Abstract The use of peer-to-peer (P2P) networks for multimedia distribution has spread out globally in recent years. The mass popularity is primarily driven by cost-effective distribution of content, also giving rise to piracy. An end user (buyer peer) of a P2P content distribution system does not want to reveal his her identity during a transaction with a content owner (merchant), whereas the merchant does not want the buyer to further distribute the content illegally. To date, different P2P distribution systems have been proposed that provide copyright and privacy protection at a cost of high computational burden at the merchant׳s and or at the buyer׳s end and thus, making these systems impractical. In this paper, we propose PSUM, a P2P content distribution system which allows efficient distribution of large-sized multimedia content while preserving the security and privacy of merchants and buyers. The security of PSUM is ensured by using an asymmetric fingerprinting protocol based on collusion-resistant codes. In addition, PSUM enables buyers to obtain digital contents anonymously, but this anonymity can be revoked as soon as he she is found guilty of copyright violation. The paper presents a thorough performance analysis of PSUM, through different experiments and simulations, and also analyzes several security compromising attacks and countermeasures.
However, merging collusion-resistant fingerprinting schemes and secure embedding is a difficult task. Early secure watermark embedding schemes assumed that the use of anti-collusion codes make the schemes resistant against collusion attacks without giving any proof-of-concept. Recently, two asymmetric fingerprinting schemes based on @math -secure codes were proposed. @cite_6 proposed a solution that allows a buyer to pick up fingerprint bits from a list controlled by the merchant, in such a way that he she does not know the chosen elements. However, the proposed scheme requires heavy computation due to use of an oblivious transfer protocol. Also, the number of communication rounds between a buyer and a seller is impracticable as it has a linear relation with the length of the code. @cite_10 proposed an asymmetric fingerprinting scheme based on the B-S code with constant communication round but at a cost of a longer codeword.
@cite_10 @cite_6
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A buyer seller watermarking protocol is intended to ensure copyright protection, privacy and security for both the buyer and seller simultaneously in an e-commerce application. A traitor should not be able to deny his responsibility of a copyright violation caused by him in such protocols. This feature is identified as non-repudiation in the literature. An efficient approach taken is through secure embedding of watermarks in an encrypted domain by using dither modulation and homomorphic encryption. To support non-repudiation along with collusion resistance, one needs an asymmetric collusion resistant fingerprinting code that is compatible with the watermarking technique. The design of such codes has not yet studied thoroughly with an exception of a recent work by Charpentier et. al. in [4]. In this paper, we propose an asymmetric binary fingerprinting code based on Boneh-Shaw code. When applied to the secure embedding of watermarks, we show that our code outperforms the code introduced by [4]: (i) we achieve constant communication round, (ii) we do not require any oblivious transfer protocol and (iii) we do not require any public Write Once Read Many (WORM) directory. We study a fingerprinting game in which the number of colluders and the collusion channel are unknown. The encoder embeds fingerprints into a host sequence and provides the decoder with the capability to trace back pirated copies to the colluders. Fingerprinting capacity has recently been derived as the limit value of a sequence of maximin games with mutual information as their payoff functions. However, these games generally do not admit saddle-point solutions and are very hard to solve numerically. Here under the so-called Boneh-Shaw marking assumption, we reformulate the capacity as the value of a single two-person zero-sum game, and show that it is achieved by a saddle-point solution. If the maximal coalition size is k and the fingerprinting alphabet is binary, we show that capacity decays quadratically with k. Furthermore, we prove rigorously that the asymptotic capacity is 1 (k221n2) and we confirm our earlier conjecture that Tardos' choice of the arcsine distribution asymptotically maximizes the mutual information payoff function while the interleaving attack minimizes it. Along with the asymptotics, numerical solutions to the game for small k are also presented. Asymmetric fingerprinting protocols are designed to prevent an untrustworthy Provider incriminating an innocent Buyer. These protocols enable the Buyer to generate their own fingerprint by themself, and ensure that the Provider never has access to the Buyer's copy of the Work. Until recently, such protocols were not practical because the collusion-resistant codes they rely on were too long. However, the advent of Tardos codes means that the probabilistic collusion-resistant codes are now sufficiently short that asymmetric fingerprint codes should, in theory, be practical. Unfortunately, previous asymmetric fingerprinting protocols cannot be directly applied to Tardos codes, because generation of the Tardos codes depends on a secret vector that is only known to the Provider. This knowledge allows an untrustworthy Provider to attack traditional asymmetric fingerprinting protocols. We describe this attack, and then propose a new asymmetric fingerprinting protocol, specifically designed for Tardos codes. In this paper, we present a technique for fingerprinting relational data by extending 's watermarking scheme. The primary new capability provided by our scheme is that, under reasonable assumptions, it can embed and detect arbitrary bit-string marks in relations. This capability, which is not provided by prior techniques, permits our scheme to be used as a fingerprinting scheme. We then present quantitative models of the robustness properties of our scheme. These models demonstrate that fingerprints embedded by our scheme are detectable and robust against a wide variety of attacks including collusion attacks.