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Security, Trust and Risk in Multimedia Social Networks

With the rapid development of network socialization, multimedia social networks (MSNs) have increasingly emerged. These MSNs offer network tools, services and applications for multimedia content (e.g. electronic book, digital image, audio and video) that can be shared among users in the same group or between different groups within social networks. Many MSNs, such as video Youtube and audio SongTaste sharing networks, are increasingly widely used. However, easy digital content reproduction, convenient distribution and sharing of such content facilitated by open MSNs environments have enabled people to share and distribute valuable copyrighted digital content within social networks. Copyright infringement behaviour, such as illicit copying, malicious distribution, unauthorized usage and free sharing of copyright-protected digital content, will also become a much more common phenomenon. Some research frontiers on media content security in social networks applications have been in progress, including enhanced security mechanisms, methods and algorithms, trust assessment and risk management in social network applications, as well as social factors and soft computing in social media distributions. The special issue attempts to bring together researchers, content industry engineers and administrators resorting to the state-of-the-art technologies and ideas to protect valuable media content and services against security attacks and piracy exposure in the emerging social networks. In the first section of the special issue, there are five original articles in the field of MSNs security, privacy and forensics. First, Patsakis et al. made a survey on the most significant security and privacy issues related to the exposure of multimedia content in online social network (OSN), and then discussed possible countermeasures and methods. In the second paper, Hui Zhu et al. attempted to explore privacy setting policies in OSN, and proposed a general stochastic model called diffusion model based on privacy setting with multiple diffusion mechanisms for OSN services. By a series of experimental simulations and analysis, the paper shows that the novel model can precisely describe the diffusion process. Next, Hong Zhu et al. highlighted an independent -Diversity principle, based on which a privacypreserving data publication model is presented to prevent individual sensitive information disclosure in the corruption attack. The proposed model could prevent attacks from attackers who have known data publishing algorithms and have the corruption abilities. Followed by media content security and forensics in the section, Weitao Song et al. paid more attention to the type-flaw attacks detection and security protocol formalism. They introduced a multi-branch tag tree to establish a three-level model for detecting typeflaw attacks on security protocols. In the final fifth paper, considering an effective forensic analysis on digital images, the authors, Bin Yang et al., represented a novel shadow-based method, by which the fake shadow of the composites can be detected. The special issue’s second section focuses on MSNs trust and reputation issues, and also includes the following five selected papers. Ayesha Kanwal et al. have performed indepth analyses of the existing trust models in the cloud environment, and presented panoramic taxonomies covering the state-of-the-art features. Furthermore, they have applied the proposed taxonomies as assessment criteria for the analysis of various trust models in the cloud domain. In addition, the emerging MSNs services and tools, in recent years, have generally facilitated convenient platforms for users to