The mainstream adoption of cryptocurrencies has led to a surge in wallet-related issues reported by ordinary users on social media platforms. In parallel, there is an increase in an emerging fraud trend called cryptocurrency-based technical support scam, in which fraudsters offer fake wallet recovery services and target users experiencing wallet-related issues.In this paper, we perform a comprehensive study of cryptocurrency-based technical support scams. We present an analysis apparatus called HoneyTweet to analyze this kind of scam. Through HoneyTweet, we lure over 9K scammers by posting 25K fake wallet support tweets (so-called honey tweets). We then deploy automated systems to interact with scammers to analyze their modus operandi. In our experiments, we observe that scammers use Twitter as a starting point for the scam, after which they pivot to other communication channels (e.g., email, Instagram, or Telegram) to complete the fraud activity. We track scammers across those communication channels and bait them into revealing their payment methods. Based on the modes of payment, we uncover two categories of scammers that either request secret key phrase submissions from their victims or direct payments to their digital wallets. Furthermore, we obtain scam confirmation by deploying honey wallet addresses and validating private key theft. We also collaborate with the prominent payment service provider by sharing scammer data collections. The payment service provider feedback was consistent with our findings, thereby supporting our methodology and results. By consolidating our analysis across various vantage points, we provide an end-to-end scam lifecycle analysis and propose recommendations for scam mitigation.

Cryptojacking is the permissionless use of a target device to covertly mine cryptocurrencies. With cryptojacking, attackers use malicious JavaScript codes to force web browsers into solving proof-of-work puzzles, thus making money by exploiting the resources of the website visitors. We systematically analyze the static, dynamic, and economic aspects of in-browser cryptojacking to understand and counter such attacks. For static analysis, we perform currency-based and code-based categorization of cryptojacking samples to 1) measure their distribution across websites, 2) highlight their platform affinities, and 3) study their code complexities. We apply machine learning techniques to distinguish cryptojacking scripts from benign and malicious JavaScript samples with 100% accuracy. For dynamic analysis, we analyze the effect of cryptojacking on critical system resources, such as CPU and battery usage. We also perform web browser fingerprinting to analyze the information exchange between the victim node and the dropzone cryptojacking server. We also build an analytical model to empirically evaluate the feasibility of cryptojacking as an alternative to online advertisement. Our results show a sizeable negative profit and loss gap, indicating that the model is economically infeasible. Finally, leveraging insights from our analyses, we build countermeasures for in-browser cryptojacking that improve the existing remedies.

The Bitcoin blockchain safety relies on strong network synchrony. Therefore, violating the blockchain safety requires strong adversaries that control a mining pool with ≈51% hash rate. In this paper, we show that the network synchrony does not hold in the real world Bitcoin network which can be exploited to feasibly violate the blockchain safety and chain quality. Towards that, first we construct the Bitcoin ideal functionality to formally specify its ideal execution model in a synchronous network. We then develop a large-scale data collection system through which we connect with more than 103K IP addresses of the Bitcoin nodes and identify 871 mining nodes. We contrast the ideal functionality against the real world measurements to expose the network anomalies that can be exploited to optimize the existing attacks. Particularly, we observe a non-uniform block propagation pattern among the mining nodes showing that the Bitcoin network is asynchronous in practice. To realize the threat of an asynchronous network, we present the HashSplit attack that allows an adversary to orchestrate concurrent mining on multiple branches of the blockchain to violate common prefix and chain quality properties. We also propose the attack countermeasures by tweaking Bitcoin Core to model the Bitcoin ideal functionality. Our measurements, theoretical modeling, proposed attack, and countermeasures open new directions in the security evaluation of Bitcoin and similar blockchain systems.

FIDO2 is a suite of protocols that combines the usability of local authentication (e.g., biometrics) with the security of public-key cryptography to deliver passwordless authentication. It eliminates shared authentication secrets (i.e., passwords, which could be leaked or phished) and provides strong security guarantees assuming the benign behavior of the client-side protocol components.

The biased distribution of cryptocurrency nodes across Autonomous Systems (ASes) increases the risk of spatial partitioning attacks, allowing an adversary to isolate nodes by hijacking AS prefixes. Prior works on spatial partitioning attacks have mainly focused on the Bitcoin network, showing that the prominent cryptocurrency network can be paralyzed by disrupting the physical topology through BGP hijacks.Despite the persisting threat of BGP hijacks, Bitcoin and other cryptocurrencies have not been frequently targeted, likely due to their shielded overlay topology, which limits the exposure of physical network anomalies. In this paper, we present a new perspective by examining the security of cryptocurrency networks, considering shared network resources (network interdependence). We conduct measurements extending beyond the Bitcoin network and analyze commonalities in Bitcoin, Ethereum, and Ripple node hosting patterns. We observe that all three networks are highly centralized, predominantly sharing the common ASes. We also note that among the three cryptocurrencies, Ripple does not shield its overlay topology, which can be exploited to learn about the physical network anomalies. The observed network anomalies present practical attack strategies that can be launched to target all three cryptocurrencies simultaneously.1We supplement our analysis by surveying recent BGP attacks on high-profile ASes and recognizing a need for application-level countermeasures. We propose attack countermeasures that reduce the risk of spatial partitioning, notwithstanding the increasing centralization of nodes and network interdependence.

Payment Service Providers (PSPs) provide software development toolkits (SDKs) for integrating complex payment processing code into applications. Security weaknesses in payment SDKs can impact thousands of applications. In this work, we propose AARDroid for statically assessing payment SDKs against OWASP’s MASVS industry standard for mobile application security. In creating AARDroid, we adapted application-level requirements and program analysis tools for SDK-specific analysis, tailoring dataflow analysis for SDKs using domain-specific ontologies to infer the security semantics of application programming interfaces (APIs). We apply AARDroid to 50 payment SDKs and discover security weaknesses including saving unencrypted credit card information to files, use of insecure cryptographic primitives, insecure input methods for credit card information, and insecure use of WebViews. These results demonstrate the value of applying security analysis at the SDK granularity to prevent the widespread deployment of insecure code.

Bitcoin is the leading example of a blockchain application that facilitates peer-to-peer transactions without the need for a trusted third party. This paper considers possible attacks related to the decentralized network architecture of Bitcoin. We perform a data driven study of Bitcoin and present possible attacks based on spatial and temporal characteristics of its network. Towards that, we revisit the prior work, dedicated to the study of centralization of Bitcoin nodes over the Internet, through a fine-grained analysis of network distribution, and highlight the increasing centralization of the Bitcoin network over time. As a result, we show that Bitcoin is vulnerable to spatial, temporal, spatio-temporal, and logical partitioning attacks with an increased attack feasibility due to the network dynamics. We verify our observations through data-driven analyses and simulations, and discuss the implications of each attack on the Bitcoin network. We conclude with suggested countermeasures.

The Bitcoin blockchain safety relies on strong network synchrony. Therefore, violating the blockchain safety requires strong adversaries that control a mining pool with 51% hash rate. In this paper, we show that the network synchrony does not hold in the real world Bitcoin network which can be exploited to lower the cost of various attacks that violate the blockchain safety and chain quality. Towards that, first we construct the Bitcoin ideal functionality to formally specify its ideal execution model in a synchronous network. We then develop a large-scale data collection system through which we connect with more than 36K IP addresses of the Bitcoin nodes and identify 359 mining nodes. We contrast the ideal functionality against the real world measurements to expose the network anomalies that can be exploited to optimize the existing attacks. Particularly, we observe a non-uniform block propagation pattern among the mining nodes showing that the Bitcoin network is asynchronous in practice.

The existing Bitcoin security research has mainly followed the security models in [22, 35], which stipulate that an adversary controls some mining power in order to violate the blockchain consistency property (i.e., through a double-spend attack). These models, however, largely overlooked the impact of the realistic network synchronization, which can be manipulated given the permissionless nature of the network. In this paper, we revisit the security of Bitcoin blockchain by incorporating the network synchronization into the security model and evaluating that in practice. Towards this goal, we propose the ideal functionality for the Bitcoin network synchronization and specify bounds on the network outdegree and the block propagation delay in order to preserve the consistency property. By contrasting the ideal functionality against measurements, we find deteriorating network synchronization reported by Bitnodes and a notable churn rate with 10% of the nodes arriving and departing from the network daily.

The Bitcoin network synchronization is crucial for its security against partitioning attacks. From 2014 to 2018, the Bitcoin network size has increased, while the percentage of synchronized nodes has decreased due to block propagation delay, which increases with the network size. However, in the last few months, the network synchronization has deteriorated despite a constant network size. The change in the synchronization pattern suggests that the network size is not the only factor in place, necessitating a root cause analysis of network synchronization. In this paper, we perform a root cause analysis to study four factors that affect network synchronization: the unreachable nodes, the addressing protocol, the information relaying protocol, and the network churn. Our study reveals that the unreachable nodes size is 24x the reachable network size. We also found that the network addressing protocol does not distinguish between reachable and unreachable nodes, leading to inefficiencies due to attempts to connect with unreachable nodes/addresses. We note that the outcome of this behavior is a low success rate of the outgoing connections, which reduces the average outdegree. Through measurements, we found malicious nodes that exploit this opportunity to flood the network with unreachable addresses. We also discovered that Bitcoin follows a round-robin relaying mechanism that adds a small delay in block propagation. Finally, we observe a high churn in the Bitcoin network where ≈8 % nodes leave the network every day. In the last few months the churn among synchronized nodes has doubled, which is likely the most dominant factor in decreasing network synchronization. Consolidating our insights, we propose improvements in Bitcoin Core to increase network synchronization.

Blockchain applications that rely on the Proof-of-Work (PoW) have increasingly become energy inefficient with a staggering carbon footprint. In contrast, energy efficient alternative consensus protocols such as Proof-of-Stake (PoS) may cause centralization and unfairness in the blockchain system. To address these challenges, we propose a modular version of PoS-based blockchain systems called e-PoS that resists the centralization of network resources by extending mining opportunities to a wider set of stakeholders. Moreover, e-PoS leverages the in-built system operations to promote fair mining practices by penalizing malicious entities. We validate e-PoS 's achievable objectives through theoretical analysis and simulations. Our results show that e-PoS ensures fairness and decentralization, and can be applied to existing blockchain applications.

Blockchain-based audit trails provide a consensus-driven and tamper-proof trail of system events that are helpful in creating provenance in enterprise solutions. However, taking into account the transaction bulk generated by these applications and the throughput limitations of existing blockchains, a single ledger for record keeping can be inefficient and costly. To that end, we see an imperative need for a new blockchain design that is capable of addressing current challenges, without compromising security and provenance. Hence, we propose BlockTrail, a scalable and efficient blockchain solution for auditing applications. BlockTrail fragments the legacy blockchain systems into layers of co-dependent hierarchies, thereby reducing the time and space complexity, and increasing the throughput. BlockTrail is prototyped on "Practical Byzantine Fault Tolerance" (PBFT) protocol with a custom-built blockchain. Experiments with BlockTrail show that compared to the conventional schemes, BlockTrail is more efficient, and has less storage footprint.

Bitcoin is the leading example of a blockchain application that facilitates peer-to-peer transactions without the need for a trusted intermediary. This paper considers possible attacks related to the decentralized network architecture of Bitcoin. We perform a data driven study of Bitcoin and present possible attacks based on spatial and temporal characteristics of its network. Towards that, we revisit the prior work, dedicated to the study of centralization of Bitcoin nodes over the Internet, through a fine-grained analysis of network distribution, and highlight the increasing centralization of the Bitcoin network over time. As a result, we show that Bitcoin is vulnerable to spatial, temporal, spatio-temporal, and logical partitioning attacks with an increased attack feasibility due to network dynamics. We verify our observations by simulating attack scenarios and the implications of each attack on the Bitcoin . We conclude with suggested countermeasures.

In this paper, we highlight a new form of distributed denial of service (DDoS) attack that impacts the memory pools of cryptocurrency systems causing massive transaction backlog and higher mining fees. Towards that, we study such an attack on Bitcoin mempools and explore its effects on the mempool size and transaction fees paid by the legitimate users. We also propose countermeasures to contain such an attack. Our countermeasures include fee-based and age-based designs, which optimize the mempool size and help to counter the effects of DDoS attacks. We evaluate our designs using simulations in diverse attack conditions.

Audit logs serve as a critical component in the enterprise business systems that are used for auditing, storing, and tracking changes made to the data. However, audit logs are vulnerable to a series of attacks, which enable adversaries to tamper data and corresponding audit logs. In this paper, we present BlockAudit: a scalable and tamper-proof system that leverages the design properties of audit logs and security guarantees of blockchains to enable secure and trustworthy audit logs. Towards that, we construct the design schema of BlockAudit, and outline its operational procedures. We implement our design on Hyperledger and evaluate its performance in terms of latency, network size, and payload size. Our results show that conventional audit logs can seamlessly transition into BlockAudit to achieve higher security, integrity, and fault tolerance.