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), leaving users with worthless tokens. Although rug pulls in Ethereum and Binance Smart Chain (BSC) have gained attention recently, analysis of rug pulls in Solana remains largely under-explored. In this paper, we introduce SolRPDS (Solana Rug Pull Dataset), the first public rug pull dataset derived from Solana's transactions. We examine approximately four years of DeFi data (2021-2024) that covers suspected and confirmed tokens exhibiting rug pull patterns. The dataset, derived from 3.69 billion transactions, consists of 62,895 suspicious liquidity pools. The data is annotated for inactivity states, which is a key indicator, and includes several detailed liquidity activities such as additions, removals, and last interaction as well as other attributes such as inactivity periods and withdrawn token amounts, to help identify suspicious behavior. Our preliminary analysis reveals clear distinctions between legitimate and fraudulent liquidity pools and we found that 22,195 tokens in the dataset exhibit rug pull patterns during the examined period. SolRPDS can support a wide range of future research on rug pulls including the development of data-driven and heuristic-based solutions for real-time rug pull detection and mitigation.

Singapore, Jan. 08, 2023 (GLOBE NEWSWIRE) -- A platform launched by DefiLabs in 2021 is now ready to harness the power of Artificial Intelligence (AI) to revolutionize the world of decentralized finance (DeFi). DefiLabs is a fully intelligent and decentralized asset management crypto staking platform which is built on Binance Smart Chain. DefiLabs uses artificial intelligence based on quantum algorithms to dynamically manage portfolios, perform efficient asset allocation, and predictively model asset management strategies. Thus, make profits for users in different fields such as lending, leverage mining, and cross-chain mining to improve their portfolio in the fast-paced world of DeFi. DefiLabs deploy an ecosystem of Artificial Intelligence to support trading decisions on DefiLabs which will help increase the value and returns of the users by providing liquidity to DeFi markets.

The first automated market maker (AMM) that integrates Yield Farming with Artificial Intelligence (AI). Artichain is a decentralized finance (DeFi) platform that runs on Binance Smart Chain (BSC) with incorporated features that easily let you earn tokens. Gain access to trade, earn and win big on the platform through ArtiChain Swap. ArtiChain Swap allows users to exchange their digital assets for an equivalent portion in tokens either through staking, farming or liquidity pool, thus increasing their digital assets value. Artichain Swap exchange to allow you trade against a liquidity pool and receive extra income gained from the trading fees.

AI and machine learning network Fetch.ai As mentioned in a blog post by Fetch.ai: "GLOW-DRB is a new decentralized random beacon that [aims to] provide incorruptible sources of randomness for decentralized applications. A "decentralized" Random Beacon is an "incorruptible" (cannot be altered by unauthorized or unapproved entities) and "unpredictable" source of randomness that is computed or calculated by several different parties in a manner that no individual or entity is able to interrupt or interfere with its calculation or "bias its value." These randomness techniques may be used in software programs that require the coordination of several different parties in environments that need high degrees of trust (for e.g., like in the finance or healthcare sectors). As explained by the Fetcha.ai DRB can, for instance, be used to determine which cryptocurrency trades may be matched in decentralized or non-custodial exchanges. The randomness values may also be used to deal cards in a "decentralized" game of poker, choose the winner of a lottery, or determine which service provider in a transport consortium should carry out a delivery. GLOW-DRB differs from the previous BLS scheme in its ability to achieve more reliable security levels known as pseudorandomness, which means that no single node can obtain any information on the random beacon value before other nodes have made their contribution to the multi-party computation."