Aweke Lemma

In a forensic watermarking architecture, a buyer-seller protocol protects the watermark secrets from the buyer and prevents false infringement accusations by the seller. Existing protocols encrypt the watermark and the content with a homomorphic public-key cipher and perform embedding under encryption. When used for multimedia data, these protocols create a large computation and bandwidth overhead. In this correspondence, we show that the same functionality can be achieved efficiently using recently proposed secure watermark embedding algorithms.

We propose a novel method for embedding robust forensic tracking watermarks to complement encryption in electronic music distribution applications. The watermark is embedded at the player during the AAC decoding process through modification of scale-factors in pre-defined frequency bands. It thereby modulates the short-time envelope of the decoded audio in the corresponding band. The resulting watermark is robust to various attacks such as re-compression and acoustic transmission. The method, due to its negligible computational overhead, can be used in resource constrained devices such as portable players.

Collusion attack is a malicious watermark removal attack in which the hacker has access to multiple copies of the same content with different watermarks and tries to remove the watermark using averaging. In the literature, several solutions to collusion attacks have been reported. The main stream solutions aim at designing watermark codes that are inherently resistant to collusion attacks. The other approaches propose signal processing based solutions that aim at modifying the watermarked signals in such a way that averaging multiple copies of the content leads to a significant degradation of the content quality. In this paper, we present signal processing based technique that may be deployed for deterring collusion attacks. We formulate the problem in the context of electronic music distribution where the content is generally available in the compressed domain. Thus, we first extend the collusion resistance principles to bit stream signals and secondly present experimental based analysis to estimate a bound on the maximum number of modified versions of a content that satisfy good perceptibility requirement on one hand and destructive averaging property on the other hand.

Successful watermarking algorithms have already been developed for various applications ranging from meta-data tagging to forensic tracking. Nevertheless, it is commendable to develop alternative watermarking techniques that provide a broader basis for meeting emerging services, usage models and security threats. To this end, we propose a new multiplicative watermarking technique for video, which is based on the principles of our successful MASK audio watermark. Audio-MASK has embedded the watermark by modulating the short-time envelope of the audio signal and performed detection using a simple envelope detector followed by a SPOMF (symmetrical phase-only matched filter). Video-MASK takes a similar approach and modulates the image luminance envelope. In addition, it incorporates a simple model to account for the luminance sensitivity of the HVS (human visual system). Preliminary tests show algorithms transparency and robustness to lossy compression.