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Ethereum Phishing Scam Detection Based on Data Augmentation Method and Hybrid Graph Neural Network Model [PDF]
SensorsThe rapid advancement of blockchain technology has fueled the prosperity of the cryptocurrency market. Unfortunately, it has also facilitated certain criminal activities, particularly the increasing issue of phishing scams on blockchain platforms such as
Zhen Chen +5 more
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Detection of Internet scam using logistic regression [PDF]
2011 IEEE International Conference on Systems, Man, and Cybernetics, 2011 Internet scam is fraudulent or intentionally misleading information posted on the web, usually with the intent of tricking people into sending money or disclosing sensitive information. We describe an application of logistic regression to detection of Internet scam. The developed system automatically collects 43 characteristic statistics about websites
Eugene Fink, Jaime G Carbonell
exaly +3 more sources
Do Not Rug on Me: Leveraging Machine Learning Techniques for Automated Scam Detection
Mathematics, 2022 Uniswap, as with 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.
Bruno Mazorra, Victor Adan, Vanesa Daza
doaj +6 more sources
Eth-PSD: A Machine Learning-Based Phishing Scam Detection Approach in Ethereum
IEEE Access, 2022 Recently, the rapid flourish of blockchain technology in the financial field has attracted many cybercriminals’ attention to launching blockchain-based attacks such as ponzi schemes, scam wallets, and phishing scams.
Arkan Hammoodi Hasan Kabla +3 more
doaj +3 more sources
A lightweight wheat ear counting model in UAV images based on improved YOLOv8 [PDF]
Frontiers in Plant ScienceWheat (Triticum aestivum L.) is one of the significant food crops in the world, and the number of wheat ears serves as a critical indicator of wheat yield.
Ruofan Li +13 more
doaj +2 more sources
Blockchain: Research and Applications, 2022 The “Bitcoin Generator Scam” (BGS) is a cyberattack in which scammers promise to provide victims with free cryptocurrencies in exchange for a small mining fee. In this paper, we present a data-driven system to detect, track, and analyze the BGS. It works
Emad Badawi +2 more
doaj +3 more sources
SMS Scam Detection Application Based on Optical Character Recognition for Image Data Using Unsupervised and Deep Semi-Supervised Learning [PDF]
SensorsThe growing problem of unsolicited text messages (smishing) and data irregularities necessitates stronger spam detection solutions. This paper explores the development of a sophisticated model designed to identify smishing messages by understanding the ...
Anjali Shinde +5 more
doaj +2 more sources
IEEE AccessThe surge in cryptocurrencies has been accompanied by a significant rise in scams, underscoring the critical need for precise scam detection. Cryptocurrency markets and transaction networks are dynamic, leading to evolving scam tactics and transaction ...
Min-Woo Nam, Hyeon-Ju Lee, Seok-Jun Buu
doaj +3 more sources
FSCA-YOLO: An Enhanced YOLO-Based Model for Multi-Target Dairy Cow Behavior Recognition [PDF]
AnimalsIn real-world dairy farming environments, object recognition models often suffer from missed or false detections due to complex backgrounds and cow occlusions.
Ting Long +5 more
doaj +2 more sources
An Intelligent Obstacle Detection Method for Rail Transit Scenarios [PDF]
SensorsTraditional signal equipment is incapable of real-time monitoring of foreign objects intruding into track zones. To effectively ensure the operational safety of trains, this paper presents an intelligent obstacle detection approach of visual sensing for ...
Zhao Sheng +5 more
doaj +2 more sources