We study fast inversion of the Paillier encryption function. Especially, we focus only on key generation, and do not modify the Paillier encryption function. We propose three key generation algorithms based on the speeding-up techniques for the RSA encryption function. By using our algorithms, the size of the private CRT exponent is half of that of Paillier-CRT. The first algorithm employs the extended Euclidean algorithm. The second algorithm employs factoring algorithms, and can construct the private CRT exponent with low Hamming weight. The third algorithm is a variant of the second one, and has some advantage such as compression of the private CRT exponent and no requirement for factoring algorithms. We also propose the settings of the parameters for these algorithms and analyze the security of the Paillier encryption function by these algorithms against known attacks. Finally, we give experimental results of our algorithms.

This paper describes non-reference objective quality evaluation for noise-reduced speech. First, a subjective test is conducted in accordance with ITU-T Rec. P.835 to obtain the speech quality, the noise quality, and the overall quality of noise-reduced speech. Based on the results, we then propose an overall quality estimation model. The unique point of the proposed model is that the estimation of the overall quality is done only using the previously estimated speech quality and noise quality, in contrast to conventional models, which utilize the acoustical features extracted. Finally, we propose a non-reference objective quality evaluation method using the proposed model. The results of an experiment with different noise reduction algorithms and noise types confirmed that the proposed method gives more accurate estimates of the overall quality compared with the method described in ITU-T Rec. P.563.

Consider a client who intends to perform a massive computing task comprsing a number of sub-tasks, while both storage and computation are outsourced by a third-party service provider. How could the client ensure the integrity and completeness of the computation result? Meanwhile, how could the assurance mechanism incur no disincentive, e.g., excessive communication cost, for any service provider or client to participate in such a scheme? We detail this problem and present a general model of execution assurance for massive computing tasks. A series of key features distinguish our work from existing ones: a) we consider the context wherein both storage and computation are provided by untrusted third parties, and client has no data possession; b) we propose a simple yet effective assurance model based on a novel integration of the machineries of data authentication and computational private information retrieval (cPIR); c) we conduct an analytical study on the inherent trade-offs among the verification accuracy, and the computation, storage, and communication costs.

LCD Automatic Vision Inspection (AVI) systems automatically detect defect features and measure their sizes via camera vision. AVI systems usually report different measurements on the same defect with some variations on position or rotation mainly because we get different images. This is caused by possible variations in the image acquisition process including optical factors, non-uniform illumination, random noise, and so on. For this reason, conventional area based defect measuring method has some problems in terms of robustness and consistency. In this paper, we propose a new defect size measuring method to overcome these problems. We utilize volume information which is completely ignored in the area based conventional defect measuring method. We choose a bell shape as a defect model for experiment. The results show that our proposed method dramatically improves robustness of defect size measurement. Given proper modeling, the proposed volume based measuring method can be applied to various types of defect for better robustness and consistency.

RC4 is the stream cipher proposed by Rivest in 1987, which is widely used in a number of commercial products because of its simplicity and substantial security. RC4 exploits shuffle-exchange paradigm, which uses a permutation S. Many attacks have been reported so far. No study, however, has focused on correlations in the Pseudo-Random Generation (PRGA) between two permutations S and S' with some differences, nevertheless such correlations are related to an inherent weakness of shuffle-exchange-type PRGA. In this paper, we investigate the correlations between S and S' with some differences in the initial round. We show that correlations between S and S' remain before "i" is in the position where the nonzero-bit difference exists in the initial round, and that the correlations remain with non negligible probability even after "i" passed by the position. This means that the same correlations between S and S' will be observed after the 255-th round. This reveals an inherent weakness of shuffle-exchange-type PRGA.

This letter proposes a low-complexity scheme for estimating the frequency of a complex sinusoid in flat fading channels. The proposed estimator yields an estimation performance that is comparable to the existing autocorrelation-based frequency estimator, while retaining the same frequency range. Its implementation complexity is much lower than the conventional scheme, thus this allows for fast estimation in real time.

This paper presents a fast method capable of accelerating the Smith-Waterman algorithm for biological database search on a cluster of graphics processing units (GPUs). Our method is implemented using compute unified device architecture (CUDA), which is available on the nVIDIA GPU. As compared with previous methods, our method has four major contributions. (1) The method efficiently uses on-chip shared memory to reduce the data amount being transferred between off-chip video memory and processing elements in the GPU. (2) It also reduces the number of data fetches by applying a data reuse technique to query and database sequences. (3) A pipelined method is also implemented to overlap GPU execution with database access. (4) Finally, a master/worker paradigm is employed to accelerate hundreds of database searches on a cluster system. In experiments, the peak performance on a GeForce GTX 280 card reaches 8.32 giga cell updates per second (GCUPS). We also find that our method reduces the amount of data fetches to 1/140, achieving approximately three times higher performance than a previous CUDA-based method. Our 32-node cluster version is approximately 28 times faster than a single GPU version. Furthermore, the effective performance reaches 75.6 giga instructions per second (GIPS) using 32 GeForce 8800 GTX cards.

In this paper, we propose a method for finding web sites whose links are hijacked by web spammers. A hijacked site is a trustworthy site that points to untrustworthy sites. To detect hijacked sites, we evaluate the trustworthiness of web sites, and examine how trustworthy sites are hijacked by untrustworthy sites in their out-neighbors. The trustworthiness is evaluated based on the difference between the white and spam scores that calculated by two modified versions of PageRank. We define two hijacked scores that measure how likely a trustworthy site is to be hijacked based on the distribution of the trustworthiness in its out-neighbors. The performance of those hijacked scores are compared using our large-scale Japanese Web archive. The results show that a better performance is obtained by the score that considers both trustworthy and untrustworthy out-neighbors, compared with the one that only considers untrustworthy out-neighbors.

Bag-of-Visual-Words representation has recently become popular for scene classification. However, learning the visual words in an unsupervised manner suffers from the problem when faced these patches with similar appearances corresponding to distinct semantic concepts. This paper proposes a novel supervised learning framework, which aims at taking full advantage of label information to address the problem. Specifically, the Gaussian Mixture Modeling (GMM) is firstly applied to obtain "semantic interpretation" of patches using scene labels. Each scene induces a probability density on the low-level visual features space, and patches are represented as vectors of posterior scene semantic concepts probabilities. And then the Information Bottleneck (IB) algorithm is introduce to cluster the patches into "visual words" via a supervised manner, from the perspective of semantic interpretations. Such operation can maximize the semantic information of the visual words. Once obtained the visual words, the appearing frequency of the corresponding visual words in a given image forms a histogram, which can be subsequently used in the scene categorization task via the Support Vector Machine (SVM) classifier. Experiments on a challenging dataset show that the proposed visual words better perform scene classification task than most existing methods.

Social bookmarking services have recently made it possible for us to register and share our own bookmarks on the web and are attracting attention. The services let us get structured data: (URL, Username, Timestamp, Tag Set). And these data represent user interest in web pages. The number of bookmarks is a barometer of web page value. Some web pages have many bookmarks, but most of those bookmarks may have been posted far in the past. Therefore, even if a web page has many bookmarks, their value is not guaranteed. If most of the bookmarks are very old, the page may be obsolete. In this paper, by focusing on the timestamp sequence of social bookmarkings on web pages, we model their activation levels representing current values. Further, we improve our previously proposed ranking method for web search by introducing the activation level concept. Finally, through experiments, we show effectiveness of the proposed ranking method.

The bit-error-rate (BER) performance predicted by the semi-analytical evolution technique proposed by Li Ping et al. becomes inaccurate for parallel concatenated coded interleave-division multiple-access (PCC-IDMA) systems. To solve this problem, we develop a novel evolution technique of such systems. Numerical results show that the predicted performance agrees well with the simulation results, and that this technique is useful for system optimization.

People are being inundated under enormous volumes of information and they often dither about making the right choices from these. Interactive user support by information service system such as concierge services will effectively assist such people. However, human-machine interaction still lacks naturalness and thoughtfulness despite the widespread utilization of intelligent systems. The system needs to estimate user's interest to improve the interaction and support the choices. We propose a novel approach to estimating the interest, which is based on the relationship between the dynamics of user's eye movements, i.e., the endogenous control mode of saccades, and machine's proactive presentations of visual contents. Under a specially-designed presentation phase to make the user express the endogenous saccades, we analyzed the timing structures between the saccades and the presentation events. We defined resistance as a novel time-delay feature representing the duration a user's gaze remains fixed on the previously presented content regardless of the next event. In experimental results obtained from 10 subjects, we confirmed that resistance is a good indicator for estimating the interest of most subjects (75% success in 28 experiments on 7 subjects). This demonstrated a higher accuracy than conventional estimates of interest based on gaze duration or frequency.

With the scaling down of CMOS devices, process variation is becoming the leading cause of CMOS based analog circuit failures. For example, a mere 5% variation in feature size can trigger circuit failure. Various methods such as Monte-Carlo and corner-based verification help predict variation caused problems at the expense of thousands of simulations before capturing the problem. This paper presents a new methodology for analog circuit performance prediction. The new method first applies statistical uncertainty analysis on all associated devices in the circuit. By evaluating the uncertainty importance of parameter variability, it approximates the circuit with only components that are most critical to output results. Applying Chebyshev Affine Arithmetic (CAA) on the resulting system provides both performance bounds and probability information in time domain and frequency domain.

As the spread of high-speed networks and the development of network technologies, P2P technologies are actively used today for information exchange in the network. While information exchange in a P2P network is quite flexible, there is an important problem--lack of reliability. Since we cannot know the details of how the data was obtained, it is hard to fully rely on it. To ensure the reliability of exchanged data, we have proposed the framework of a traceable P2P record exchange based on database technologies. In this framework, records are exchanged among autonomous peers, and each peer stores its exchange and modification histories in it. The framework supports the function of tracing queries to query the details of the obtained data. A tracing query is described in datalog and executed as a recursive query in the P2P network. In this paper, we focus on the query processing strategies for the framework. We consider two types of queries, ad hoc queries and continual queries, and present the query processing strategies for their executions.

A network of sensors can be used to obtain state based data from the area in which they are deployed. To reduce costs, the data sent via intermediate sensors to a sink are often aggregated. In this letter, we introduce Self-Construction of Aggregation Tree (SCAT) scheme which uses a novel data aggregation scheme utilizing the knowledge of the mobile node and the infrastructure (static node tree) in gathering the data from the mobile node. The static nodes can construct a near- optimal aggregation tree by themselves, using the knowledge of the mobile node, which is a process similar to forming the centralized aggregation tree.

A new mixed-voltage I/O buffer for low-voltage low-latency operation is proposed in this paper. The proposed buffer adopts a novel delay-based timing-control scheme to efficiently avoid problems like gate-oxide stress and hot-carrier degradation. The proposed timing-control scheme also allows the buffer to have a lower latency for transmitting data by avoiding the use of timing-critical circuits like series-connected transmission gates (TGs) and triple-stacked transistors. The latency for receiving data at low supply voltage is also reduced by employing a variable stacked transistor gate-biasing scheme. Comparison results in an 80-nm CMOS process indicated that the proposed mixed-voltage I/O buffer improved up to 79.3% for receiving the external data and up to 23.8% for transmitting the internal data at a supply voltage of 1.2 V.

Recently, the orthogonal frequency-division multiple access (OFDMA) based wireless communication system is usually used in interactive digital video broadcasting environments or the wireless metropolitan area network (WMAN). Therefore, the relative condition of the inter-user channel can be easily deteriorated. This letter proposes and evaluates the mutual amplify-and-forward (AF) cooperation between two users using modified space time block code (STBC) to provide the reliability for an OFDMA system with a single antenna in an inferior inter-user channel environment. As a result, an OFDMA system adopting the proposed cooperation becomes more robust to inferior inter-user channels than our previously proposed decode-and-forward (DF) cooperation.

A new adaptive algorithm is proposed by introducing some modifications to the recursive least squares (RLS) algorithm. Except for the noise variance, the proposed algorithm does not require any statistics or knowledge of the desired signal, thus, it is suitable for adaptive filtering for channel estimation in code division multiple access (CDMA) systems in cases where the standard RLS approach cannot be used. A theoretical analysis demonstrates the convergence of the proposed algorithm, and simulation results for CDMA channel estimation show that the proposed algorithm outperforms existing channel estimation schemes.

A novel turbo coded modulation scheme, called the turbo-APPM, for deep space optical communications is proposed. The proposed turbo-APPM is a serial concatenation of turbo codes, an accumulator and a pulse position modulation (PPM), where turbo codes act as an outer code while the accumulator and the PPM act together as an inner code. The generator polynomial and the puncturing rule for generating turbo codes are chosen to lower the bit error rate. At the receiver, the joint iterative decoding is performed between the inner decoder and the outer turbo decoder. In the outer decoder, local iterative decoding for turbo codes is conducted. Simulation results are presented showing that the proposed turbo-APPM outperforms all previously proposed schemes such as LDPC-APPM, RS-PPM and SCPPM reported in the literature.

In this paper, a modified Belief Propagation (BP) decoding algorithm for low-density parity check (LDPC) codes based on minimum mean square error (MMSE) criterion is proposed. This modified algorithm uses linear equation to replace the hyperbolic function in the original BP algorithm and optimizes the linear approximation error based on MMSE criterion. As a result, compared with the standard BP algorithm the computational complexity is reduced significantly as the modified algorithm requires only addition operations to implement. Besides that simulation results show our modified algorithm can achieve an error performance very close to the BP algorithm on the additive white Gaussian noise channel.