Disguised interactions: an empirical study on socially evolved comment bots and their underlying scam campaigns in youtube

Abstract

This paper presents a pioneering investigation into a novel form of scam advertising method on YouTube, termed “Social Scam Bots” (SSBs). These bots have evolved to emulate benign user behavior by posting comments and engaging with other users, oftentimes appearing prominently among the top rated comments. We analyzed the YouTube video comments and proposed a method to identify SSBs and extract the underlying scam domains. Our study revealed 2,114 SSBs promoting more than 18 scam campaign groups responsible for infecting 30.49% of crawled videos. Further investigation revealed that SSBs exhibit advances that surpass traditional bots. Notably, they demonstrated understanding of the target audience by aligning scam campaigns with the specific video content, effectively leveraging the YouTube recommendation algorithm. We monitored these SSBs for six months and conducted a follow-up assessment after an additional six-month period, enabling us to evaluate the effectiveness of YouTube's mitigation efforts. We uncovered various strategies employed by SSBs to evade mitigation attempts, including a novel strategy called “self-engagement," aimed at boosting the ranking of their comments. By shedding light on the phenomenon of SSBs and their evolving tactics, our study aims to raise awareness and contribute to the prevention of these malicious actors, ultimately fostering a safer online platform.