EventChain: A Blockchain Framework for Secure, Privacy-Preserving Event Verification - Schwarz-Rüsch, Signe; Behlendorf, Michael; Becker, Markus Horst; Kudlek, René; Mohamed, Hesham Hosney Elsayed; Schoenitz, Felix; Jehl, Leander; Kapitza, Rüdiger (23rd ACM/IFIP International Middleware Conference, 2022)
The number of fake news written by bots or malicious actors on social media is rising. One cause is the ability of users to post anything, at any place, at any time. This offers great flexibility, but it also poses the risk that users share misinformation. One type includes events that allegedly have occurred in a location, without the reporting user necessarily having been present. A user may add her location to posts to appear as an eyewitness and thus more trustworthy; however, basing that trust on commonly used and easily faked GPS locations is not reasonable. We present EventChain, which enriches social media posts with hard to fake trust scores based on the user's recent motion profile to give actual eyewitnesses more credibility. Users' motion profiles are integrity- and privacy-preservingly logged in a blockchain. Once the user posts an event, her locality is evaluated for a location rating. The location evaluation is secured by a trusted execution environment to ensure users' location data is private and under the users' control at all times. EventChain also enables interactive assessments of a post via nearby users, whose location is similarly evaluated. This way other eyewitnesses can credibly provide further information, thus leading to a consensus about the event's actual occurrences, increasing trust in social media posts, and limiting the spread of fake new
Keywords: Blockchain; TEE; Location Privacy; Fake News