Cryptocurrency has transformed finance and investment, with platforms like Uniswap facilitating billions of dollars in trades. However, malicious smart contracts and scam tokens have led to significant financial losses for decentralized finance (DeFi) users. Code analysis alone cannot detect rug pulls using social engineering tactics. To address this issue, machine learning algorithms can leverage the vast amount of transactional data stored on the blockchain, particularly time series data, to identify scam tokens. This study aims to determine the optimal timeframe for detecting rug pulls and highlights the importance of token volume and transaction count features. The findings suggest that shorter timeframes are sufficient for detecting rug pull tokens since most incidents occur soon after token creation. This research offers new insights into scam token classification and prevention and contributes to a broader understanding of this field. • Rug pull detection in Uniswap V3 is researched via on-chain indicators over time. • Many rug pulls occur during the first day after token creation. • Time windows close to rug pull events significantly influence the model's predictions.
Blockchain aggregators play an instrumental role in the evolution of blockchain technology, serving as pivotal enablers of interoperability, efficiency, and user accessibility in an increasingly decentralized digital world. However, the literature on this emerging technology is scarce and is not systematized, making it harder for practitioners and researchers to understand the field. In this paper, we systematize bridge aggregators, a type of blockchain aggregators. We present an exhaustive analysis of a diverse array of token and message aggregators, each distinguished by its unique architecture. Our research delves into critical aspects of these aggregators, encompassing their functionality, security measures, pricing models, and latency. This research aims to provide readers, users, and developers with insightful and actionable information, facilitating informed navi-gation through the complex landscape of blockchain aggregators. We explore our findings and compare them with our intuitive expectations. We show that there is a value in centralizing token aggregators. Message aggregators are found to be more powerful but less efficient in transaction cost and latency. Finally, we propose a set of future research directions for practitioners.
Xin Zhou, Liaoyi Ning, Bin Wang, Chao Yang · 6 authors
Load shedding scheme is utilized to deal with black-outs caused by continuously growing loads. Conventional load shedding scheme repressively shed interruptible loads ignoring the economic profits of them. This paper proposes a smart contract based load shedding scheme in an industrial park. The proposed scheme incentivizes factories in the industrial park to actively shed their interruptible loads by designing a market that maximizes the total social welfare. Furthermore, the load shedding process is implemented using a smart contract to automatically obtain trustable and transparent load shedding results. The modified IEEE 33-bus distribution case proves that the proposed load shedding scheme effectively increases the profits of all participating factories and incentivizes them to shed their interruptible loads.
Nowadays, searching for parking is a tedious and cruising task. Also, static parking pricing leads to traffic congestion, air pollution, and illegal parking in parking areas because the driver always chooses the nearest parking. Intelligent Transportation System (ITS) mainly focuses on roadside traffic and road issues, while parking problems are generally not considered. But, parking a vehicle consumes a major time of traveling trip. Hence, it is required to research parking management and pricing. In this article, we have proposed Artificial Intelligence (AI) and Blockchain (BC) based integrated architecture to predict parking availability and parking pricing rates based on vehicle type and nonpeak time (i.e., demand is low). Prices are predicted based on distance, time, provided services, vehicle type using intelligent algorithms. All parking service providers are connected to the BC Network (BN), which brings them at the same platform for fair and transparent pricing distribution. Also, BC ensures the security and privacy of parking service provider's and driver's information. We have also presented the performance evaluation and result analysis of the proposed model.
Based on the reliability mechanism of biological system, the design theories and methods of high reliabe power electronic system, includingautonomous decentralized control,redundancy design, intelligent design, self-reproducion and self-repair, self-adaptive and self-organization control, are firstly described in detail. The research results show that the reliabi1ity of complex power electronic systems is improved markedly in these bionic methods. The power electronics technology can draw some research inspiration from living being. And bionics will have wide applications in the field of power electronics. As a concept Autonomous Cell (AC) and Autonomous Decentralized Power Electric System (ADPES) are defined. It is pointed that AC is autonomous controllable and autonomous cooperative. Based on AC, ADPES is built.A novel autonomous decentralized single-phase inverter of high reliability is inverstigated in the method of bionic. Bionic design methods of power electronics system are original from methodological point of view in this paper. Theresearch in this paper is a practical guide to the applications of bionics on power electronics, especial on design of high reliable power electronics systems.