Seung Ho Na
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 1,134 SSBs promoting 72 scam campaigns responsible for infecting 31.73% of crawled videos. Further investigation revealed that SSBs exhibit advances that surpass traditional bots. Notably, they targeted specific audience by aligning scam campaigns with related video content, effectively leveraging the YouTube recommendation algorithm. We monitored these SSBs over a period of six months, enabling us to evaluate the effectiveness of YouTube's mitigation efforts. We also uncovered various strategies they use to evade mitigation attempts, including a novel strategy called "self-engagement," aimed at boosting their comment ranking. 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.
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Index Terms
- Evolving Bots: The New Generation of Comment Bots and their Underlying Scam Campaigns in YouTube
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