Malicious Removal Research Articles

Full Characterization of a Class of Graphs Tailored for Software Watermarking

Digital watermarks have been regarded as a promising way to fight copyright violations in the software industry. In some graph-based watermarking schemes, identification data is disguised as control-flow graphs of dummy code. Recently, Chroni and Nikolopoulos proposed an ingenious such scheme whereby an integer is encoded into a particular kind of permutation graph. We give a formal characterization of the class of graphs generated by their encoding function, which we call canonical reducible permutation graphs. A linear-time recognition algorithm is also given, setting the basis for a polynomial-time algorithm to restore watermarks that underwent the malicious removal of some edges. Finally, we give a simpler decoding algorithm for Chroni and Nikolopoulos’ watermarks.

Watermarking Relying on Cover Signal Content to Hide Synchronization Marks

In watermarking, the exploitation of synchronization marks embedded within the cover signal has been widely used to provide robustness against geometrical distortions. However, in most schemes, synchronization marks are easily detectable which makes them vulnerable to malicious removal or tampering. Relying on embedded signals which exhibit strong reference features to recover synchronization can therefore lead to security flaws in the watermarking system. In this paper, we present and discuss the synchronization recovery process through detection of the periodicity of the embedded signal. We then propose a scheme to hide synchronization marks through the modulation of the embedded signal by a content-based pseudo-random signal. We study the robustness of this pseudo-random masking signal and illustrate the efficiency of this approach on watermark patterns with a periodic structure.