Emerging from the research lab of San Diego State University, an artificial intelligence (AI) algorithm, coined GiveawayScamHunter, has become a beacon against the backdrop of rising cryptocurrency scams. A year-long study from June 2022 to June 2023 observed Twitter’s network for such transgressions, and GiveawayScamHunter revealed a shocking 95,111 scam lists, orchestrated by 87,617 accounts.
Appropriating this state-of-the-art technology, the researchers extracted pivotal data such as web addresses linked to the scams and new entries of scam-associated cryptocurrency wallets. It was estimated that during the one-year tenure, more than 365 victims fell prey to such scams, resulting in losses exceeding $872,000. Such figures bring light to the pervasive presence of cyber threats in the ever-evolving cryptocurrency landscape.
In the meantime, Twitter Lists, an otherwise beneficial networking feature, turned into an exploitable platform owing to its permissionless nature. To sieving out such scam-entangled lists, a linguistic computational tool was trained on pre-identified scam data. This ingenious approach unveiled about 100,000 new instances of scam interactions and led to the unearthing of previously undisclosed scam-associated domains and wallets.
Ensuring transparency, the researchers have shared these findings with Twitter and the cryptocurrency community. Amidst these revelations, a significant concern is that nearly 44% of the associated accounts were still operational at the time of their paper’s publication. This necessitates not only a relentless hunt for these fraudsters but also preemptive steps to inhibit the extensive scam propagation on social media platforms.
Simultaneously, the AI technology, traditionally considered a deterrent, has surprisingly found proponents among scammers to devise new deceit strategies. AI-powered tools amplify their deceptive reach, create a facade of fake followers, lending credibility to their scam campaigns. The use of AI chatbots to interact with potential victims, offering dubious investment schemes or promoting non-existent cryptos, has become commonplace. This propels the question of social proof-of-work reliability, which predicates project legitimacy based on its follower strength.
In a disturbing application of AI, “pig butchering” scams are instances where AI entities befriend potentially vulnerable victims over several days, only to eventually defraud them. This highlights the double-edged nature of advancements like AI, offering numerous possibilities on one hand and posing novel threats on the other. As we navigate these digital landscapes, we must stay vigilant, value transparency, and stay abreast of the emerging technological frontiers.
Source: Cryptonews
