PDFPhantom: Exploiting PDF Attacks Against Academic Conferences' Paper Submission Process with Counterattack

Abstract

First launched nearly three decades ago, PDF, which stands for Portable Document Format, has become one of the most common formats for text documents. Nowadays, PDF is widely used by individuals, companies, and organizations. At most notable academic conferences, including IEEEs, papers are required to be submitted in PDF format. Along with its increasing popularity in recent times, PDF has been a target for many attacks, some of which are called content-masking attacks. Content-masking attacks are based on the idea of causing underlying text, which is extracted by text-mining softwares and read by machines, to be displayed differently to humans. Inspired by the same idea but is designed and implemented differently, our proposed attack is against the paper submission process at large academic conferences, which consists of two subprocesses: plagiarism detection and automatic assignment of reviewers to papers. Our attack overcomes many weaknesses of previous attacks. In addition, we introduce a method to avoid content masking attacks against the automatic reviewers' assignment process by preventing attackers from getting true topic information from PDF documents.