Biblio

Most anti-collusion audio fingerprinting schemes are aiming at finding colluders from the illegal redistributed audio copies. However, the loss caused by the redistributed versions is inevitable. In this letter, a novel fingerprinting scheme is proposed to eliminate the motivation of collusion attack. The audio signal is transformed to the frequency domain by the Fourier transform, and the coefficients in frequency domain are reversed in different degrees according to the fingerprint sequence. Different from other fingerprinting schemes, the coefficients of the host media are excessively modified by the proposed method in order to reduce the quality of the colluded version significantly, but the imperceptibility is well preserved. Experiments show that the colluded audio cannot be reused because of the poor quality. In addition, the proposed method can also resist other common attacks. Various kinds of copyright risks and losses caused by the illegal redistribution are effectively avoided, which is significant for protecting the copyright of audio.

In this paper, we address the problem of demand response of electrical vehicles (EVs) during microgrid outages in the smart grid through the application of Vehicle-to-Grid (V2G) technology. Particularly, we present a novel privacy-preserving double auction scheme. In our auction market, the MicroGrid Center Controller (MGCC) acts as the auctioneer, solving the social welfare maximization problem of matching buyers to sellers, and the cloud is used as a broker between bidders and the auctioneer, protecting privacy through homomorphic encryption. Theoretical analysis is conducted to validate our auction scheme in satisfying the intended economic and privacy properties (e.g., strategy-proofness and k-anonymity). We also evaluate the performance of the proposed scheme to confirm its practical effectiveness.