Data security has always been a major concern and a huge challenge for governments and individuals throughout the world since early times. Recent advances in technology, such as the introduction of cloud computing, make it even a bigger challenge to keep data secure. In parallel, high throughput mobile devices such as smartphones and tablets are designed to support these new technologies. The high throughput requires power-efficient designs to maintain the battery-life. In this paper, we propose a novel Joint Security and Advanced Low Density Parity Check (LDPC) Coding (JSALC) method. The JSALC is composed of two parts: the Joint Security and Advanced LDPC-based Encryption (JSALE) and the dual-step Secure LDPC code for Channel Coding (SLCC). The JSALE is obtained by interlacing Advanced Encryption System (AES)-like rounds and Quasi-Cyclic (QC)-LDPC rows into a single primitive. Both the JSALE code and the SLCC code share the same base quasi-cyclic parity check matrix (PCM) which retains the power efficiency compared to conventional systems. We show that the overall JSALC Frame-Error-Rate (FER) performance outperforms other cryptcoding methods by over 1.5 dB while maintaining the AES-128 security level. Moreover, the JSALC enables error resilience and has higher diffusion than AES-128.

Summary form only given. Ciphers encrypted with the same key are called ciphers in depth. A depth attack is a form of cryptanalysis that takes advantage of finding ciphers in depth and could break a cryptosystem without even knowing the encryption algorithm. The first task in a depth attack is to cluster ciphers according to their common keys and is called depth detection. Then, one may want to know the file type of the underlying message of each cipher. In this research, depth detection is accomplished for stream ciphers with a hit rate of 99.5%. Next, ciphers in depth are further classified according to the file types of their underlying messages with an accuracy of over 90%. One important goal of this research is not to use the structure and key words of any specific file types as this allows the result to be applied to general file types. Also, the features extracted from the test samples for classification are simple ones, leaving room for improving the performance by adopting more complicated features.

A simple direct sequence-code division multiple access receiver that combines adaptive beamforming with parallel interference cancellation in a multipath fading channel is proposed and analyzed. A fast adaptation, conjugate gradient algorithm is used to find the optimum beamformer weights. By beamforming, the desired user's signal is enhanced and the cochannel interference from other directions is reduced. For in-beam multiple access interference reduction, a parallel interference canceller is used in each RAKE finger. In the demodulation process, we propose a new demodulation method in which the incoming signal is correlated with the effecting spreading code rather than the physical spreading code called the effective matched filter. A new combining method called equivalent maximal ratio combining is also proposed and analyzed. The average uncoded bit error rate as a function of the average antenna signal-to-noise ratio and the number of receiving antennas is examined in a frequency selective Rayleigh fading channel for all proposed receiver structures. Both simulation and analysis show an increase in system capacity as a function of the number of antennas and the number of interferers canceled per finger.

A simple DS-CDMA receiver that combines adaptive beamforming together with parallel interference cancellation in a multipath fading channel is presented. A fast adaptation, a conjugate gradient (CG) algorithm is used to find the optimum beamformer weights. By CG beamforming, the desired user's signal is enhanced and the cochannel interference from other directions is reduced. For in-beam multiple access interference reduction, a parallel interference canceller is used in each RAKE finger. The average uncoded bit error rate (BER) as a function of the average antenna signal-to-noise ratio (SNR) and the number of receiving antennas is examined in a frequency selective Rayleigh fading channel. Simulation results show an increase in system capacity as a function of the number of antennas and the number of interferers canceled per finger.

Given a set of training samples, the commonly used approach to determine a universal model is accomplished by averaging the statistics over all training samples. It is suggested to use average divergence as a measurement for the effectiveness of a universal model and a minimax universal model that minimizes the maximum average divergence among all training samples is proposed. Efficient searching algorithms are developed and experimental results are presented.>

The encoding schemes utilize the first- and second-order Markov models to describe the source structure. Two coding techniques, Huffman encoding and arithmetic encoding, are used to achieve a high coding efficiency. Universal code tables which match the statistics of contour line drawings obtained from 64 contour maps are presented and can be applied to encode all contour line drawings with chain code representations. Experiments have shown about a 50% improvement on the code amount over the conventional chain encoding scheme with arithmetic coding schemes, and also have shown a compression rate comparable to that obtained by T. Kaneko and M. Okudaira (1985) with Huffman coding schemes, while this implementation is substantially simpler.>

A method for classifying closed planar shapes is presented. A shape is preprocessed and represented by several ordered sequences of vertices which are obtained by using an optimal polygon approximation algorithm with different approximation error criteria. A dynamic alignment algorithm is used to compute a similarity index between two sets of shape descriptors. The shape recognition process is hierarchical and invariant to rotation, translation and scaling. Classification experiments using noisy contours and objects have been performed with satisfactory results.>

Several compression techniques need to be integrated for the achievement of effective low-bit-rate coding of moving images. Image entropy codes are used in conjunction with either predictive or transform coding methods. In this paper, we investigate the possible advantages of using arithmetric codes for image entropy coding. A theory of source modeling is established based on the concept of source parsing and conditioning trees. The key information-theoretic properties of conditioning trees are discussed along with algorithms for the construction of optimal and suboptimal trees. The theory and algorithms are then applied to evaluating the performance of entropy coding for the discrete cosine transform coefficients of digital images from the "Walter Cronkite" video sequence. The performance of arithmetic codes is compared to that of a traditional combination of run length and Huffman codes. The results indicate that binary arithmetic codes outperform run length codes by a factor of 55 percent for low-rate coding of the zero-valued coefficients. Hexadecimal arithmetic codes provide a coding rate improvement as high as 28 percent over truncated Huffman codes for the nonzero coefficients. The complexity of these arithmetic codes is suitable for practical implementation.

Two-dimensional digital curves are often uniformly approximated by polygons or piecewise linear curves. Several algorithms have been proposed in the literature to find such curves. We present an algorithm that finds a piecewise linear curve with the minimal number of segments required to approximate a curve within a uniform error with fixed initial and final points. We compare our optimal algorithm to several suboptimal algorithms with respect to the number of linear segments required in the approximation and the execution time of the algorithm.

Delta modulation communication systems are a popular and effective approach for transmitting analog signals over a binary channel. The performance of a discrete-time linear and leaky delta modulator is compared to the performance of the optimal delta modulator for a firstorder Gauss-Markov source.

With digital implementations of the Viterbi decoding algorithm for convolutional codes, soft quantization is preferred over hard quantization because it generally yields superior performance. Since the decoder needs to know the signal energy and channel noise variance with soft quantization, inaccurate information can result in a mismatch between the channel and decoder. Bounds which are tight for high signal-to-noise ratios are obtained on the bit error probability using the generating function approach. Automatic gain control level inaccuracies, imperfect carrier phase, symbol timing synchronization error, and path metric digitization are discussed in the context of a mismatch between the channel and decoder.

It is shown for a class of symbol-by-symbol encoding schemes, including delta modulation and some adaptive quantization schemes, that the joint input-state-output sequence is asymptotically mean stationary if the input sequence is stationary. Asymptotic mean stationarity is also obtained for the sequence of outputs produced by a general kind of variable-length to variable-length scheme, as well as for some sequences of waiting times arising in queueing theory.

It is shown that a convolutional code can be decoded with a sliding-block decoder, a time-invariant nonlinear digital filter with finite memory and delay. If the memory and delay are small, then the sliding-block decoder can be implemented as a table lookup procedure in ROM, resulting in a low cost, high speed, and high reliability decoder.

In a trellis encoding communication system the decoder is a time-invariant nonlinear filter with finite memory (sliding-block code), and the encoder is a trellis search algorithm matched to the decoder. A coding theorem is established for a trellis encoding of a stationary and ergodic source over a discrete memoryless noisy channel which shows that such communication systems can perform arbitrarily close to the source distortion-rate function evaluated at the channel capacity.

For a discreten-valued random variableX, Leung-Yan-Cheung and Cover recently showed that the minimal expected length of one-to-one (not necessarily uniquely decodable) codes satisfiesH(X)+ 1 >L_{l:l} \geq H(X) - \log( \sum^{n}_{i-1}2/(i+2)). A simple and direct proof of their lower bound is given which does not use the method of Lagrange multipliers.

For simple substitution ciphers an exact expression and bounds are derived for the message equivocation in terms of the key equivocation. It is established that the message equivocation approaches the key equivocation exponentially fast for discrete memoryless sources. It is observed that the exponential behavior of the message equivocation is not determined by redundancy in the message source but by either the symbol probabilities which are closest in a certain sense or the sum of the two smallest symbol probabilities.

Berger's proof of the abstract-alphabet block source coding with a fidelity criterion theorem is shown to be incomplete due to an error by Perez in extending the Shannon-McMillan Theorem to general stationary sources. A result of Pinsker is used to simply and directly complete the proof of the theorem.