This letter presents a simple and explicit formulation of non-unique Wiener filters associated with the linear predictor for processing of sinusoids. It was shown in the literature that, if the input signal consists of only sinusoids and does not include a white noise, the input autocorrelation matrix in the Wiener-Hopf equation becomes rank-deficient and thus the Wiener filter is not uniquely determined. In this letter we deal with this rank-deficient problem and present a mathematical description of non-unique Wiener filters in a simple and explicit form. This description is directly obtained from the tap number, the frequency of sinusoid, and the delay parameter. We derive this result by means of the elementary row operations on the augmented matrix given by the Wiener-Hopf equation. We also show that the conventional Wiener filter for noisy input signal is included as a special case of our description.

Buffer overflow is one of the main approaches to get control of vulnerable programs. This paper presents a protection technique called BFWindow for performance and resource sensitive embedded systems. By coloring data structure in memory with single associate property bit to each byte and extending the target memory block to a BFWindow(2), it validates each memory write by speculatively checking consistency of data properties within the extended buffer window. Property bits are generated by compiler statically and checked by hardware at runtime. They are transparent to users. Experimental results show that the proposed mechanism is effective to prevent sequential memory writes from crossing buffer boundaries which is the common scenario of buffer overflow exploitations. The performance overhead for practical protection mode across embedded system benchmarks is under 1%.

Network Intrusion Detection Systems (NIDS) are deployed to protect computer networks from malicious attacks. Proper evaluation of NIDS requires more scrutiny than the evaluation for general network appliances. This evaluation is commonly performed by sending pre-generated traffic through the NIDS. Unfortunately, this technique is often limited in diversity resulting in evaluations incapable of examining the complex data structures employed by NIDS. More sophisticated methods that generate workload directly from NIDS rules consume excessive resources and are incapable of running in real-time. This work proposes a novel approach to real-time workload generation for NIDS evaluation to improve evaluation diversity while maintaining much higher throughput. This work proposes a generative grammar which represents an optimized version of a context-free grammar derived from the set of strings matching to the given NIDS rule database. The grammar is memory-efficient and computationally light when generating workload. Experiments demonstrate that grammar-generated workloads exert an order of magnitude more effort on the target NIDS. Even better, this improved diversity comes at much smaller cost in memory and speeds four times faster than current approaches.

A simple approach is presented for designing an antipodal Vivaldi antenna in this paper. A new and better estimation of the low frequency end of the operational range is shown. Final dimensions of the antenna parameters are determined by using the High Frequency Structure Simulator (HFSS). The proposed antenna has a simple configuration but exhibits low return loss, good radiation characteristics, and high and flat gain in the operating ultra wideband frequency range (3.1-10.6 GHz). Lastly, the fabrication has been done along with the specification to confirm the properties by measurements.

In this paper, we propose a single-channel speech enhancement method for a push-to-talk enabled wireless communication device. The proposed method is based on adaptive weighted β-order spectral amplitude estimation under speech presence uncertainty and enhanced instantaneous phase estimation in order to achieve flexible and effective noise reduction while limiting the speech distortion due to different noise conditions. Experimental results confirm that the proposed method delivers higher voice quality and intelligibility than the reference methods in various noise environments.

In the European satellite broadcasting specifications, the symbol rate and the carrier frequency are not regulated. Furthermore, the first generation format DVB-S does not have any control signals. In a practical environment, the received signal condition is not stable due to the imperfect reception environment, i.e., unterminated receiver ports, cheap indoor wiring cables etc. These issues prevent correct detection of the satellite signals. For this reason, the conventional signal detection method uses brute force search for detecting the received signal's cyclostationarity, which is an extremely time-consuming approach. A coarse estimation method of the carrier frequency and the bandwidth was proposed by us based on the power spectrum. We extend this method to create a new method for detecting satellite broadcasting signals, which can significantly reduce the search range. In other words, the proposed method can detect the signals in a relatively short time. In this paper, the proposed method is applied to signals received in an actual environment. Our analysis shows that the proposed method can effectively reduce the detection time at almost a same detection performance.

This study investigates a real-time joint channel and hyperparameter estimation method for orthogonal frequency division multiplexing mobile communications. The channel frequency response of the pilot subcarrier and its fixed hyperparameters (such as channel statistics) are estimated using a Liu and West filter (LWF), which is based on the state-space model and sequential Monte Carlo method. For the first time, to our knowledge, we demonstrate that the conventional LWF biases the hyperparameter due to a poor estimate of the likelihood caused by overfitting in noisy environments. Moreover, this problem cannot be solved by conventional smoothing techniques. For this, we modify the conventional LWF and regularize the likelihood using a Kalman smoother. The effectiveness of the proposed method is confirmed via numerical analysis. When both of the Doppler frequency and delay spread hyperparameters are unknown, the conventional LWF significantly degrades the performance, sometimes below that of least squares estimation. By avoiding the hyperparameter estimation failure, our method outperforms the conventional approach and achieves good performance near the lower bound. The coding gain in our proposed method is at most 10 dB higher than that in the conventional LWF. Thus, the proposed method improves the channel and hyperparameter estimation accuracy. Derived from mathematical principles, our proposal is applicable not only to wireless technology but also to a broad range of related areas such as machine learning and econometrics.

Forming Business Continuity Planning (BCP) is recognized as a significant counter-measure against future large-scale disasters by private enterprises after the 2011 Great East Japan Earthquake more than before. Based on a questionnaire survey, this paper reports business recovery conditions of private enterprises in Miyagi Prefecture affected by the disaster. Analyzing the results of questionnaire, it suggests some important points: (1) estimation of long-term internal/external factors that influence business continuity, (2) development of concrete pre-disaster framework, (3) multi-media-based advertising strategy, and (4) re-allocation of resources.

Based on a ternary perfect sequence and a binary orthogonal matrix, the Z-periodic complementary sequence (ZPCS) sets over the 8-QAM+ constellation are constructed. The resultant sequences can be used in multi-carriers code division multiple access (MC-CDMA) systems to remove interference and increase the transmission rate. The proposed construction provides flexible choice for parameters so as to meet different requirements in the application. A construction of shift sequence sets is proposed and the number of 8-QAM ZPCS sets is extended by changing the parameters of shift sequences. As a result, more users can be accommodated in the system.

We introduce the design and deployment of the latest version of the VNode infrastructure, VNode-i. We present new extended VNode-i functions that offer high performance and provide convenient deep programmability to network developers. We extend resource abstraction to the transport network and achieve highly precise slice measurement for resource elasticity. We achieve precise resource isolation for VNode-i. We achieve coexistence of high performance and programmability. We also enhance AGW functions. In addition, we extend network virtualization from the core network to edge networks and terminals. In evaluation experiments, we deploy the enhanced VNode-i on the JGN-X testbed and evaluate its performance. We successfully create international federation slices across VNode-i, GENI, and Fed4FIRE. We also present experimental results on video streaming on a federated slice across VNode-i and GENI. Testbed experiments confirm the practicality of the enhanced VNode-i.

With the flourish of applications based on the Internet of Things (IoT), privacy issues have been attracting a lot of attentions. Although the concept of privacy homomorphism was proposed along with the birth of the well-known RSA cryptosystems, cryptographers over the world have spent about three decades for finding the first implementation of the so-called fully homomorphic encryption (FHE). Despite of, currently known FHE schemes, including the original Gentry's scheme and many subsequent improvements as well as the other alternatives, are not appropriate for IoT-oriented applications because most of them suffer from the problems of inefficient key size and noisy restraining. In addition, for providing fully support to IoT-oriented applications, symmetric fully homomorphic encryptions are also highly desirable. This survey presents an analysis on the challenges of designing secure and practical FHE for IoT, from the perspectives of lightweight requirements as well as the security requirements. In particular, some issues about designing noise-free FHE schemes would be addressed.

Location-based services (LBSs) are useful for many applications in internet of things(IoT). However, LBSs has raised serious concerns about users' location privacy. In this paper, we propose a new location privacy attack in LBSs called hidden location inference attack, in which the adversary infers users' hidden locations based on the users' check-in histories. We discover three factors that influence individual check-in behaviors: geographic information, human mobility patterns and user preferences. We first separately evaluate the effects of each of these three factors on users' check-in behaviors. Next, we propose a novel algorithm that integrates the above heterogeneous factors and captures the probability of hidden location privacy leakage. Then, we design a novel privacy alert framework to warn users when their sharing behavior does not match their sharing rules. Finally, we use our experimental results to demonstrate the validity and practicality of the proposed strategy.

Logistic regression is a powerful machine learning tool to classify data. When dealing with sensitive or private data, cares are necessary. In this paper, we propose a secure system for privacy-protecting both the training and predicting data in logistic regression via homomorphic encryption. Perhaps surprisingly, despite the non-polynomial tasks of training and predicting in logistic regression, we show that only additively homomorphic encryption is needed to build our system. Indeed, we instantiate our system with Paillier, LWE-based, and ring-LWE-based encryption schemes, highlighting the merits and demerits of each instantiation. Besides examining the costs of computation and communication, we carefully test our system over real datasets to demonstrate its utility.

In this paper, we propose a multi-cell structure backscatter based wireless-powered communication network (WPCN) where a number of backscatter cells are locally separated, each containing a subset of users around a carrier emitter. The multi-cell structure backscatter based WPCN can be implemented in two ways, namely time-division multiplexing (TDM) and frequency-division multiplexing (FDM). Here users harvest energy from the carrier signal transmitted by the carrier emitter, and then transmit their own information in a passive way via the reflection of the carrier signal using frequency-shift keying modulation. We characterize the energy-free condition and the signal-to-noise ratio (SNR) outage zone in a backscatter based WPCN. Also, a backscatter based harvest-then-transmit protocol is adopted to maximize the sum-throughput of all users by optimally allocating time for energy harvesting and information transmission. Numerical results demonstrate that the backscatter based WPCN ensures an increased long-range coverage and a diminished SNR outage zone compared to conventional radio based WPCNs. Also, comparing the two types of multi-cell structure backscatter based WPCN, TDM within each backscatter cell and FDM across backscatter cells versus FDM within each backscatter cell and TDM across backscatter cells, numerical results confirm that which one yields a better performance.

Interference alignment (IA) is a method to improve the capacity of cell-edge users and thus attracts an intense research interest. We focus on the IA extended to the multiple-input multiple-output (MIMO) interference network. In this method, each coordinated transmitter generates beamforming vectors to align interference from different transmitters into confined subspace at each receiver. Then, using singular value decomposition (SVD) with the relative magnitude coefficients, transmitters calculate the beamforming vectors and the received vectors. However, in this method it is difficult to determine the value of the relative magnitude coefficients so that the system capacity is improved, because it is necessary to solve the non-linear function of multivariable. In this paper, we propose a design method of the relative magnitude coefficients of interference channels to improve system capacity using Brent's method on the K-User MIMO interference channel (MIMO-IFC). The proposed method can improve system capacity, though the system complexity increases due to Brent's method that requires multiple SVD calculation to calculate the null space. Thus, instead of using SVD, we introduce the complexity reduction method to calculate the null space of the matrix. Furthermore, we extend the proposed method to be applicable for more common systems where all base stations have the same number of transmit antennas. Through simulation, we show that the proposed method achieves a higher system capacity than the conventional one. We also show that the method that calculates the null space needs much lower complexity than SVD. In addition, we show that the proposed design method reduces the degradation of the system capacity caused by the interference not eliminated, and achieves the fairness of capacities among users for an increase of the number of design coefficients.

Recently in an SDN/NFV-enabled network, a consolidated middlebox is proposed in which middlebox functions required by a network flow are provided at a single machine in a virtualized manner. With the promising advantages such as simplifying network traffic routing and saving resources of switches and machines, consolidated middleboxes are going to replace traditional middleboxes in the near future. However, the location of consolidated middleboxes may affect the performance of an SDN/NFV network significantly. Accordingly, the consolidated middlebox positioning problem in an SDN/NFV-enabled network must be addressed adequately with service chain constraints (a flow must visit a specific type of consolidated middlebox), resource constraints (switch memory and processing power of the machine), and performance requirements (end-to-end delay and bandwidth consumption). In this paper, we propose a novel solution of the consolidated middlebox positioning problem in an SDN/NFV-enabled network based on flow clustering to improve the performance of service chain flows and utilization of a consolidated middlebox. Via extensive simulations, we show that our solution significantly reduces the number of routing rules per switch, the end-to-end delay and bandwidth consumption of service flows while meeting service chain and resource constraints.

This paper proposes a blind, inaudible, robust digital-audio watermarking scheme based on singular-spectrum analysis, which relates to watermarking techniques based on singular value decomposition. We decompose a host signal into its oscillatory components and modify amplitudes of some of those components with respect to a watermark bit and embedding rule. To improve the sound quality of a watermarked signal and still maintain robustness, differential evolution is introduced to find optimal parameters of the proposed scheme. Test results show that, although a trade-off between inaudibility and robustness still persists, the difference in sound quality between the original and the watermarked one is considerably smaller. This improved scheme is robust against many attacks, such as MP3 and MP4 compression, and band-pass filtering. However, there is a drawback, i.e., some music-dependent parameters need to be shared between embedding and extraction processes. To overcome this drawback, we propose a method for automatic parameter estimation. By incorporating the estimation method into the framework, those parameters need not to be shared, and the test results show that it can blindly decode watermark bits with an accuracy of 99.99%. This paper not only proposes a new technique and scheme but also discusses the singular value and its physical interpretation.

In this paper, we propose an overloaded multiple-input multiple-output (MIMO) signal detection scheme with slab decoding and lattice reduction (LR). The proposed scheme firstly splits the transmitted signal vector into two parts, the post-voting vector composed of the same number of signal elements as that of receive antennas, and the pre-voting vector composed of the remaining elements. Secondly, it reduces the candidates of the pre-voting vector using slab decoding and determines the post-voting vectors for each pre-voting vector candidate by LR-aided minimum mean square error (MMSE)-successive interference cancellation (SIC) detection. From the performance analysis of the proposed scheme, we derive an upper bound of the error probability and show that it can achieve the full diversity order. Simulation results show that the proposed scheme can achieve almost the same performance as the optimal ML detection while reducing the required computational complexity.

We arrange disaster mitigation activities into temporal order and discuss the contribution of information and communications technology (ICT) to the reduction of disaster damage in the stages of precaution, emergency response, and post-mortem study. Examples of the current contribution of ICT are introduced and future possible uses of ICT are discussed. We focus on the contribution of ICT to decision-making in emergency responses by augmenting human intelligence. Research directions of ICT for disaster mitigation technology are summarized in the categories “tough ICT”, “intelligence amplification for decision-making in disaster mitigation” and “safe ICT.”

We propose a simple configuration for colorless and directionless (CD) reconfigurable optical add/drop multiplexers that enables ultra-low contention add/drop operation to be achieved. In the configuration, we apply a combination of multiple small-port-count CD add/drop banks (CD banks) and round-robin CD bank assignment. Evaluation results show that the proposed configuration can substantially reduce intra-node contention rate, which is less than 0.1%. We also find that the proposed configuration can improve the utilization efficiency of wavelength resources and transponders. We discuss the mechanism of how the proposed configuration reduces intra-node contention by analyzing the status of wavelength assignments in direction ports and CD banks.