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Paper – A First Look at Zoombombing

A First Look at Zoombombing. Chen Ling, Utkucan Balcı, Jeremy Blackburn, Gianluca Stringhini. Computers and Society. arXiv:2009.03822 [cs.CY].

“Abstract—Online meeting tools like Zoom and Google Meethave become central to our professional, educational, and personal lives. This has opened up new opportunities for large scale harassment. In particular, a phenomenon known as zoombombing has emerged, in which aggressors join online meetings with the goal of disrupting them and harassing their participants.In this paper, we conduct the first data-driven analysis of calls for zoombombing attacks on social media. We identify ten popular online meeting tools and extract posts containing meeting invitations to these platforms on a mainstream social network, Twitter, and on a fringe community known for organizing coordinated attacks against online users, 4chan. We then perform manual annotation to identify posts that are calling for zoombombing attacks, and apply thematic analysis to develop a codebook to better characterize the discussion surrounding calls for zoombombing. During the first seven months of 2020,we identify over 200 calls for zoombombing between Twitter and 4chan, and analyze these calls both quantitatively and qualitatively. Our findings indicate that the vast majority of calls for zoombombing are not made by attackers stumbling upon meeting invitations or brute forcing their meeting ID, but rather by insiders who have legitimate access to these meetings,particularly students in high school and college classes. This has important security implications, because it makes common protections against zoombombing, such as password protection,ineffective. We also find instances of insiders instructing attackers to adopt the names of legitimate participants in the class to avoid detection, making countermeasures like setting up a waiting room and vetting participants less effective. Based on these observations, we argue that the only effective defense against zoombombing is creating unique join links for each participant

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