Behavior modeling and forensics for multimedia social networks

Zhao

Liu

2011

IEEE Trans. Multimedia

Self Cite

Abstract-Multimedia social network is a network infrastructure in which the social network users share multimedia contents with all different purposes. Analyzing user behavior in multimedia social networks helps design more secured and efficient multimedia and networking systems. Multimedia fingerprinting protects multimedia from illegal alterations and multiuser collusion is a cost-effective attack. The colluder social network is naturally formed during multiuser collusion with which colluders gain reward by redistributing the colluded multimedia contents. Since the colluders have conflicting interest, the maximal-payoff collusion for one colluder may not be the maximal-payoff collusion for others. Hence, before a collusion being successful, the colluders must bargain with each other to reach agreements. We first model the bargaining behavior among colluders as a noncooperative game and study four different bargaining solutions of this game. Moreover, the market value of the redistributed multimedia content is often time-sensitive. The earlier the colluded copy being released, the more the people are willing to pay for it. Thus, the colluders have to reach agreements on how to distribute reward and risk among themselves as soon as possible. This paper further incorporates this time-sensitiveness of the colluders' reward and studies the time-sensitive bargaining equilibrium. The study in this paper reveals the strategies that are optimal for the colluders; thus, all the colluders have no inventive to disagree. Such understanding reduces the possible types of collusion into a small finite set.

Section: B Scalable Multimedia Fingerprinting and Collusion Attackmentioning

confidence: 99%

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confidence: 99%

See 1 more Smart Citation

Game-theoretic strategies and equilibriums in multimedia fingerprinting social networks

Zhao

Liu

2011

IEEE Trans. Multimedia

Self Cite

“…The service provider, data-plan subscribers and the secondary buyers who are interested in the video data interact with each other and in uence each other's decisions and performance. In such a scenario, game theory is a mathematical tool to model and analyzes the strategic interactions among rational decision makers [3]. In our previous work [4], the equilibrium price of the video stream in the redistribution network was derived.…”

Section: Introductionmentioning

confidence: 99%

Pricing game and evolution dynamics for mobile video streaming

2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Liu

2011

The recent developments of smart mobile phones and 3G networks enable users to enjoy video programs by subscribing to data plans. Due to phone-to-phone communication technologies and ubiquity of mobile phones, data-plan subscribers are able to redistribute the video content to non-subscribers. Such a redistribution mechanism is a potential competitor for the mobile service provider and is very dif cult to trace given users' high mobility. The service provider has to set a reasonable price for the data plan to prevent such unauthorized re-distribution behavior to protect or maximize his/her own pro t. In this paper, we investigate the evolutionarily stable ratio of mobile users who decide to subscribe to the data plan. Such an analysis can help the service provider preserve his/her pro t under the threat of the redistribution networks and can improve the quality of service for end users.

“…Recently, it draws great attention in cognitive networking [24], multimedia social networking [25], and is being applied to many multimedia signal processing problems such as video coding [26] and multimedia communications [27]. In P2P networks, peers make intelligent decisions on their strategies of requesting and forwarding packets based on their needs and other peers' actions.…”

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confidence: 99%

Cooperative peer-to-peer streaming: An evolutionary game-theoretic approach

Chen

Wang

IEEE Trans. Circuits Syst. Video Technol.

et al. 2010

Abstract-While peer-to-peer (P2P) video streaming systems have achieved promising results, they introduce a large number of unnecessary traverse links, which consequently leads to substantial network inefficiency. To address this problem and achieve better streaming performance, we propose to enable cooperation among "group peers," which are geographically neighboring peers with large intra-group upload and download bandwidths. Considering the peers' selfish nature, we formulate the cooperative streaming problem as an evolutionary game and derive, for every peer, the evolutionarily stable strategy (ESS), which is the stable Nash equilibrium and no one will deviate from. Moreover, we propose a simple and distributed learning algorithm for the peers to converge to the ESSs. With the proposed algorithm, each peer decides whether to be an agent who downloads data from the peers outside the group or a freerider who downloads data from the agents by simply tossing a coin, where the probability of being a head for the coin is learned from the peer's own past payoff history. Simulation results show that the strategy of a peer converges to the ESS. Compared to the traditional non-cooperative P2P schemes, the proposed cooperative scheme achieves much better performance in terms of social welfare, probability of real-time streaming, and video quality (source rate).