precious metals, stock market, and exchange rate risk. The study employed the various Quantile Regression models to observe the hedging ability of Bitcoin under bearish and bullish scenarios. The daily data of China and the USA have been collected, from July 18, 2010, to August 31, 2021. The result indicates that under different market phenomena, Bitcoin holds hedge and safe-haven asset properties against precious metals such as gold, silver, and platinum. Bitcoin can be used as an alternative to money during the currency devaluation against the US Dollar since it holds a hedge and safe- haven properties against S&P 500 Index and SSEC Index. The study elaborates the several implications for investors portfolios. Finally, the study draws the attention of policymakers towards the legalisation of Bitcoin as a currency alternative considering its efficient performance under different economic conditions, supported by detailed theoretical and empirical analyses.
The use of blockchains for automated and adversarial trading has become commonplace. However, due to the transparent nature of blockchains, an adversary is able to observe any pending, not-yet-mined transactions, along with their execution logic. This transparency further enables a new type of adversary, which copies and front-runs profitable pending transactions in real-time, yielding significant financial gains. Shedding light on such "copy-paste" malpractice, this paper introduces the Blockchain Imitation Game and proposes a generalized imitation attack methodology called Ape. Leveraging dynamic program analysis techniques, Ape supports the automatic synthesis of adversarial smart contracts. Over a timeframe of one year (1st of August, 2021 to 31st of July, 2022), Ape could have yielded 148.96M USD in profit on Ethereum, and 42.70M USD on BNB Smart Chain (BSC). Not only as a malicious attack, we further show the potential of transaction and contract imitation as a defensive strategy. Within one year, we find that Ape could have successfully imitated 13 and 22 known Decentralized Finance (DeFi) attacks on Ethereum and BSC, respectively. Our findings suggest that blockchain validators can imitate attacks in real-time to prevent intrusions in DeFi.
We have been hearing about Bitcoins for several years not only in the news but also in TV series. The problem is that in most cases, especially in TV series, what Bitcoins really are and what we can do with them is distorted. It is not controlled by any authority, it is not stored in banks, it is not traceable and, in many cases, especially in the early days, it is associated with illegal activities related to drug and arms trade. But if we dig a little deeper into what this new currency actually means, we can see that it could become a widely used currency by users in the near future. Bitcoins is the thing that used by any person or organization without any restriction and this currency may be used as a currency officially. To understand transferring bitcoins among parties globally, it can be essential to clarify what a bitcoin is itself.
As the largest blockchain platform that supports smart contracts, Ethereum has developed with an incredible speed. Yet due to the anonymity of blockchain, the popularity of Ethereum has fostered the emergence of various illegal activities and money laundering by converting ill-gotten funds to cash. In the traditional money laundering scenario, researchers have uncovered the prevalent traits of money laundering. However, since money laundering on Ethereum is an emerging means, little is known about money laundering on Ethereum. To fill the gap, in this paper, we conduct an in-depth study on Ethereum money laundering networks through the lens of a representative security event on \textit{Upbit Exchange} to explore whether money laundering on Ethereum has traditional traits. Specifically, we construct a money laundering network on Ethereum by crawling the transaction records of \textit{Upbit Hack}. Then, we present five questions based on the traditional traits of money laundering networks. By leveraging network analysis, we characterize the money laundering network on Ethereum and answer these questions. In the end, we summarize the findings of money laundering networks on Ethereum, which lay the groundwork for money laundering detection on Ethereum.
This research develops a methodology to identify transactions through data-driven tracking and analysis of ransomware-Bitcoin payment networks [30]. We demonstrate the methodology by applying the GraphSAGE embedding algorithm to the WannaCry ransomware-Bitcoin cash-out network. The paper takes a data-driven approach to building a machine learning system that allows analysts to define features relevant to ransomware-Bitcoin payment networks.
In recent times, there has been a swift advancement in the field of cryptocurrency. The advent of cryptocurrency has provided us with convenience and prosperity, but has also given rise to certain illicit and unlawful activities. Unlike classical currency, cryptocurrency conceals the activities of criminals and exposes their behavioral patterns, allowing us to determine whether present cryptocurrency transactions are legitimate by analyzing their behavioral patterns. There are two issues to consider when determining whether cryptocurrency transactions are legitimate. One is that most cryptocurrency transactions comply with laws and regulations, but only a small portion of them are used for illegal activities, which is related to the sample imbalance problem. The other issue concerns the excessive volume of data, and there are some unknown illegal transactions, so the data set contains an abundance of unlabeled data. As a result, it is critical to accurately distinguish between which transactions among the plethora of cryptocurrency transactions are legitimate and which are illegal. This presents quite a difficult challenge. Consequently, this paper combines mutual information and self-supervised learning to create a self-supervised model on the basis of mutual information that is used to improve the massive amount of untagged data that exist in the data set. Simultaneously, by merging the conventional cross-entropy loss function with mutual information, a novel loss function is created. It is employed to address the issue of sample imbalance in data sets. The F1-Score results obtained from our experimentation demonstrate that the novel loss function in the GCN method improves the performance of cryptocurrency illegal behavior detection by four points compared with the traditional loss function of cross-entropy; use of the self-supervised network that relies on mutual information improves the performance by three points compared with the original GCN method; using both together improves the performance by six points.
Decentralized autonomous organizations (DAOs) are blockchain-based organizations fed by a peer-to-peer (P2P) networkof contributors. Their management is decentralized without top executive teams and built on automated rules encoded insmart
Fake news, misinformation and disinformation have significantly increased over the past years, and they have a profound effect on societies and supply chains. This paper examines the relationship of information risks with supply chain disruptions and proposes blockchain applications and strategies to mitigate and manage them. We critically review the literature of SCRM and SCRES and find that information flows and risks are relatively attracting less attention. We contribute by suggesting that information integrates other flows, processes and operations, and it is an overarching theme that is essential in every part of the supply chain. Based on related studies we create a theoretical framework that incorporates fake news, misinformation and disinformation. To our knowledge, this is a first attempt to combine types of misleading information and SCRM/SCRES. We find that fake news, misinformation and disinformation can be amplified and cause larger supply chain disruptions, especially when they are exogenous and intentional. Finally, we present both theoretical and practical applications of blockchain technology to supply chain and find support that blockchain can actually advance risk management and resilience of supply chains. Cooperation and information sharing are effective strategies.
Lakshmi P. Krishnan, Iman Vakilinia, Sandeep Reddivari, Sanjay Ahuja
With the emergence of cryptocurrencies and Blockchain technology, the financial sector is turning its gaze toward this latest wave. The use of cryptocurrencies is becoming very common for multiple services. Food chains, network service providers, tech companies, grocery stores, and so many other services accept cryptocurrency as a mode of payment and give several incentives for people who pay using them. Despite this tremendous success, cryptocurrencies have opened the door to fraudulent activities such as Ponzi schemes, HYIPs (high-yield investment programs), money laundering, and much more, which has led to the loss of several millions of dollars. Over the decade, solutions using several machine learning algorithms have been proposed to detect these felonious activities. The objective of this paper is to survey these models, the datasets used, and the underlying technology. This study will identify highly efficient models, evaluate their performances, and compile the extracted features, which can serve as a benchmark for future research. Fraudulent activities and their characteristics have been exposed in this survey. We have identified the gaps in the existing models and propose improvement ideas that can detect scams early.
Fraud across the decentralized finance (DeFi) ecosystem is growing, with victims losing billions to DeFi scams every year. However, there is a disconnect between the reported value of these scams and associated legal prosecutions. We use open-source investigative tools to (1) investigate potential frauds involving Ethereum tokens using on-chain data and token smart contract analysis, and (2) investigate the ways proceeds from these scams were subsequently laundered. The analysis enabled us to (1) uncover transaction-based evidence of several rug pull and pump-and-dump schemes, and (2) identify their perpetrators’ money laundering tactics and cash-out methods. The rug pulls were less sophisticated than anticipated, money laundering techniques were also rudimentary and many funds ended up at centralized exchanges. This study demonstrates how open-source investigative tools can extract transaction-based evidence that could be used in a court of law to prosecute DeFi frauds. Additionally, we investigate how these funds are subsequently laundered.
Sadia Nazar Hussain, Abdul Raheman, Muhammad Anwar ul Haq
Water always finds its way" so do the money launderers, who are always successful in finding new ways of committing the crime. This study primarily aims to identify opportunities that launderers are exploiting to whitewash their black money. Dual nationality (DN), financial system sophistication (FSS), and cryptocurrency legal status (CCLS) are the advanced opportunities being used by launders to clean their funds. Some studies highlight the link between cryptocurrency and money laundering, but the role of dual nationality and financial system sophistication in money laundering is still a less addressed phenomenon (Ebeke, 2011) and (T. P. and J. Walker, 2011). The objective of this study is to explore the role of these three variables in money laundering by making improvements to the original version of the Walker model. The study's theoretical model was developed by borrowing justifications from Rational Choice Theory (RCT). For quantitative analysis, FGLS was employed over strongly balanced panel datasets. The final dataset of the study was prepared by gathering secondary data from 177 countries for 11 years (2009-2019). The study has found that overall, financial system sophistication is an important factor in choosing a laundering centre around the globe. However, Pakistani launderers do not perceive FSS as an attractive element for laundering their black money. In contrast, dual nationality was identified as a significant element in money laundering from Pakistan to other countries. However, the aspect of cryptocurrency legal status was found to be a significant attractive element for both national and international launders. The findings of the study guide policymakers and practitioners in strengthening the anti-money laundering strategy.
The banking sector is identified as the main means for laundering illicit money, these banks generally have access to both banking mechanism and legal authority to make decisions. Money launderers and those financing terrorism are conveniently accessing financial institutions and its mechanism. These institutions provide all financial funds transfers both domestic and international range. Anti-money laundering (AML) laws and other data protection laws that keep getting stricter have forced many financial institutions to put in place long, expensive processes to stay in compliance. To bridge the gap, emerging technology can help in mitigating money laundering and other financial crimes. Blockchain is considered one of the world's best-known examples of Distributed Ledger Technology. In the financial sector, this type of technology has been hailed as the key to future success. Emerging technology can be used in many ways in Financial Services. It can change many processes, payments between peer-to-peer, trade agreements and tracking of supply chains. Emerging technology can be used in many ways in financial services and can change many processes, peer-to-peer payments, trade agreements, and the tracking of supply chains. These use cases depend on the participants or users being identified and verified. "Know Your Customer" is the term for this (KYC). Before making a transaction, one of the most basic ways to build trust between the people involved is to check out the user. This current paper focuses on issues of compliance and Anti Money Laundering policies in the banking sector by using new emerging technologies such as blockchain; further, the paper focuses keenly on issues relating to the manipulation of KYC and the financial burden on banks while also addressing AML policies, Finally, the paper provides ideas and suggestions regarding the rise of emerging technologies such as blockchain while addressing the problems of ML. This also includes the capability of blockchain technology to bring banking systems with recalibrated mode of compliances polices.
Daniel Mider, Przemysław Potocki, Robert Staniszewski
PURPOSE: The aim of this article is to examine the volume, trust and risk perceived by Poles in terms of broadly understood types of payments, from cash, through various electronic payments, to cryptocurrencies. This is particularly important in the context of the hypothesis of a cashless societies predicted by some researchers.
Hanna Kim, Jian Cui, Eugene Jang, Chanhee Lee · 7 authors
As Non-Fungible Tokens (NFTs) continue to grow in popularity, NFT users have become targets of phishing attacks by cybercriminals, called \textit{NFT drainers}. Over the last year, \$100 million worth of NFTs were stolen by drainers, and their presence remains a serious threat to the NFT trading space. However, no work has yet comprehensively investigated the behaviors of drainers in the NFT ecosystem. In this paper, we present the first study on the trading behavior of NFT drainers and introduce the first dedicated NFT drainer detection system. We collect 127M NFT transaction data from the Ethereum blockchain and 1,135 drainer accounts from five sources for the year 2022. We find that drainers exhibit significantly different transactional and social contexts from those of regular users. With these insights, we design \textit{DRAINCLoG}, an automatic drainer detection system utilizing Graph Neural Networks. This system effectively captures the multifaceted web of interactions within the NFT space through two distinct graphs: the NFT-User graph for transaction contexts and the User graph for social contexts. Evaluations using real-world NFT transaction data underscore the robustness and precision of our model. Additionally, we analyze the security of \textit{DRAINCLoG} under a wide variety of evasion attacks.
Abstract As a financial innovation of the information age, cryptocurrency is a complex concept with clear advantages and disadvantages and is worthy of discussion. Exploring from a terrorism perspective, this study uses the time-varying parameter/stochastic volatility vector autoregression model to explore the risk hedging and terrorist financing capabilities of Bitcoin. Empirical results show that both terrorist incidents and brutality may explain Bitcoin price, but their effects are slightly different. Compared to terrorist brutality, terrorist incidents have a weaker impact on Bitcoin price, showing that Bitcoin investors are more concerned about the number of deaths than the frequency of terrorist attacks. In turn, the impact of Bitcoin price on terrorist attacks is negligible. Bitcoin is a potential means of financing terrorism, but it does not currently play an important role. Our research findings can help investors analyze and predict Bitcoin prices and help improve the theoretical system of anti-terrorist financing, helping to maintain world peace and security.