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.
Unlike the P2P content distribution systems described in the above paragraph, the following P2P distribution systems fail to provide privacy to the end users. A fingerprint generation and embedding method was proposed by @cite_9 for complex P2P file sharing networks for copyright protection. In this system, wavelet transforms and principal component analysis (PCA) techniques are used for the fingerprint generation. The proposed framework provides a novel solution of legal content distribution, but it does not include collusion resistance and user privacy. Similarly, @cite_15 proposed a P2P system which provides secure distribution of copyright-protected music contents. In this framework, the RSA public-key cryptosystem is used to generate a unique digital fingerprint for every end user within the network. Then, the generated fingerprint is embedded into the music file such that the music provider can establish the identification of any end user performing an unauthorized re-distribution of the file. The proposed system provides a secure mean for distributing large-scale music contents over P2P networks, but it fails to offer privacy to the end users.
@cite_9 @cite_15
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Due to rapid advances in the network communications field in recent years, the distribution of large-scale music contents has become easier and more efficient than ever before. However, the unauthorized distribution of copyright-protected content has emerged as a major concern. Accordingly, this paper presents a content distribution framework with a DRM capability for P2P networks. The robustness of the content distribution is ensured by using a network coding approach based on the Lagrange polynomial interpolation method. When the downloading peer within the network receives sufficient coded pieces, it not only reconstructs the associated blocks using a finite field Gaussian elimination method, but also creates its own copies of the coded pieces within these blocks and shares these copies amongst the other peers in the network. As a result, the distribution overhead imposed on the music provider is substantially reduced and the number of coded pieces within the network is significantly increased, thereby overcoming the ''last piece problem'' inherent in existing P2P schemes. In the DRM module of the framework, the RSA public-key cryptosystem is used to generate a unique digital fingerprint for every user within the network. The fingerprint is embedded within the music file in a protected form such that the music provider can establish the identification of any user performing an unauthorized distribution of the file. The experimental results confirm that the proposed framework provides an efficient and secure means of distributing large-scale copyright-protected music contents with no discernible degradation in the audio quality. In order to utilize peer-to-peer (P2P) networks in legal content distribution to benefit the legal content providers, copyright protection needs to be enhanced. In this paper, a fingerprint generation and embedding method is proposed for complex P2P file sharing networks. In this method, wavelet and principal component analysis (PCA) techniques are used for fingerprint generation. First, the wavelet technique obtains a low-frequency representation of the test image (or source file, which is assumed to be one I frame of a video with a DVD quality) and PCA finds the features of the representation. Then, a set of fingerprint matrices can be created based on a proposed algorithm. Finally, each matrix combines with the low-frequency representative to become a unique fingerprinted matrix. The fingerprinted matrix is not only much smaller than the original image in size but also contains the most important information. Without this information, the quality of the reconstructed image will be very poor. Thus, the fingerprinted file is more suitable for distribution in P2P networks, because, in the distribution stage, the uniquely fingerprinted matrix will only be dispensed by the source host and leave the rest for P2P networks to handle. On the other hand, among other frames of the same video which are not decomposed, some will be embedded with sharable fingerprints. The relationship between unique fingerprint and sharable fingerprint and the purpose of using it will be discussed in the paper. Our result indicates that the proposed fingerprint has shown strong robustness against common attacks such as Gaussian noise, median filter, and lossy compression. We propose to establish a secure communication channel among devices based on similar audio patterns. Features from ambient audio are used to generate a shared cryptographic key between devices without exchanging information about the ambient audio itself or the features utilized for the key generation process. We explore a common audio-fingerprinting approach and account for the noise in the derived fingerprints by employing error correcting codes. This fuzzy-cryptography scheme enables the adaptation of a specific value for the tolerated noise among fingerprints based on environmental conditions by altering the parameters of the error correction and the length of the audio samples utilized. In this paper, we experimentally verify the feasibility of the protocol in four different realistic settings and a laboratory experiment. The case studies include an office setting, a scenario where an attacker is capable of reproducing parts of the audio context, a setting near a traffic loaded road, and a crowded canteen environment. We apply statistical tests to show that the entropy of fingerprints based on ambient audio is high. The proposed scheme constitutes a totally unobtrusive but cryptographically strong security mechanism based on contextual information. 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.