Explore a comprehensive analysis of linguistic-collision search poisoning attacks in this 18-minute IEEE conference talk. Delve into the first large-scale study examining 1.77 million misspelled search terms on Google and Baidu, focusing on English and Chinese languages. Learn about the sophisticated attack method targeting queries where misspelled terms are legitimate words in other languages, evading auto-correction mechanisms. Discover how a deep learning model improves the collection rate of linguistic-collision search terms by 2.84x compared to random sampling. Gain insights into the prevalence of abuse, with 1.19% of linguistic-collision search terms on major search engines leading to malicious websites. Understand the main target categories for cybercriminals, including gambling, drugs, and adult content. Examine the disproportionate impact on mobile device users and explore potential mitigation strategies for this emerging threat in search engine poisoning.