Sextortion has rapidly expanded into a global cyber-enabled crime that leverages anonymous digital communication and decentralized payment systems. This study examines the financial infrastructures underlying contemporary sextortion by conducting a two-phase analysis of 87 confirmed cases involving cryptocurrency payments. Using blockchain forensic tools and open-source intelligence, the research traces fund movements across perpetrator-controlled wallets, identifies laundering techniques such as mixers, peel-chain transfers, and exchange-based cash-outs, and links these behaviors to narrative patterns within victim reports. The results reveal a dual-tier ecosystem in which mass-produced, multilingual extortion scripts coexist with divergent laundering typologies that differentiate lower-value, high-volume scams from more organized and higher-yield operations. By integrating qualitative and quantitative evidence, this study provides a forensic framework for detecting illicit cryptocurrency activity, improving threat classification, and strengthening investigative and regulatory responses to sextortion and related crypto-enabled interpersonal crimes.
Brandon Dulisse, Chivon H. Fitch, Nathan T. Connealy
Cryptocurrency fraud represents one of the fastest-growing financial crimes worldwide, yet the psychological mechanisms that enable these scams remain understudied. Drawing on 282 verified victim narratives from California and Wisconsin state crypto scam trackers (2023–2024), this study systematically coded the use of seven psychological tactics (PTacs) and seven psychological techniques (PTechs) previously validated in cyber social engineering research. Fraudulent trading platforms (51.5%) and pig-butchering schemes (33.7%) dominated the sample. Across all cases, scammers relied overwhelmingly on impersonation and persuasion techniques paired with fit-and-form and familiarity tactics. On average, 1.77 tactics and 1.86 techniques were deployed per incident; higher psychological complexity (4–6 combined elements) was significantly associated with greater financial losses in fraudulent trading platform scams ($135,346 vs. $63,034, p =.029). These findings demonstrate that cryptocurrency fraud resembles more of a repeatable, psychologically-engineered “playbook” rather than random opportunism by unorganized actors. By revealing consistent patterns of manipulation that scale harm, our study provides an evidence-based roadmap for prevention: psychologically informed user education, platform-level disruption of scripted interaction sequences, standardized narrative reporting in complaint systems, and proactive regulatory alerts keyed to emerging PTac/PTech signatures. Implementing these targeted interventions can materially reduce both victimization rates and aggregate financial losses in digital asset markets.
The rapid development of cryptocurrency as a digital financial asset has introduced new challenges for the prevention and eradication of money laundering crimes. While cryptocurrencies offer efficiency, decentralization, and borderless transactions, these very characteristics also create significant vulnerabilities for misuse, particularly in facilitating illicit financial flows. In Indonesia, the existing legal framework on anti-money laundering, primarily regulated under Law Number 8 of 2010, was formulated prior to the widespread adoption of cryptocurrency and therefore faces limitations in addressing technology-driven financial crimes. This article examines the challenges of law enforcement in combating cryptocurrency-based money laundering in Indonesia through a normative juridical approach. The study analyzes relevant statutory regulations, institutional authority, and enforcement mechanisms involving agencies such as PPATK, Bappebti, the Financial Services Authority, and law enforcement bodies. The findings indicate that law enforcement faces substantial obstacles, including regulatory fragmentation, jurisdictional complexities, difficulties in tracing blockchain-based transactions, evidentiary constraints, and limited technical capacity among enforcement institutions. Furthermore, the absence of comprehensive regulation concerning decentralized finance and non-custodial digital wallets exacerbates enforcement difficulties. This article argues that without regulatory harmonization, enhanced institutional coordination, and the integration of technological capabilities into law enforcement practices, the Indonesian legal system risks lagging behind the evolving landscape of financial crime. Strengthening adaptive legal frameworks is therefore essential to ensure effective anti-money laundering enforcement in the digital asset era.
Global illicit fund flows exceed an estimated $3.1 trillion annually, with stablecoins emerging as a preferred laundering medium due to their liquidity. While decentralized protocols increasingly adopt zero-knowledge proofs to obfuscate transaction graphs, centralized stablecoins remain critical transparent choke points for compliance. Leveraging this persistent visibility, this study analyzes an Ethereum dataset to establish an empirical baseline for behavioral AML detection. Our findings demonstrate that domain-informed tree ensemble models achieve higher Macro-F1 score, significantly outperforming graph neural networks, which struggle with the increasing fragmentation of transaction networks. The model's interpretability goes beyond binary detection, successfully dissecting distinct typologies: it differentiates the complex, high-velocity dispersion of cybercrime syndicates from the constrained, static footprints left by sanctioned entities. This methodological approach provides actionable insights that align with industry shifts toward deterministic verification, informing the auditability and compliance requirements under regulations such as the EU's MiCA and the U.S. GENIUS Act while minimizing unjustified asset freezes. By providing a high-precision behavioral classification of suspicious wallets, this approach contributes to raising the economic cost of financial misconduct while informing compliance practice under emerging stablecoin regulations.
Abstract This research investigates how cryptocurrencies are used in illegal markets, including darknet marketplaces, ransomware payments, and money laundering. The study examines transaction patterns, anonymity techniques, and the tools used by cybercriminals to hide illicit flows. To understand the increasing complexity of these activities, the research explores how digital currencies enable fast, borderless, and pseudonymous transactions that often bypass traditional financial regulations and monitoring systems. The study combines blockchain analysis, case studies, and expert observations to map these illegal flows and identify system vulnerabilities. By assessing the role of mixing services, privacy-oriented cryptocurrencies, decentralized exchanges, and chain-hopping techniques, the research highlights the methods used to obscure the origin and destination of digital assets. These insights help reveal how criminals exploit technology to move funds in ways that challenge traditional policing mechanisms. The findings aim to provide valuable insights for policymakers, cryptocurrency exchanges, and law enforcement agencies to improve detection, prevention, and regulation of illicit cryptocurrency activities. The research also examines current regulatory frameworks, global compliance standards, and existing technological tools used to trace illegal transactions. Furthermore, it discusses the challenges faced by authorities, including cross-border jurisdiction issues, lack of unified regulations, and the rapid advancement of blockchain technologies. Overall, this study contributes to a deeper understanding of how illegal cryptocurrency markets operate and highlights opportunities for strengthening cybercrime prevention through improved regulations, data-sharing frameworks, and innovative blockchain forensic solutions.
This study explores the intersection of cryptocurrency, cybercrime, and global governance. It focuses on identifying criminal techniques, analyzing forensic and regulatory countermeasures, and evaluating the broader governance dilemmas that arise. A qualitative desk-based approach was employed, synthesizing secondary data from peer-reviewed studies, institutional policy papers (FATF, IMF, Europol), and industry reports (Chainalysis, Elliptic, TRM Labs). Thematic content analysis was used to trace patterns in illicit cryptocurrency use, law enforcement responses, and regulatory innovations. The findings indicate that while advances in blockchain forensics and policy coordination have strengthened oversight, criminals increasingly exploit decentralized finance platforms, cross-chain laundering, privacy coins, and mixers to evade detection. Enforcement remains uneven, hindered by fragmented regulations and gaps in cross-border cooperation. Overall, the study concludes that cryptocurrency-enabled cybercrime remains a resilient and evolving threat that challenges the stability of the global financial system and exposes weaknesses in governance frameworks. Without stronger coordination, adaptive regulation, and robust technological capabilities, the risks of illicit finance will continue to outpace control efforts. To mitigate these risks, the study recommends enhancing cross-border collaboration, investing in advanced blockchain forensic tools, and adopting flexible, multi-stakeholder governance models that balance innovation with accountability.
Abstract: The non-fungible token (NFT) marketplace has rapidly evolved into a transformative space, experiencing remarkable growth in recent years. NFTs serve as digital ownership certificates linked to unique assets such as art, collectibles, and digital media, exemplifying blockchain innovation. This paper employs an exploratory, systematic literature review of Scopus-indexed sources to examine the fraud-prone dimensions of the NFT ecosystem. Using the fraud triangle framework—pressure, opportunity, and rationalization—it investigates individual and organizational drivers of deceit. The study identifies major fraud types including rug pulls, wash trading, Ponzi schemes, whitelisting, and phishing, offering insights to guide policymakers and participants in mitigating NFT-related risks. Keywords: Non-Fungible Tokens, Blockchain, Digital Fraud Vulnerabilities, Three-Factor Fraud Framework, Risk Mitigation JEL Classification Number: G32, G18, K83, K24, O33
The rise in Blockchain-based digital assets has transformed the financial ecosystems, which has also created complex governance and taxation challenges. The pseudonymous and cross-border nature of crypto transactions undermines traditional tax enforcement, leaving regulators such as the South African Revenue Service (SARS) reliant on voluntary disclosures with limited verification mechanisms, while existing Blockchain forensic tools and regulatory technologies (RegTechs) have advanced in anti-money laundering and institutional compliance, their integration into issues related to taxpayer compliance and locally adapted solutions remains underdeveloped. Therefore, this study conducts a state-of-the-art review of Blockchain forensics, RegTech innovations, and crypto tax frameworks to identify gaps in the crypto tax compliance space. Then, this study builds on these insights and proposes a conceptual model that integrates digital forensics, cost basis automation aligned with SARS rules, wallet interaction mapping, and non-fungible tokens (NFTs) as verifiable audit anchors. The contributions of this study are threefold: theoretically, which reconceptualise the adoption of Blockchain forensics as a proactive compliance mechanism; practically, it conceptualises a locally adapted proof-of-concept for diverse transaction types, including DeFi and NFTs; and lastly, innovatively, which introduces NFTs to enhance auditability, trust, and transparency in digital tax compliance.
Contemporary organizational ecosystems are critically vulnerable in third-party risk management frameworks due to centralized databases, fragmented documentation systems, and manual processes of assessment. Traditional approaches result in huge inefficiencies through redundant audits, version control complexities, and delayed responses for compliance along multi-jurisdictional vendor networks. The blockchain architecture introduces a fundamental architectural transformation through distributed ledger mechanisms, creating immutable audit trails, cryptographic verification protocols, and decentralized trust formation across organizations. The article reviews how blockchain works as an integrity infrastructure within regulatory technology ecosystems, allowing the automation of compliance through smart contracts, making transparent records available for authorized stakeholders, and removing single-point vulnerabilities from centralized control systems. The technical mechanisms for implementation include immutable vendor record systems, which integrate fragmented documentation into unified, tamper-proof ledgers; smart contract automation that allows deterministic outcomes in governance; and distributed assurance networks, which allow audit verification among multiple organizations. Regulatory dimensions are related to preserving privacy through hybrid on-chain and off-chain architectures, legal recognition challenges of smart contracts within jurisdictional frameworks, and ethics in governance requirements for human input within automated ecosystems of decisions. Implementation challenges involve the complexity of legacy system integration, the development of a structure for consortium governance, scalability constraints, and the scarcity of talent. Future trajectories include hybrid ecosystems, integrating blockchain's immutability with advanced analytics, tokenized reputation frameworks, and integrations with emerging technologies such as artificial intelligence and digital identity systems toward next-generation vendor risk governance.
Meme coins have become extremely popular in the cryptocurrency market, but they also carry a high level of risk. Many of these projects rely on social media hype and community excitement, yet a large number eventually turn out to be scams where developers steal investor funds and abandon the project, commonly known as rug pulls. This paper presents a smart analysis tool designed to help investors identify such risky meme coin projects before financial loss occurs. The proposed system examines both smart contract behavior and market-related factors, including ownership control, liquidity locking, token distribution, and developer wallet activity. The tool was tested on real-world meme coins, including well-known legitimate projects as well as confirmed scam tokens. The results show that the system is able to accurately distinguish between safe and high-risk projects. This approach provides a practical and effective way to improve investor safety in the rapidly evolving decentralized finance ecosystem
Bitcoin custody systems are designed by individuals with full contextual knowledge and later encountered by others—executors, trustees, attorneys, heirs—who must interpret and operate these systems without the original owner present. This interpretive gap produces recurring failure patterns that persist even when custody components technically exist. This paper presents a taxonomy of failure modes observed in Bitcoin custody systems when those systems are encountered under stress conditions including death, incapacity, device loss, and institutional failure. The taxonomy distinguishes between legal authority and cryptographic access, between security and survivability, and between documentation that enables action and documentation that merely describes existence. Seven failure mode categories are examined: (1) documentation without usability, where correct and comprehensive records nonetheless fail to enable execution; (2) time as an active dependency, where dormant systems degrade through institutional change, memory loss, and technological obsolescence; (3) dependency overlap, where apparently redundant components share hidden common roots; (4) partial access traps, where incomplete recovery attempts constrain or block subsequent paths; (5) authority-access misalignment, where legal entitlement and operational capability diverge; (6) coordination failure, where distributed control prevents action when parties cannot align; and (7) delay-induced state changes, where outcomes differ based on when recovery is attempted. The paper provides canonical vocabulary for professional communication about custody situations and offers a scenario reference for modeling system behavior under stress. It is intended as a descriptive reference for fiduciaries, estate planning attorneys, and advisors who encounter Bitcoin custody systems in professional contexts. The paper does not provide recommendations, evaluate custody arrangements, or establish standards of care.
This article explores Jeffrey Epstein's financial habits, focusing on his longstanding efforts to evade traditional banking oversight and his early interest in emerging financial technologies such as Bitcoin. While there is no evidence linking cryptocurrency to his criminal activity, newly released records and reporting reveal that Epstein studied and invested in technology, seeking ways to minimize reliance on regulated intermediaries. The piece argues that Epstein's attraction to Bitcoin's features, especially its capacity to bypass formal banking structures, parallels the reasons cryptocurrency later became popular in illicit financial networks.
This paper documents a structural break in the risk return characteristics and cultural relevance of cryptocurrencies following the approval of the first spot Bitcoin ETF on January 10, 2024. Using daily price data from January 2021 to June 2026, we compare pre ETF and post ETF performance metrics, betas, and event study cumulative abnormal returns for Bitcoin, Dogecoin, and Ethereum relative to the S&P 500 and gold. We then introduce two independent measures of public interest, Google Trends and Wikipedia page views, to test the hypothesis that Bitcoin lost its cultural "coolness" after institutionalization. The findings are striking. Dogecoin, the quintessential speculative asset, saw its Sharpe ratio collapse from 0.30 pre ETF to 0.01 post ETF, while its annualized return fell from 63.17% to 2.82%. Google search interest for Dogecoin declined 63.1% and its Wikipedia page views collapsed 75.9%. Searches for "how to buy Bitcoin," a proxy for new retail entrants, declined 22.7%. In contrast, general "cryptocurrency" interest fell 47.5%, while Bitcoin maintained a stable Sharpe ratio and saw its beta relative to the S&P 500 decline from 1.33 to 1.11. An event study reveals that the Trump 2024 election produced a +47.37% cumulative abnormal return for Dogecoin, but this proved temporary. The MSTR sale in May 2026, Michael Saylor's first Bitcoin sale since 2022, generated a-6.56% abnormal return for Bitcoin. These results support the thesis that ETF approval marked a cultural as well as financial regime shift, as retail speculative energy exited the crypto market and Bitcoin moved toward more of a diversifier role.
The rapid expansion of blockchain-based financial systems has fundamentally transformed the structure of economic crime. While distributed ledger technologies provide unprecedented transparency, they simultaneously enable pseudonymous interactions that can be exploited for illicit financial activities, including money laundering and tax evasion. This paper develops a theoretical and computational framework for detecting illicit financial behavior in blockchain networks. By integrating economic criminology, graph-based analysis, and machine learning techniques, it proposes a composite detection model capable of identifying suspicious transaction patterns through structural and behavioral indicators. The study argues that blockchain-based financial crime is not hidden but structurally embedded within transparent systems, requiring algorithmic interpretation rather than traditional investigative approaches. The findings highlight the importance of scalable, data-driven enforcement mechanisms and coordinated regulatory responses in addressing financial crime in decentralized environments.
Progesterone is a vital endogenous steroid hormone extensively used in hormone replacement therapy, contraception, infertility management, and various gynaecological disorders. Despite its significant therapeutic importance, its clinical effectiveness is severely limited by poor aqueous solubility, extensive first-pass hepatic metabolism, and low oral bioavailability. These challenges necessitate the development of advanced drug delivery systems capable of improving its systemic absorption and therapeutic performance. Nanostructured lipid carriers (NLCs) have emerged as a promising second-generation lipid-based nanocarrier system designed to overcome these limitations are composed of a blend of solid and liquid lipids stabilized by surfactants, forming an imperfect lipid matrix that enhances drug loading capacity, stability, and controlled release behavior.
This report examines the convergence of generative artificial intelligence, cryptocurrency laundering infrastructure, and cross-border social engineering in the evolution of romance scam-enabled financial crime affecting Canadian institutions. Drawing on reporting from the Federal Bureau of Investigation Internet Crime Complaint Center (FBI IC3), the Financial Transactions and Reports Analysis Centre of Canada (FINTRAC), the Royal Canadian Mounted Police (RCMP), and blockchain analytics firms Chainalysis and TRM Labs, the analysis identifies a measurable transition from opportunistic, manually-operated fraud schemes toward industrialized transnational operations. The report documents how AI-generated personas, deepfake impersonation tools, and multilingual automation systems have reduced operational costs for fraud actors while increasing victim acquisition at scale. Particular attention is given to cryptocurrency laundering pathways — including stablecoin conversion, decentralized finance (DeFi) layering, cross-chain transfers, and over-the-counter (OTC) broker off-ramping — that exploit the opacity of digital asset ecosystems and exceed the detection capabilities of traditional threshold-based anti-money laundering (AML) monitoring systems. The report further assesses Canada's specific vulnerability profile, attributing heightened exposure to widespread Interac e-Transfer adoption, high public trust in digital financial systems, and fragmented cross-border compliance coordination. Three systemic risk vectors are identified and analyzed: the industrialization of victim acquisition, increased laundering opacity through decentralized cryptocurrency infrastructure, and the systematic exploitation of Canadian digital payment rails. Recommendations are directed at the Economic and Financial Crimes Commission (EFCC), Nigerian financial intelligence agencies, and Canadian financial institutions and cryptocurrency platforms.
The Court of Justice of the European Union's landmark ruling in Skatteverket v. David Hedqvist (Case C-264/14) established that Bitcoin-to-fiat exchanges constitute VAT-exempt services under Article 135(1)(e) of the VAT Directive, on the basis that Bitcoin serves as a contractual means of payment analogous to legal tender. However, the rapid proliferation of Non-Fungible Tokens (NFTs)-which are increasingly characterized as electronically supplied services (ESS) rather than currency-has fragmented the uniform fiscal landscape envisioned by the ruling. This paper examines a critical, underexplored nexus: whether divergent VAT/GST treatments of NFTs across EU Member States create incentives for regulatory arbitrage that systematically increases the cyber-risk profile of decentralized exchanges (DEXs). As recent incidents involving Aerodrome Finance, CoW Swap, and dYdX demonstrate, the decentralized finance (DeFi) sector remains acutely vulnerable to Domain Name System (DNS) hijacking attacks that exploit the Web2 front-end infrastructure upon which DEXs rely. The paper argues that when tax uncertainty drives platforms toward jurisdictional optimization-often involving complex routing, cross-border operations, and reliance on lessregulated infrastructure-they inadvertently expand their attack surface for adversarial DNS tunneling. Employing a socio-technical analysis that bridges fiscal harmonization and network security, this study proposes a harmonized VAT framework for NFTs to reduce the compliance-security paradox that currently incentivizes risk-increasing operational behaviors. It further recommends the integration of decentralized naming systems, such as the Ethereum Name Service (ENS), as a countermeasure to DNS-based exploitation. The findings contribute to both tax policy discourse and cybersecurity scholarship by demonstrating that fiscal harmonization is not merely an economic concern but a foundational component of DeFi infrastructure resilience.
This study explores trade surveillance models especially for wash trading and off-market pricing. These are few fraud behavior patterns that cause persistent threat to market integrity in traditional equity markets, cryptocurrency exchanges and decentralized non-fungible token (NFT) ecosystems. Although there is growing regulatory attention but there is less improvement in the current surveillance systems and remain fragmented and inconsistent in their ability to uncover manipulative behavior for different market structures. This paper summarizes findings electronic copy available at: https://ssrn.com from three peer-reviewed empirical studies to evaluate the effectiveness of current trade surveillance models and proposes an integrated detection framework that combines graph-based network analysis, econometric modeling, machine learning classifiers, and blockchain transparency tools. These reviewed literatures all together demonstrate that: (1) directed graph algorithms achieve more than 95% detection accuracy for collusive wash-trading patterns in traditional regulated markets; (2) around 70% of reported trading volume on certain cryptocurrency platforms is fabricated using coordinated self-transactions; and (3) AI-assisted blockchain analytics can identify wash-trading loops in decentralized NFT markets with more than 95% precision. Researching and studying these findings, this paper proposes a unified, AI driven surveillance architecture integrating real-time graph traversal, cross-exchange auditing, and blockchain forensic analysis. The framework designed to improve detection speed, reduce false positives, and support regulatory enforcement for both centralized and decentralized financial environments. Paper discusses the implications for regulatory policy, financial compliance infrastructure, and future surveillance system design.
The evolution of organised crime in India and its transforming relations between power and criminality increasingly reflect the logic of decentralisation, digital technologies and networked connections. The gangs headed by dons, which rely on sharp hierarchical authoritybased structures and are punctuated by layers of absentees serving only their personal interests, are giving way to a quasi-invisible architecture of fluidity, cell-based interactions and technological apparatus. Our paper places the Lawrence Bishnoi Gang at the centre of the inquiry of a contemporary interstate gang network in the digital era, exploring the dynamics of how new digital appreciation, reconnaissance, social media, encrypted exchanges and prison forays emerge to provide new reach and resiliency. Networks beg to differ; if we are to extend networkable theory to include also the study of criminality, then the Bishnoi network is the proof in the pudding. Making a special place for the records of recent homemaking, we examine how they view high visibility, dalliance in extortion, recruitment, targeted killings and crossborder desiring playing host to an archipelago in constancy even as the leaders are locked away in prisons away from home. Features like the need for hub and spoke models and high visibility required need to be varied in digital amplification, conspiring to leverage symbolic power, fear and reputation that take over physicality and locomotion for effective control over regions. Under considerable stake in the legal framework, the duration study examines most existing laws in the Indian Constitution that deal with gangsterism, such as the Indian Penal Code, better coupled with the Unlawful Activities (Prevention) Act and new media protocols dilemmas seen in the context of jurisdictions, lax borders and differential standards in prosecuting loosely accreted actors. Themes, such as suggestions, Honda variants like focus on interstate security units in combating the malady of cyber threats are safeguarded, and digital surveillance, though with care for the future.
We develop a model of aberrant behavior by Bitcoin miners and test it with a new 2017-2025 dataset.Miners' rewards, comprised partly of user fees, exhibit variability across blocks of transactions.When large reward disparities exist between adjacent blocks, miners have incentives to attempt alternative versions of prior blocks and claim other miners' rewards for themselves.Regression analysis shows that fee differentials are associated with these attacks and longer waiting times between blocks.These patterns imply potential destabilization of the Bitcoin blockchain as future mining rewards become more volatile due to gradual withdrawal of fixed block subsidies.
Airdrops are widely used in blockchain ecosystems as mechanisms for token distribution, user bootstrapping, and governance decentralization. These mechanisms frequently rely on balance or stake snapshots taken at specific blockchain heights or epochs to determine eligibility. However, snapshot-based distribution introduces a critical temporal vulnerability: the assumption that momentary state accurately represents sustained economic participation.This paper defines and analyzes <b><i>Airdrop Snapshot Spoofing</i></b>, a class of temporal state manipulation attacks in which adversaries exploit the gap between snapshot definition, execution, and settlement to illegitimately capture token allocations. We demonstrate that such exploits are not edge cases but structural weaknesses inherent to snapshot-based systems across Proof-of-Stake (PoS) and tokenized networks. We further argue that snapshot spoofing represents a core-layer economic security failure rather than a marketing or distribution flaw, and we outline mitigation strategies based on time-weighted enforcement and validator-level continuity checks.
Abstract Cheap, disposable online identities make abuse easier to externalize. Users can harass, evade bans, amplify content through fake accounts, or abandon a damaged reputation at low cost, while other users, moderators, and platforms bear the consequences. This paper examines verified pseudonymity as an institutional response to that problem. First, I model online communities as club-governed informational commons in which incivility degrades the shared environment and raises enforcement costs. The model shows that conduct can improve when sanctions attach to a persistent pseudonymous identity and when users have future access, reputation, or governance rights at stake. Second, I compare verified pseudonymity with open pseudonymity, real-name mandates, centralized know-your-customer verification, algorithmic moderation, and no intervention. Decentralized identifiers, verifiable credentials, proof of personhood, and non-transferable standing credentials matter because they can separate authentication from public identification. Third, I add a community-currency layer that separates access to scarce attention from governance rights. The result is a governance framework in which accountability depends less on public naming than on durable standing, credible sanctions, and reusable privacy-preserving credentials.