Group signatures are a class of digital signatures with enhanced privacy. By using this type of signature, a user can sign a message on behalf of a specific group without revealing his identity, but in the case of a dispute, an authority can expose the identity of the signer. However, it is not always the case that we need to know the specific identity of a signature. In this paper, we propose the notion of deniable group signatures, where the authority can issue a proof showing that the specified user is NOT the signer of a signature, without revealing the actual signer. We point out that existing efficient non-interactive zero-knowledge proof systems cannot be straightforwardly applied to prove such a statement. We circumvent this problem by giving a fairly practical construction through extending the Groth group signature scheme (ASIACRYPT 2007). In particular, a denial proof in our scheme consists of 96 group elements, which is about twice the size of a signature in the Groth scheme. The proposed scheme is provably secure under the same assumptions as those of the Groth scheme.

Fuzzy controller can be useful to realize a practical closed-loop FES controller, because it is possible to make it easy to design FES controller and to determine its parameter values, especially for controlling multi-joint movements by stimulating many muscles including antagonistic muscle pairs. This study focused on using fuzzy controller for the closed-loop control of cycling speed during FES cycling with pedaling wheelchair. However, a designed fuzzy controller has to be tested experimentally in control performance. In this paper, a closed-loop fuzzy FES controller was designed and tested in knee extension movements comparing to a PID controller with healthy subjects before applying to FES cycling. The developed fuzzy controller showed good control performance as a whole in comparing to PID controller and its parameter values were determined through simple control tests of the target movement.

An inter-subset uncorrelated zero-correlation zone (ZCZ) sequence pair set is one consisting of multiple ZCZ sequence pair subsets. What's more, two arbitrary sequence pairs which belong to different subsets should be uncorrelated sequence pairs in this set, i.e., the cross-correlation function (CCF) between arbitrary sequence pairs in different subsets are zeros at everywhere. Meanwhile, each subset is a typical ZCZ sequence pair set. First, a class of uncorrelated ZCZ (U-ZCZ) sequence pair sets is proposed from interleaving perfect sequence pairs. An U-ZCZ sequence pair set is a type of ZCZ sequence pair set, which of most important property is that the CCF between two arbitrary sequence pairs is zero at any shift. Then, a type of inter-subset uncorrelated ZCZ sequence pair set is obtained by interleaving proposed U-ZCZ sequence pair set. In particular, the novel inter-subset uncorrelated ZCZ sequence pair sets are expected to be useful for designing spreading codes for QS-CDMA systems.

We describe SyncSync, a time-of-arrival (ToA)-based localization method for smartphones. In general, ToA measurements show better precision than time-difference-of-arrival (TDoA) measurements, although ToA systems require a synchronization mechanism between anchor and mobile nodes. For this synchronization, we employ modulated LED light with an acoustic wave for time-of-flight distance measurements. These are detected by the smartphone's video camera and microphone. The time resolution in consumer video cameras is typically only a few tenths of a second, but by utilizing a CMOS image sensor's rolling shutter effect we obtain synchronization resolutions of a few microseconds, which is sufficient for precise acoustic ToA measurements. We conducted experiments to confirm operation of the system, and obtained ToA localization errors within 10mm. The characteristics of the error distributions for both TDoA and ToA measurements were explained by dilution of precision.

This letter presents two constructions of Gaussian integer Z-periodic complementary sequences (ZPCSs), which can be used in multi-carriers code division multiple access (MC-CDMA) systems to remove interference and increase transmission rate. Construction I employs periodic complementary sequences (PCSs) as the original sequences to construct ZPCSs, the parameters of which can achieve the theoretical bound if the original PCS set is optimal. Construction II proposes a construction for yielding Gaussian integer orthogonal matrices, then the methods of zero padding and modulation are implemented on the Gaussian integer orthogonal matrix. The result Gaussian integer ZPCS sets are optimal and with flexible choices of parameters.

Ransomware becomes more and more threatening nowadays. In this paper, we propose CLDSafe, a novel and efficient file backup system against ransomware. It keeps shadow copies of files and provides secure restoration using cloud storage when a computer is infected by ransomware. After our system measures file similarities between a new file on the client and an old file on the server, the old file on the server is backed up securely when the new file is changed substantially. And then, only authenticated users can restore the backup files by using challenge-response mechanism. As a result, our proposed solution will be helpful in recovering systems from ransomware damage.

This paper expands Bartlett's bisection theorem. The theory of modal S-parameters and their circuit representation is constructed from a group-theoretic perspective. Criteria for the division of a circuit at a fixed node whose state is distinguished by the irreducible representation of its stabilizer subgroup are obtained, after being inductively introduced using simple circuits as examples. Because these criteria use only circuit symmetry and do not require human judgment, the distinction is reliable and implementable in a computer. With this knowledge, the entire circuit can be characterized by a finite combination of smaller circuits. Reducing the complexity of symmetric circuits contributes to improved insights into their characterization, and to savings of time and effort in calculations when applied to large-scale circuits. A three-phase filter and a branch-line coupler are analyzed as application examples of circuit and electromagnetic field analysis, respectively.

Many basic tasks in Wireless Sensor Networks (WSNs) rely heavily on the availability and accuracy of target locations. Since the number of targets is usually limited, localization benefits from Compressed Sensing (CS) in the sense that measurements can be greatly reduced. Though some CS-based localization schemes have been proposed, all of these solutions make an assumption that all targets are located on a pre-sampled and fixed grid, and perform poorly when some targets are located off the grid. To address this problem, we develop an adaptive dictionary algorithm where the grid is adaptively adjusted. To achieve this, we formulate localization as a joint parameter estimation and sparse signal recovery problem. Additionally, we transform the problem into a tractable convex optimization problem by using Taylor approximation. Finally, the block coordinate descent method is leveraged to iteratively optimize over the parameters and sparse signal. After iterations, the measurements can be linearly represented by a sparse signal which indicates the number and locations of targets. Extensive simulation results show that the proposed adaptive dictionary algorithm provides better performance than state-of-the-art fixed dictionary algorithms.

Wireless sensor network (WSN) has attracted many researchers to investigate it in recent years. It can be widely used in the areas of surveillances, health care and agriculture. The location information is very important for WSN applications such as geographic routing, data fusion and tracking. So the localization technology is one of the key technologies for WSN. Since the computational complexity of the traditional source localization is high, the localization method can not be used in the sensor node. In this paper, we firstly introduce the Neyman-Pearson criterion based detection model. This model considers the effect of false alarm and missing alarm rate, so it is more realistic than the binary and probability model. An affinity propagation algorithm based localization method is proposed. Simulation results show that the proposed method provides high localization accuracy.

The Internet of Things (IoT) is defined as a global infrastructure for the Information Society, enabling advanced services by interconnecting (physical and virtual) things based on, existing and evolving, interoperable information and communication technologies by ITU-T. Data may be communicated in low-power and lossy environments, which causes complicated security issues. Furthermore, concerns are raised over access of personally identifiable information pertaining to IoT devices, network and platforms. Security and privacy concerns have been main barriers to implement IoT, which needs to be resolved appropriate security and privacy measures. This paper describes security threats and privacy concerns of IoT, surveys current studies related to IoT and identifies the various requirements and solutions to address these security threats and privacy concerns. In addition, this paper also focuses on major global standardization activities for security and privacy of Internet of Things. Furthermore, future directions and strategies of international standardization for theInternet of Thing's security and privacy issues will be given. This paper provides guidelines to assist in suggesting the development and standardization strategies forward to allow a massive deployment of IoT systems in real world.

IEEE 802.11ah is an emerging wireless LAN standard in the sub-1-GHz license-exempt bands for cost-effective and range-extended communication. One of the most challenging issues that need to be overcome in relation to IEEE 802.11ah is to ensure that thousands of stations are able to associate efficiently with a single access point. During network initialization, several thousand stations try to associate with the access point, leading to heavy channel contention and long association delay. Therefore, IEEE 802.11ah has introduced an authentication control mechanism that classifies stations into groups and only a small number of stations in a group are allowed to access the medium in a beacon interval. This grouping strategy provides fair channel access to a large number of stations. However, the approach to grouping the stations and determining the best group size is undefined in the draft of IEEE 802.11ah. In this paper, we first model the authentication/association in IEEE 802.11ah. Our analysis shows that there exists the best group size that results in minimal association delay. Consequently, the analytical model is extended to determine the best group size. Finally, an enhanced authentication control algorithm, which utilizes the best group size to provide the minimum association delay, is proposed. The numerical and the simulation results we obtained with the proposed method demonstrate that our method succeeds in minimizing the association delay.

In this study, an anonymization infrastructure for the secondary use of data is proposed. The proposed infrastructure can publish data that includes privacy information while preserving the privacy by using anonymization techniques. The infrastructure considers a situation where ill-motivated users redistribute the data without authorization. Therefore, we propose a watermarking method for anonymized data to solve this problem. The proposed method is implemented, and the proposed method's tolerance against attacks is evaluated.

The growing demand for high-speed data communication has continued to meet the need for ever-increasing I/O bandwidth in recent VLSI systems. However, signal integrity issues, such as intersymbol interference (ISI) and reflections, make the channel band-limited at high-speed data rates. We propose high-speed data transmission techniques for VLSI systems using Tomlinson-Harashima precoding (THP). Because THP can eliminate ISI by inverting the characteristics of channels with limited peak and average power at the transmitter, it is suitable for implementing advanced low-voltage and high-speed VLSI systems. This paper presents a novel double-rate THP equalization technique especially intended for multi-valued data transmission to further improve THP performance. Simulation and measurement results show that the proposed THP equalization with a double sampling rate can enhance the data transition time and, therefore, improve the eye opening.

In this paper, we propose a novel method for the design of CSD (Canonic Signed Digit) coefficient FIR (Finite Impulse Response) filters based on ACO (Ant Colony Optimization). This design problem is formulated as a combinatorial optimization problem and requires high computation time to obtain the optimal solution. Therefore, we propose an ACO approach for the design of CSD coefficient FIR filters. ACO is one of the promising approaches and appropriate for solving a combinatorial optimization problem in reasonable computation time. Several design examples showed the effectiveness of our method.

Discrete structure manipulation is a fundamental technique for many problems solved by computers. BDDs/ZDDs have attracted a great deal of attention for twenty years, because those data structures are useful to efficiently manipulate basic discrete structures such as logic functions and sets of combinations. Recently, one of the most interesting research topics related to BDDs/ZDDs is Frontier-based search method, a very efficient algorithm for enumerating and indexing the subsets of a graph to satisfy a given constraint. This work is important because many kinds of practical problems can be efficiently solved by some variations of this algorithm. In this article, we present recent research activity related to BDD and ZDD. We first briefly explain the basic techniques for BDD/ZDD manipulation, and then we present several examples of the state-of-the-art algorithms to show the power of enumeration.

In this paper, we present a method of analyzing relationships between items in specific health examination data, as one of the basic researches to address increases of lifestyle-related diseases. We use self-organizing maps, and pick up the data from the examination dataset according to the condition specified by some item values. We then focus on twelve items such as hemoglobin A1c (HbA1c), aspartate transaminase (AST), alanine transaminase (ALT), gamma-glutamyl transpeptidase (γ-GTP), and triglyceride (TG). We generate training data presented to a map by calculating the difference between item values associated with successive two years and normalizing the values of this calculation. We label neurons in the map on condition that one of the item values of training data is employed as a parameter. We finally examine the relationships between items by comparing results of labeling (clusters formed in the map) to each other. From experimental results, we separately reveal the relationships among HbA1c, AST, ALT, γ-GTP and TG in the unfavorable case of HbA1c value increasing and those in the favorable case of HbA1c value decreasing.

Massive multiple-input multiple-output (MIMO) technology is one of the key enablers in the fifth generation mobile communications (5G), in order to accommodate growing traffic demands and to utilize higher super high frequency (SHF) and extremely high frequency (EHF) bands. In the paper, we propose a novel transmit precoding named “nonlinear block multi-diagonalization (NL-BMD) precoding” for multiuser MIMO (MU-MIMO) downlink toward 5G. Our NL-BMD precoding strategy is composed of two essential techniques: block multi-diagonalization (BMD) and adjacent inter-user interference pre-cancellation (IUI-PC). First, as an extension of the conventional block diagonalization (BD) method, the linear BMD precoder for the desired user is computed to incorporate a predetermined number of interfering users, in order to ensure extra degrees of freedom at the transmit array even after null steering. Additionally, adjacent IUI-PC, as a nonlinear operation, is introduced to manage the residual interference partially allowed in BMD computation, with effectively-reduced numerical complexity. It is revealed through computer simulations that the proposed NL-BMD precoding yields up to 67% performance improvement in average sum-rate spectral efficiency and enables large-capacity transmission regardless of the user distribution, compared with the conventional BD precoding.

Nonnegative matrix factorization (NMF) is one of the most popular machine learning tools for speech enhancement. The supervised NMF-based speech enhancement is accomplished by updating iteratively with the prior knowledge of the clean speech and noise spectra bases. However, in many real-world scenarios, it is not always possible for conducting any prior training. The traditional semi-supervised NMF (SNMF) version overcomes this shortcoming while the performance degrades. In this letter, without any prior knowledge of the speech and noise, we present an improved semi-supervised NMF-based speech enhancement algorithm combining techniques of NMF and robust principal component analysis (RPCA). In this approach, fixed speech bases are obtained from the training samples chosen from public dateset offline. The noise samples used for noise bases training, instead of characterizing a priori as usual, can be obtained via RPCA algorithm on the fly. This letter also conducts a study on the assumption whether the time length of the estimated noise samples may have an effect on the performance of the algorithm. Three metrics, including PESQ, SDR and SNR are applied to evaluate the performance of the algorithms by making experiments on TIMIT with 20 noise types at various signal-to-noise ratio levels. Extensive experimental results demonstrate the superiority of the proposed algorithm over the competing speech enhancement algorithm.

This letter considers a backscatter assisted wireless powered communication network (BAWPCN) with non-orthogonal multiple access (NOMA). This model consists of a hybrid access point (HAP) and multiple users which can work in either backscatter or harvest-then-transmit (HTT) protocol. To fully exploit time for information transmission, the users working in the backscatter protocol are scheduled to reflect modulated signals during the first phase of the HTT protocol which is dedicated for energy transfer. During the second phase, all users working in the HTT protocol transmit information to the HAP simultaneously since NOMA is adopted. Considering both short-term and long-term optimization problems to maximize the system throughput, the optimal resource allocation policies are obtained. Simulation results show that the proposed model can significantly improve the system performance.

Recently, much progress has been made in the study of belief propagation (BP) based signal detection with large-scale factor graphs. When we apply the BP algorithm to equalization in a SISO multipath channel, the corresponding factor graph has many short loops and patterns in an edge connection/strength. Thus, proper convergence may not be achieved. In general, the log-likelihood ratio (LLR) oscillates in ill-converged cases. Therefore, LLR oscillation avoidance is important for BP-based equalization. In this paper, we propose applying node selection (NS) to prevent the LLR from oscillating. The NS extends the loop length virtually by a serial LLR update. Thus, some performance improvement is expected. Simulation results show that the error floor is significantly reduced by NS in the uncoded case and that the NS works very well in the coded case.