LIJDLR

DIGITAL IDENTITY PROTECTION IN THE ERA OF AI AND DEEPFAKES

Adv. Nivedita Pandey, 3rd Semester, LLM in Intellectual Property Rights, student at KES' Shri Jayatilal H. Patel Law College, Independent Advocate practicing at Bombay High Court and Metropolitan Magistrates courts in Mumbai (India)

In a world heading towards a growing trend in obligation to have an online presence whether for the purpose of business or being a professional influencer, a sudden spike in cyber-crimes related to data identity theft with the aid of AI and Deepfakes have become prevalent. Identity of a person is attached to their reputation and dignity in the society, however, this element of a person’s being is being blatantly tarnished for selfish motives by certain individuals. This paper examines the difficulties faced by the government as well as the people in protecting their Digital Identities, the threats posed by the circulation of Deepfakes, the disparity existing between the celebrities and the non-celebrities in effectively finding a remedy against their Identity Theft and protecting their right to privacy as enshrined in Article 21 of Indian Constitution in intersection with the post mortem privacy aspect. It critically examines the global laws of various countries in terms of their effectiveness and swiftness in protecting the identity of their citizens against the Deepfakes with the special focus on Denmark’s historic proposal to amend its Copyright law in order to avail its citizens the right to protect their Personal Identity under the same. The legislation, which is still under consideration, if passed, will allow an individual to have complete legal ownership of their Personal Identity. The study concludes by suggesting how Denmark’s proposal can be used as a global model to bring about a change in the International IPR laws in protecting Digital Identity.

📄 Type 🔍 Information
Research Paper LawFoyer International Journal of Doctrinal Legal Research (LIJDLR), Volume 4, Issue 3, Page 01–12.
🔗 Creative Commons © Copyright
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License . © Authors, 2026. All rights reserved.