Use Of Chinese Remainder Theorem Research Articles

Identification of proteins by the use of Chinese remainder theorem codes over finite commutative rings

Identification of proteins by the use of Chinese remainder theorem codes over finite commutative rings

LIFE: a lightweight and flexible key management scheme for securely and pervasively file editing in mobile cloud computing

As cloud servers provide on-demand and on-line storage services, it is possible for mobile users to work any-time and any-where by using hand-held smart devices. Mobile users upload working documents into cloud servers and other users can cooperatively read and edit them. Cloud servers are usually assumed untrustworthy, thus uploaded files have to be encrypted for confidentiality. It thus arises a security problem for key management, e.g., key distributing, updating and revoking. In mobile cloud computing context, key management must be lightweight in terms of power consumption and flexible, because devices have energy constraints, as well as users and files dynamically changes. In this paper, we propose a lightweight and flexible scheme, called LIFE, for key management in mobile cloud computing without relying on any trusted third party. LIFE provides a uniform key management framework for both pairwise keys and group keys by making use of Chinese remainder theorem. LIFE can implicitly update or revoke group keys, which extra protects the privacy of group membership. In addition, LIFE can also guarantee forward and backward secrecy. The security and performance of LIFE are analysed extensively, which justifies its applicability.

Sparse Sensing With Co-Prime Samplers and Arrays

This paper considers the sampling of temporal or spatial wide sense stationary (WSS) signals using a co-prime pair of sparse samplers. Several properties and applications of co-prime samplers are developed. First, for uniform spatial sampling with M and N sensors where M and N are co-prime with appropriate interelement spacings, the difference co-array has O(MN) freedoms which can be exploited in beamforming and in direction of arrival estimation. An M -point DFT filter bank and an N-point DFT filter bank can be used at the outputs of the two sensor arrays and their outputs combined in such a way that there are effectively MN bands (i.e., MN narrow beams with beamwidths proportional to 1/MN), a result following from co-primality. The ideas are applicable to both active and passive sensing, though the details and tradeoffs are different. Time domain sparse co-prime samplers also generate a time domain co-array with O(MN) freedoms, which can be used to estimate the autocorrelation at much finer lags than the sample spacings. This allows estimation of power spectrum of an arbitrary signal with a frequency resolution proportional to 2π/(MNT) even though the pairs of sampled sequences xc(NTn) and xc(MTn) in the time domain can be arbitrarily sparse - in fact from the sparse set of samples xc(NTn) and xc(MTn) one can estimate O(MN) frequencies in the range |ω| <; π/T. It will be shown that the co-array based method for estimating sinusoids in noise offers many advantages over methods based on the use of Chinese remainder theorem and its extensions. Examples are presented throughout to illustrate the various concepts.