A. James Clark School of Engineering
Permanent URI for this communityhttp://hdl.handle.net/1903/1654
The collections in this community comprise faculty research works, as well as graduate theses and dissertations.
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Item Resiliency Assessment and Enhancement of Intrinsic Fingerprinting(2012) Chuang, Wei-Hong; Wu, Min; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Intrinsic fingerprinting is a class of digital forensic technology that can detect traces left in digital multimedia data in order to reveal data processing history and determine data integrity. Many existing intrinsic fingerprinting schemes have implicitly assumed favorable operating conditions whose validity may become uncertain in reality. In order to establish intrinsic fingerprinting as a credible approach to digital multimedia authentication, it is important to understand and enhance its resiliency under unfavorable scenarios. This dissertation addresses various resiliency aspects that can appear in a broad range of intrinsic fingerprints. The first aspect concerns intrinsic fingerprints that are designed to identify a particular component in the processing chain. Such fingerprints are potentially subject to changes due to input content variations and/or post-processing, and it is desirable to ensure their identifiability in such situations. Taking an image-based intrinsic fingerprinting technique for source camera model identification as a representative example, our investigations reveal that the fingerprints have a substantial dependency on image content. Such dependency limits the achievable identification accuracy, which is penalized by a mismatch between training and testing image content. To mitigate such a mismatch, we propose schemes to incorporate image content into training image selection and significantly improve the identification performance. We also consider the effect of post-processing against intrinsic fingerprinting, and study source camera identification based on imaging noise extracted from low-bit-rate compressed videos. While such compression reduces the fingerprint quality, we exploit different compression levels within the same video to achieve more efficient and accurate identification. The second aspect of resiliency addresses anti-forensics, namely, adversarial actions that intentionally manipulate intrinsic fingerprints. We investigate the cost-effectiveness of anti-forensic operations that counteract color interpolation identification. Our analysis pinpoints the inherent vulnerabilities of color interpolation identification, and motivates countermeasures and refined anti-forensic strategies. We also study the anti-forensics of an emerging space-time localization technique for digital recordings based on electrical network frequency analysis. Detection schemes against anti-forensic operations are devised under a mathematical framework. For both problems, game-theoretic approaches are employed to characterize the interplay between forensic analysts and adversaries and to derive optimal strategies. The third aspect regards the resilient and robust representation of intrinsic fingerprints for multiple forensic identification tasks. We propose to use the empirical frequency response as a generic type of intrinsic fingerprint that can facilitate the identification of various linear and shift-invariant (LSI) and non-LSI operations.Item Behavior Modeling and Forensics for Multimedia Social Networks(2009) Lin, Wan-Yi; Liu, K.J. Ray; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Within the past decades, the explosive combination of multimedia signal processing, communications and networking technologies has facilitated the sharing of digital multimedia data and enabled pervasive digital media distribution over all kinds of networks. People involved in the sharing and distribution of multimedia contents form \emph{multimedia social networks} in which users share and exchange multimedia content, as well as other resources. Users in a multimedia social network have different objectives and influence each other's decision and performance. It is of ample importance to understand how users interact with and respond to each other and analyze the impact of human factors on multimedia systems. This thesis illustrates various aspects of issues and problems in multimedia social networks via two case studies of human behavior in multimedia fingerprinting and peer-to-peer live streaming. Since media security and content protection is a major issue in current multimedia systems, this thesis first studies the user dynamics of multimedia fingerprinting social networks. We investigate the side information which improves the traitor-tracing performance and provide the optimal strategies for both users (fingerprint detector and the colluders) in the multimedia fingerprinting social network. Furthermore, before a collusion being successfully mounted, the colluders must be stimulated to cooperate with each other and all colluders have to agree on the attack strategy. Therefore, not all types of collusion are possible. We reduce the possible collusion set by analyzing the incentives and bargaining behavior among colluders. We show that the optimal strategies designed based on human behavior can provide more information to the fingerprint detector and effectively improve the collusion resistance. The second part of this thesis focuses on understanding modelling and analyzing user dynamics for users in various types of peer-to-peer live streaming social networks. We stimulate user cooperation by designing the optimal, cheat-proof, and attack-resistant strategies for peer-to-peer live streaming social networks over Internet as well as wireless networks. Also, as more and more smart-phone users subscribe to the live-streaming service, a reasonable market price has to be set to prevent the users from reselling the live video. We start from analyzing the equilibrium between the users who want to resell the video and the potential buyers to provide the optimal price for the content owner.Item QOS-DRIVEN SCHEDULING FOR MULTIMEDIA APPLICATIONS(IEEE, 2004-05) Hua, Shaoxiong; Qu, Gang;Multimedia applications have intrinsic quality of service (QoS) requirements that may not be captured by the simple traditional completion ratio model. We have proposed a new quantitative QoS metric based on task completion ratio while differentiating firm and soft deadlines and taking data dependency into consideration. Using the decoding of MPEG movies as an example, we have shown that the proposed QoS metric is much better than completion ratio in measuring the quality of presentation (QoP) of the movies. Based on the new QoS metric, we present a set of new online algorithms that outperform popular scheduling algorithms (such as EDF, FCFS, and LETF) and enhance QoP significantly, particularly when the system is overloaded. All the proposed online algorithms have low computation overhead and can be easily integrated into real-time operating systems to improve multimedia embedded system’s performance and/or to save system resources.