This dissertation presents a novel problem inspired by the characteristics of sensor networks. The basic setup through-out the dissertation is that a set of sensor nodes encipher their data without collaboration and without any prior shared secret materials. The challenge is dealt by an eavesdropper who intercepts a subset of the enciphered data and wishes to gain knowledge of the uncoded data. This problem is challenging and novel given that the eavesdropper is assumed to know everything, including secret cryptographic keys used by both the encoders and decoders. We study the above problem using information theoretic models as a necessary first step towards an understanding of the characteristics of this system problem. This dissertation contains four parts. The first part deals with noiseless channels, and the goal is for sensor nodes to both source code and encipher their data. We derive inner and outer regions of the capacity region (i.e the set of all source coding and equivocation rates) for this problem under general distortion constraints. The main conclusion in this part is that unconditional secrecy is unachievable unless the distortion is maximal, rendering the data useless. In the second part we thus provide a practical coding scheme based on distributed source coding using syndromes (DISCUS) that provides secrecy beyond the equivocation measure, i.e. secrecy on each symbol in the message. The third part deals with discrete memoryless channels, and the goal is for sensor nodes to both channel code and encipher their data. We derive inner and outer regions to the secrecy capacity region, i.e. the set of all channel coding rates that achieve (weak) unconditional secrecy. The main conclusion in this part is that interference allows (weak) unconditional secrecy to be achieved in contrast with the first part of this dissertation. The fourth part deals with wireless channels with fading and additive Gaussian noise. We derive a general outer region and an inner region based on an equal SNR assumption, and show that the two are partially tight when the maximum available user powers are admissible.

Thesis (M.S.)--Worcester Polytechnic Institute. / Keywords: binary field arithmetic, gcd, hardware architectures, polynomial arithmetic, cryptosystem, hyperelliptic curves. Includes bibliographical references (leaves 82-87).

Thesis (M.S.)--Florida State University, 2003. / Advisor: Dr. Yvo Desmedt, Florida State University, College of Arts and Sciences, Department of Computer Science. Title and description from dissertation home page (viewed Sept. 24, 2003). Includes bibliographical references.

We develop the dual system encryption methodology to provide fully secure functional encryption systems. We introduce new proof techniques and explore their applications, resulting in systems that advance the state of the art in terms of functionality, security, and efficiency. Our approach constructs versatile tools for adapting the dual system encryption methodology to new functionalities and efficiency goals. As particular demonstrations of our techniques, we obtain fully secure ciphertext-policy attribute-based encryption systems in the single authority and decentralized settings. Our work has provided the first fully secure attribute-based encryption schemes as well as the first decentralized schemes achieving desired levels of flexibility. / text

Secure Multi-party Computation (SMC) is one significant research area in information security. In SMC, multiple parties jointly work on some function and no parties take the risk of revealing their private data. Since A.C. Yao first proposed this problem in 1982, there have been a lot of researchers working on different versions of SMC. In this thesis, we address three different researches in this setting, including the Privacy-Preserving Cooperative Scientific Computation, Privacy Preserving Data Mining (PPDM), and PPDM in cloud environment. In Privacy-Preserving Cooperative Scientific Computation, we propose a solution to the Privacy Preserving Weighted Average Problem (PPWAP) under the hybrid security model, which guarantees the malicious parties will not get the correct final result if they behalf maliciously. Later, the extended version of our scheme is shown as a highly efficient and secure PPWAP solution under the malicious model, a stronger security model requiring more resource. Privacy reserving data mining is one important branch of SMC, where all participants want to get the same and correct mining result from collaborated data mining without any threat of disclosing their private data. In another word, each party refuses to review its individual private database while carrying out collaborated data mining. We propose a PPDM solution of building up a decision tree from a hybrid distributed database, which is a quite common situation in real life but has not been solved before. Previous research works only focus on horizontally or vertically distributed database. With the great development of cloud computing, it provides a much more flexible and efficient platform for Internet service providers and users. However, the privacy issues of cloud service has become the bottleneck of its further development, and this problem also draw a lot of researchers' attention in recent decade. In this thesis, we propose the first solution to cloud-based PPDM. The cloud server carries out data mining on encrypted databases, and our solution can guarantee the privacy of each client. This scheme can protect client from malicious users. With aid of a hardware box, our design can also protect clients from untrusted cloud server. Another novel feature of this solution is that it works even when the databases from different parties share overlapped parts. Furthermore, with the help of homomorphic encryption and black box, our scheme can carry out the calculation on the overlapped data. This kind of problem has never been resolved by previous works as far as we know. / published_or_final_version / Computer Science / Doctoral / Doctor of Philosophy

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This report presents the RSA encryption and decryption schemes and discusses several methods for expediting the computations required, specifically the modular exponentiation operation that is required for RSA. A hardware implementation of the CIOS (Coarsely Integrated Operand Scanning) algorithm for modular multiplication is attempted on a XILINX Spartan3 FPGA in the TLL-5000 development platform used at the University of Texas at Austin. The development of the hardware is discussed in detail and some Verilog source code is provided for an implementation of modular multiplication. Some source code is also provided for an RSA executable to run on the TLL-6219 ARM-based development platform, to be used to generate test vectors. / text

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