# Blockchain and Smart Contracts for Digital Copyright Protection
## 2 Related Work  
The first buyer-seller watermarking protocols exploit WCAs and public-key infrastructures (PKIs) based on \"privacy-homomorphic\" encryption schemes [18]. WCAs can thus encrypt watermarks with the buyers' public keys and then directly embed them into the contents encrypted by sellers with the same buyers' public keys. Buyers can decrypt the requested contents by applying their private keys and thus obtain their copies protected by personalized watermarks, which are unknown to sellers [3]. The first protocols based on WCAs and privacy-homomorphic encryption schemes are characterized by several problems, the most important of which are the \"unbinding problem\" [3] and the collusion problems caused by malicious WCAs [2]. Their solution has led to protocols that do not employ WCAs [19] or that use off-line WCAs [4; 20]. The different approach based on the \"client-side embedding\" protection scheme carries out a joint watermark insertion between seller and buyer by employing symmetric ciphers and \"partial encryption\" [21]. The seller adds a noise sequence to a set of selected transform coefficients of content in order to distort them. The buyer then employs a specific decryption key received by the seller to partially remove the added noise sequence and thus leave only the watermark. Such a scheme is characterized by a double advantage: it avoids WCAs and is scalable since it distributes the computing load generated by watermark insertion equally between buyer and seller. However, it is still affected by the \"customer's rights problem\" and collusion problems, which are caused by the fact that sellers have access to the decryption keys needed to partially remove the noise sequences so as to leave client-specific watermarks in the contents. The promising scheme described in [21] is improved by the protocols proposed in [7; 8], which mainly focus on the process by which fingerprints are left in the contents by decryption keys. In particular, the protocol in [7] generates decryption keys that can leave in the contents personalized binary fingerprints that are unknown to sellers. The protocol in [8], in addition, implements collusion resistance facilities within the scheme described in [7] by generating two types of fingerprints: near orthogonal independent Gaussian fingerprints and Tardos code-based fingerprints [22]. The results are represented by protocols characterized by scalability, collusion resistance, and absence of WCAs. The protocols, however, have a significant drawback: they require buyers to remove noise sequences from the purchased contents. Therefore, they force buyers to carry out complex security actions [1]. The protocols described in [5; 6] represent an example of provably secure collusion-resistant interaction schemes. They do not use WCAs. However, they make the participation of buyers in the protocols rather difficult since buyers have to take charge of interactive zero-knowledge proofs, encryptions, group signatures, and watermark generations. Such a peculiarity makes these protocols unsuitable for the current Internet. The buyer-seller watermarking protocols also inspire systems, known as DRM (Digital Rights Management) systems, specifically designed to protect the copyright of digital content on the Internet. DRMs are more complex than watermarking protocols since they can exploit advanced facilities, such as file-sharing peer-to-peer networks and blockchain technology, to implement specific services focused on the managed digital content and their modifications or copyright transfers [23; 24]. DRMChain is a DRM system based on blockchain [25]. It uses the InterPlanetary File System (IPFS) to store protected content and supports content protection and traceability of copyright violations. It also provides specific security services, such as privacy-preserving user authentication, content encryption and watermarking, and a system that exploits conditional identity management to trace license violations.