Information-Theoretic Secure Outsourced Computation in Distributed Systems

Secure multi-party computation (secure MPC) has been established as the de facto paradigm for protecting privacy in distributed computation. One of the earliest secure MPC primitives is the Shamir\u27s secret sharing (SSS) scheme. SSS has many advantages over other popular secure MPC primitives like garbled circuits (GC) -- it provides information-theoretic security guarantee, requires no complex long-integer operations, and often leads to more efficient protocols. Nonetheless, SSS receives less attention in the signal processing community because SSS requires a larger number of honest participants, making it prone to collusion attacks. In this dissertation, I propose an agent-based computing framework using SSS to protect privacy in distributed signal processing. There are three main contributions to this dissertation. First, the proposed computing framework is shown to be significantly more efficient than GC. Second, a novel game-theoretical framework is proposed to analyze different types of collusion attacks. Third, using the proposed game-theoretical framework, specific mechanism designs are developed to deter collusion attacks in a fully distributed manner. Specifically, for a collusion attack with known detectors, I analyze it as games between secret owners and show that the attack can be effectively deterred by an explicit retaliation mechanism. For a general attack without detectors, I expand the scope of the game to include the computing agents and provide deterrence through deceptive collusion requests. The correctness and privacy of the protocols are proved under a covert adversarial model. Our experimental results demonstrate the efficiency of SSS-based protocols and the validity of our mechanism design

Algorithms and Architectures for Secure Embedded Multimedia Systems

Embedded multimedia systems provide real-time video support for applications in entertainment (mobile phones, internet video websites), defense (video-surveillance and tracking) and public-domain (tele-medicine, remote and distant learning, traffic monitoring and management). With the widespread deployment of such real-time embedded systems, there has been an increasing concern over the security and authentication of concerned multimedia data. While several (software) algorithms and hardware architectures have been proposed in the research literature to support multimedia security, these fail to address embedded applications whose performance specifications have tighter constraints on computational power and available hardware resources. The goals of this dissertation research are two fold: 1. To develop novel algorithms for joint video compression and encryption. The proposed algorithms reduce the computational requirements of multimedia encryption algorithms. We propose an approach that uses the compression parameters instead of compressed bitstream for video encryption. 2. Hardware acceleration of proposed algorithms over reconfigurable computing platforms such as FPGA and over VLSI circuits. We use signal processing knowledge to make the algorithms suitable for hardware optimizations and try to reduce the critical path of circuits using hardware-specific optimizations. The proposed algorithms ensures a considerable level of security for low-power embedded systems such as portable video players and surveillance cameras. These schemes have zero or little compression losses and preserve the desired properties of compressed bitstream in encrypted bitstream to ensure secure and scalable transmission of videos over heterogeneous networks. They also support indexing, search and retrieval in secure multimedia digital libraries. This property is crucial not only for police and armed forces to retrieve information about a suspect from a large video database of surveillance feeds, but extremely helpful for data centers (such as those used by youtube, aol and metacafe) in reducing the computation cost in search and retrieval of desired videos