Book

As blockchain technology and decentralized finance rapidly reshape the global economy, the absence of traditional gatekeepers has opened the door to unprecedented financial risks. Millions of investors fall victim to sophisticated scams every day, ranging from sudden rug pulls and honeypot smart contracts to hidden Ponzi schemes and malicious market manipulation. Spotting the Fake: AI-Driven Detection of Fraudulent Cryptocurrencies by Dr. Ali Mohammadiounotikandi offers a definitive, cutting-edge solution to this growing crisis. Spanning twelve comprehensive chapters, this book serves as an essential manual for navigating the dark side of digital assets. It bridges the critical gap between artificial intelligence, cybersecurity, and blockchain forensics, equipping developers, compliance officers, researchers, and serious investors with the tools needed to outsmart bad actors. Readers will explore the taxonomy of crypto fraud, learn how to extract powerful on-chain and off-chain features, and master traditional machine learning models alongside advanced Graph Neural Networks to track suspicious wallet behaviors and sybil clusters. Furthermore, the book dives deep into Natural Language Processing to analyze whitepapers and social media hype, while leveraging Large Language Models and automated static analysis to audit smart contracts for malicious code. By integrating regulatory compliance frameworks like MiCA and FATF with real-time anomaly detection, this book empowers you to move beyond superficial hype and uncover the truth behind deceptive tokenomics. Transform your approach to digital asset security, protect your capital, and learn how to build a safer, more transparent cryptographic ecosystem before the next fraud strikes.