Abstract
The authors explore the issue of safeguarding personal data, particularly its identifying components, in the context of the Internet. Doxing, a criminal act involving the unauthorized collection of information and its public dissemination without the owner’s consent, has gained significant traction on social media platforms, where identifying information can be quickly spread and misused against individuals. Large language models (artificial intelligence) are integrated into many software programs designed to protect personal data. However, in light of large-scale data breaches, the authors raise concerns about the liability of entities or individuals who fail to adequately secure such data, especially when cyber incidents are linked to the use of AI. The rapid advancement and widespread use of artificial intelligence contribute to these growing concerns. In 2023, the emergence of several language models facilitated both the manipulation and aggregation of data, exacerbating the problem. The authors express serious concerns about ensuring user privacy and information security in a landscape increasingly shaped by open-source intelligence and the further exploitation of such data. In an era where personal data has become a highly valuable commodity, protecting it has become a priority for governments worldwide. In light of this, the authors aim to examine and synthesize international legal approaches to safeguarding the right to privacy and regulating the protection of personal (identifying) information on the Internet. The study relies on general scientific methods of inquiry, including comparative analysis and modelling. The authors conclude that cyberattacks, the theft of personal data, the increasing use of open-source intelligence, the penetration of digital identification technologies into all socio-economic processes, and the proliferation of the Internet of Things pose real threats to individual privacy and the security of identifying information as a critical component of personal data.
Published Version
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