Milivoj Simeonovski
M.Sc. | Researcher

Curriculum Vitae

I am a PhD student at Saarland University, Germany. I work in the Information Security & Cryptography group of Prof. Michael Backes. Since October 2012 I hold a scholarship of the International Max Planck Research School for Computer Science (IMPRS-CS) .

--Work Experience--
2010 - 2012 Network Engineer and IT Security NLB Tutunska Banka, A.D. Skopje
2008 - 2010 Software Developer NLB Tutunska Banka, A.D. Skopje
2011 - 2012 Part-time Android Software Developer DDN Media
2008 - 2009 Part-time System Administrator Evolution IT
2007 - 2009 Research Assistant SAFE EMF Project - FP6, INCO-CT-2007-043638


  • 2012 – Scholarship by the Graduate School of Computer Science;
    Admission to the Graduate School at the Saarland University including funding for the PhD preparation phase.
  • 2012 – PhD Scholarship of the International Max Planck Research School for Computer Science;
    Admission into the IMPRS-CS including funding for the PhD.



Search engines are the prevalently used tools to collect information about individuals on the Internet. Search results typically comprise a variety of sources that contain personal information -- either intentionally released by the person herself, or unintentionally leaked or published by third parties, often with detrimental effects on the individual\'s privacy. To grant individuals the ability to regain control over their disseminated personal information, the European Court of Justice recently ruled that EU citizens have a right to be forgotten in the sense that indexing systems, must offer them technical means to request removal of links from search results that point to sources violating their data protection rights. As of now, these technical means consist of a web form that requires a user to manually identify all relevant links upfront and to insert them into the web form, followed by a manual evaluation by employees of the indexing system to assess if the request is eligible and lawful. We propose a universal framework Oblivion to support the automation of the right to be forgotten in a scalable, provable and privacy-preserving manner. First, Oblivion enables a user to automatically find and tag her disseminated personal information using natural language processing and image recognition techniques and file a request in a privacy-preserving manner. Second, Oblivion provides indexing systems with an automated and provable eligibility mechanism, asserting that the author of a request is indeed affected by an online resource. The automated ligibility proof ensures censorship-resistance so that only legitimately affected individuals can request the removal of corresponding links from search results. We have conducted comprehensive evaluations, showing that Oblivion is capable of handling 278 removal requests per second, and is hence suitable for large-scale deployment.