Related papers: LROO Rug Pull Detector: A Leakage-Resistant Framew…
Rug pull is a critical attack in the world of blockchain technology. Despite this, the absence of sufficient time-bound and well-structured datasets is considered one of the significant issues faced while identifying early detection.…
Rug pull scams have emerged as a persistent threat to cryptocurrency, causing significant financial losses. A typical scenario involves scammers deploying honeypot contracts to attract investments, restricting token sales, and draining the…
Solana has experienced rapid growth due to its high performance and low transaction costs, but the extremely low barrier to token issuance has also led to widespread Rug Pulls. Unlike Ethereum-based Rug Pulls that rely on malicious smart…
This paper presents a machine learning framework for the early detection of rug pull scams on decentralized exchanges (DEXs) within The Open Network (TON) blockchain. TON's unique architecture, characterized by asynchronous execution and a…
The explosive growth of Non-Fungible Tokens (NFTs) has revolutionized digital ownership by enabling the creation, exchange, and monetization of unique assets on blockchain networks. However, this surge in popularity has also given rise to a…
Rug pulls in Solana have caused significant damage to users interacting with Decentralized Finance (DeFi). A rug pull occurs when developers exploit users' trust and drain liquidity from token pools on Decentralized Exchanges (DEXs),…
Rug pulls pose a grave threat to the cryptocurrency ecosystem, leading to substantial financial loss and undermining trust in decentralized finance (DeFi) projects. With the emergence of new rug pull patterns, research on rug pull is out of…
Rugsafe introduces a comprehensive protocol aimed at mitigating the risks of rug pulls in the cryptocurrency ecosystem. By utilizing cryptographic security measures and economic incentives, the protocol provides a secure multichain system…
Uniswap, like other DEXs, has gained much attention this year because it is a non-custodial and publicly verifiable exchange that allows users to trade digital assets without trusted third parties. However, its simplicity and lack of…
Current methods to prevent crypto asset fraud are based on the analysis of transaction graphs within blockchain networks. While effective for identifying transaction patterns indicative of fraud, it does not capture the semantics of…
In recent years, Decentralized Finance (DeFi) grows rapidly due to the development of blockchain technology and smart contracts. As of March 2023, the estimated global cryptocurrency market cap has reached approximately $949 billion.…
Illicit transaction detection is often driven by transaction level attributes however, fraudulent behavior may also manifest through network structure such as central hubs, high flow intermediaries, and coordinated neighborhoods. This paper…
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…
NFT rug pull is one of the most prominent type of scam that the developers of a project abandon it and then run away with investors' funds. Although they have drawn attention from our community, to the best of our knowledge, the NFT rug…
The high-frequency issuance and short-cycle speculation of meme tokens in decentralized finance (DeFi) have significantly amplified rug-pull risk. Existing approaches still struggle to provide stable early warning under scarce anomalies,…
The explosive growth of non-fungible tokens (NFTs) on Web3 has created a new frontier for digital art and collectibles, but also an emerging space for fraudulent activities. This study provides an in-depth analysis of NFT rug pulls, which…
Smart contracts on blockchains are prone to diverse security vulnerabilities that can lead to significant financial losses due to their immutable nature. Existing detection approaches often lack flexibility across vulnerability types and…
This paper proposes a Hadith-inspired multi-axis trust modeling framework, motivated by a structurally analogous problem in classical Hadith scholarship: assessing the trustworthiness of information sources using interpretable,…
Continuous generation of streaming data from diverse sources, such as online transactions and digital interactions, necessitates timely fraud detection. Traditional batch processing methods often struggle to capture the rapidly evolving…
AI data centers which are GPU centric, have adopted liquid cooling to handle extreme heat loads, but coolant leaks result in substantial energy loss through unplanned shutdowns and extended repair periods. We present a proof-of-concept…