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The World Wide Web, a ubiquitous source of information, serves as a primaryresource for countless individuals, amassing a vast amount of data from globalinternet users. However, this online data, when scraped, indexed, and utilizedfor activities like web crawling, search engine indexing, and, notably, AImodel training, often diverges from the original intent of its contributors.The ascent of Generative AI has accentuated concerns surrounding data privacyand copyright infringement. Regrettably, the web's current framework fallsshort in facilitating pivotal actions like consent withdrawal or data copyrightclaims. While some companies offer voluntary measures, such as crawler accessrestrictions, these often remain inaccessible to individual users. To empoweronline users to exercise their rights and enable companies to adhere toregulations, this paper introduces a user-controlled consent tagging frameworkfor online data. It leverages the extensibility of HTTP and HTML in conjunctionwith the decentralized nature of distributed ledger technology. With thisframework, users have the ability to tag their online data at the time oftransmission, and subsequently, they can track and request the withdrawal ofconsent for their data from the data holders. A proof-of-concept system isimplemented, demonstrating the feasibility of the framework. This work holdssignificant potential for contributing to the reinforcement of user consent,privacy, and copyright on the modern internet and lays the groundwork forfuture insights into creating a more responsible and user-centric webecosystem.

Tag Your Fish in the Broken Net: A Responsible Web Framework for Protecting Online Privacy and Copyright