Symmetric predicate encryption schemes support a rich class of predicates over keyword ciphertexts while preserving both keyword privacy and predicate privacy. Most of these schemes treat each keyword as the smallest unit to be processed in the generation of ciphertexts and predicate tokens. To extend the class of predicates, we treat each symbol of a keyword as the smallest unit to be processed. In this letter, we propose a novel encoding to construct a symmetric inner-product encryption scheme for position-aware symbol-based predicates. The resulting scheme can be applied to a number of secure filtering and online storage services.

Currently there is not any prospect of realizing quantum computers which can compute prime factorization, which RSA relies on, or discrete logarithms, which ElGamal relies on, of practical size. Additionally the rapid growth of Internet of Things (IoT) is requiring practical public key cryptosystems which do not use exponential operation. Therefore we constituted a cryptosystem relying on the difficulty of factoring the product of two large prime numbers, based on the Chinese Remainder Theorem, fully exploiting another strength of MPKC that exponential operation is not necessary. We evaluated its security by performing the Gröbner base attacks with workstations and consequently concluded that it requires computation complexity no less than entirely random quadratic polynomials. Additionally we showed that it is secure against rank attacks since the polynomials of central map are all full rank, assuming the environment of conventional computers.

This paper shows accuracy of using azimuth-variable path-loss fitting in white-space (WS) boundary-estimation. We perform experiments to evaluate this method, and demonstrate that the required number of sensors can be significantly reduced. We have proposed a WS boundary-estimation framework that utilizes sensors to not only obtain spectrum sensing data, but also to estimate the boundaries of the incumbent radio system (IRS) coverage. The framework utilizes the transmitter position information and pathloss fitting. The pathloss fitting describes the IRS coverage by approximating the well-known pathloss prediction formula from the received signal power data, which is measured using sensors, and sensor-transmitter separation distances. To enhance its accuracy, we have further proposed a pathloss-fitting method that employs azimuth variables to reflect the azimuth dependency of the IRS coverage, including the antenna directivity of the transmitter and propagation characteristics.

The phenomenon of stochastic resonance (SR) in a mono-threshold-system-based detector (MTD) with additive background noise and multiplicative external noise is investigated. On the basis of maximum a posteriori probability (MAP) criterion, we deal with the binary signal transmission in four scenarios. The performance of the MTD is characterized by the probability of error detection, and the effects of system threshold and noise intensity on detectability are discussed in this paper. Similar to prior studies that focus on additive noises, along with increases in noise intensity, we also observe a non-monotone phenomenon in the multiplicative ways. However, unlike the case with the additive noise, optimal multiplicative noises all tend toward infinity for fixed additive noise intensities. The results of our model are potentially useful for the design of a sensor network and can help one to understand the biological mechanism of synaptic transmission.

In this paper, we derive two simple asymptotic closed-form formulas for the average bit error probability (BEP) of differential quaternary phase shift keying (DQPSK) with Gray encoding and a simple asymptotic approximation for the average symbol error probability (SEP) of doubly-differential quaternary phase shift keying (DDQPSK) in Nakagami-m fading channels. Compared with the existing BEP/SEP expressions, the derived concise formulas are much more effective in evaluating the asymptotic properties of DQPSK/DDQPSK with various Nakagami fading parameters, the accuracy of which is verified by extensive numerical results.

This paper presents a design methodology for positioning sub-platform from the viewpoint of positioning for smartphone-based location-based services (LBS). To achieve this, we analyze a mechanism of positioning error generation including principles of positioning sub-systems and structure of smartphones. Specifically, we carry out the experiments of smartphone positioning performance evaluation by the smartphone basic API (Application Programming Interface) and by the wireless LAN in various environments. Then, we describe the importance of considering three layers as follows: 1) the lower layer that caused by positioning sub-systems, e.g., GPS, wireless LAN, mobile base stations, and so on; 2) the middle layer that caused by functions provided from the platform such as Android and iOS; 3) the upper layer that caused by operation algorithm of applications on the platform.

The ordered successive interference cancellation (OSIC) detector based on the minimum mean square error (MMSE) criterion has been proved to be a low-complexity detector with efficient bit error rate (BER) performance. As the well-known MMSE-Based OSIC detector, the MMSE-Based vertical Bell Laboratories Layered Space-Time (VBLAST) detector, whose computational complexity is cubic, can not attain the minimum BER performance. Some approaches to reducing the BER of the MMSE-Based VBLAST detector have been contributed, however these improvements have large computational complexity. In this paper, a low complexity MMSE-Based OSIC detector called MMSE-OBEP (ordering based on error probability) is proposed to improve the BER performance of the previous MMSE-Based OSIC detectors, and it has cubic complexity. The proposed detector derives the near-exact error probability of the symbols in the MMSE-Based OSIC detector, thus giving priority to detect the symbol with the smallest error probability can minimize the error propagation in the MMSE-Based OSIC detector and enhance the BER performance. We show that, although the computational complexity of the proposed detector is cubic, it can provide better BER performance than the previous MMSE-Based OSIC detector.

In this paper, a method for designing of Incremental Granular Model (IGM) based on integration of Linear Regression (LR) and Linguistic Model (LM) with the aid of fuzzy granulation is proposed. Here, IGM is designed by the use of information granulation realized via Context-based Interval Type-2 Fuzzy C-Means (CIT2FCM) clustering. This clustering approach are used not only to estimate the cluster centers by preserving the homogeneity between the clustered patterns from linguistic contexts produced in the output space, but also deal with the uncertainty associated with fuzzification factor. Furthermore, IGM is developed by construction of a LR as a global model, refine it through the local fuzzy if-then rules that capture more localized nonlinearities of the system by LM. The experimental results on two examples reveal that the proposed method shows a good performance in comparison with the previous works.

This paper proposes a method of watermarking for digital audio signals based on adaptive phase modulation. Audio signals are usually non-stationary, i.e., their own characteristics are time-variant. The features for watermarking are usually not selected by combining the principle of variability, which affects the performance of the whole watermarking system. The proposed method embeds a watermark into an audio signal by adaptively modulating its phase with the watermark using IIR all-pass filters. The frequency location of the pole-zero of an IIR all-pass filter that characterizes the transfer function of the filter is adapted on the basis of signal power distribution on sub-bands in a magnitude spectrum domain. The pole-zero locations are adapted so that the phase modulation produces slight distortion in watermarked signals to achieve the best sound quality. The experimental results show that the proposed method could embed inaudible watermarks into various kinds of audio signals and correctly detect watermarks without the aid of original signals. A reasonable trade-off between inaudibility and robustness could be obtained by balancing the phase modulation scheme. The proposed method can embed a watermark into audio signals up to 100 bits per second with 99% accuracy and 6 bits per second with 94.3% accuracy in the cases of no attack and attacks, respectively.

Boneh and Franklin considered to add the revocation functionality to identity-based encryption (IBE). Though this methodology is applicable to any IBE and hierarchical IBE (HIBE), the resulting scheme is non-scalable. Therefore, a generic transformation of scalable revocable (H)IBE (R(H)IBE) from non-scalable R(H)IBE is really desirable. Towards this final goal, in this paper we introduce prototype RHIBE which does not require to be scalable (but requires some conditions), and propose a generic transformation of scalable RHIBE from prototype RHIBE. Moreover, we construct a prototype RHIBE scheme based on the decisional bilinear Diffie-Hellman (DBDH) assumption. Since our prototype RHIBE provides history-free update, insider security, and decryption key exposure resistance, our construction yields the first RHIBE scheme based on the static assumption with these desirable properties.

Broadcasting and communications networks can be used together to offer hybrid broadcasting services that incorporate a variety of personalized information from communications networks in TV programs. To enable these services, many different applications have to be run on a user terminal, and it is necessary to establish an environment where any service provider can create applications and distribute them to users. The danger is that malicious service providers might distribute applications which may cause user terminals to take undesirable actions. To prevent such applications from being distributed, we propose an application authentication protocol for hybrid broadcasting and communications services. Concretely, we modify a key-insulated signature scheme and apply it to this protocol. In the protocol, a broadcaster distributes a distinct signing key to each service provider that the broadcaster trusts. As a result, users can verify that an application is reliable. If a signed application causes an undesirable action, a broadcaster can revoke the privileges and permissions of the service provider. In addition, the broadcaster can update the signing key. That is, our protocol is secure against leakage of the signing key by the broadcaster and service providers. Moreover, a user terminal uses only one verification key for verifying a signature, so the memory needed for storing the verification key in the user terminal is very small. With our protocol, users can securely receive hybrid services from broadcasting and communications networks.

This paper presents two new types of markers of M-CubITS (M-sequence Multimodal Markers for ITS; M-Cubed for ITS) that is a ground-based positioning system, in order to advance the WYSIWYAS (What You See Is What You Are Suggested) navigation environments providing intuitive guidance. One of the new markers uses warning blocks of textured paving blocks that are often at important points as for pedestrian navigation, for example, the top and bottom of stairs, branch points, and so on. The other uses interlocking blocks that are often at wide spaces, e.g., pavements of plazas, parks, sidewalks and so on. Furthermore, we construct the integrated pedestrian navigation system equipped with the automatic marker-type identification function of the three types of markers (the warning blocks, the interlocking blocks, and the conventional marker using guidance blocks of textured paving blocks) in order to enhance the spatial availability of the whole M-CubITS and the navigation system. Consequently, we show the possibility to advance the WYSIWYAS navigation environments through the performance evaluation and the operation confirmation of the integrated system.

We propose an effective technique for estimation of targets by ground penetrating radar (GPR) using model-based compressive sensing (CS). We demonstrate the technique's performance by applying it to detection of buried landmines. The conventional CS algorithm enables the reconstruction of sparse subsurface images using much reduced measurement by exploiting its sparsity. However, for landmine detection purposes, CS faces some challenges because the landmine is not exactly a point target and also faces high level clutter from the propagation in the medium. By exploiting the physical characteristics of the landmine using model-based CS, the probability of landmine detection can be increased. Using a small pixel size, the landmine reflection in the image is represented by several pixels grouped in a three dimensional plane. This block structure can be used in the model based CS processing for imaging the buried landmine. The evaluation using laboratory data and datasets obtained from an actual mine field in Cambodia shows that the model-based CS gives better reconstruction of landmine images than conventional CS.

Purchase behavior prediction is one of the most important issues for the precision marketing of e-commerce companies. This Letter presents our solution to the purchase behavior prediction problem in E-commerce, specifically the task of Big Data Contest of China Computer Federation in 2014. The goal of this task is to predict which users will have the purchase behavior based on users' historical data. The traditional methods of recommendation encounter two crucial problems in this scenario. First, this task just predicts which users will have the purchase behavior, rather than which items should be recommended to which users. Second, the large-scale dataset poses a big challenge for building the empirical model. Feature engineering and Factorization Model shed some light on these problems. We propose to use Factorization Machines model based on the multiple classes and high dimensions of feature engineering. Experimental results on a real-world dataset demonstrate the advantages of our proposed method.

Since digital hearing aids are sensitive to time delay and power consumption, the computational complexity of noise reduction must be reduced as much as possible. Therefore, some complicated algorithms based on the analysis of the time-frequency domain are very difficult to implement in digital hearing aids. This paper presents a new approach that yields an improved noise reduction algorithm with greatly reduce computational complexity for multi-channel digital hearing aids. First, the sub-band sound pressure level (SPL) is calculated in real time. Then, based on the calculated sub-band SPL, the noise in the sub-band is estimated and the possibility of speech is computed. Finally, a posteriori and a priori signal-to-noise ratios are estimated and the gain function is acquired to reduce the noise adaptively. By replacing the FFT and IFFT transforms by the known SPL, the proposed algorithm greatly reduces the computation loads. Experiments on a prototype digital hearing aid show that the time delay is decreased to nearly half that of the traditional adaptive Wiener filtering and spectral subtraction algorithms, but the SNR improvement and PESQ score are rather satisfied. Compared with modulation frequency-based noise reduction algorithm, which is used in many commercial digital hearing aids, the proposed algorithm achieves not only more than 5dB SNR improvement but also less time delay and power consumption.

In recent years, much work has been devoted to developing protocols and architectures for supporting the growing trend of data-oriented services. One drawback of many of these proposals is the need to upgrade or replace all the routers in order for the new systems to work. Among the few systems that allow for gradual deployment is the recently-proposed Breadcrumbs technique for distributed coordination among caches in a cache network. Breadcrumbs uses information collected locally at each cache during past downloads to support in-network guiding of current requests to desired content. Specifically, during content download a series of short-term pointers, called breadcrumbs, is set up along the download path. Future requests for this content are initially routed towards the server which holds (a copy of) this content. However, if this route leads the request to a Breadcrumbs-supporting router, this router re-directs the request in the direction of the latest downloaded, using the aforementioned pointers. Thus, content requests are initially forwarded by a location ID (e.g., IP address), but encountering a breadcrumb entry can cause a shift over to content-based routing. This property enables the Breadcrumbs system to be deployed gradually, since it only enhances the existing location-based routing mechanism (i.e. IP-based routing). In this paper we evaluate the performance of a network where Breadcrumbs is only partially deployed. Our simulation results show Breadcrumbs performs poorly when sparsely deployed. However, if an overlay of Breadcrumbs-supporting routers is set-up, system performance is greatly improved. We believe that the reduced load on servers achieved with even a limited deployment of Breadcrumbs-supporting routers, combined with the flexibility of being able to deploy the system gradually, should motivate further investigation and eventual deployment of Breadcrumbs. In the paper, we also evaluate more coarse level than router level, i.e. ISP-level Breadcrumbs deployment issues. Our evaluation results show that Higher-layer first deployment approach obtains great improvement caused by Breadcrumbs redirections because of traffic aggregation in higher layer ISP.

We construct the first fully homomorphic encryption (FHE) scheme that encrypts matrices and supports homomorphic matrix addition and multiplication. This is a natural extension of packed FHE and thus supports more complicated homomorphic operations. We optimize the bootstrapping procedure of Alperin-Sheriff and Peikert (CRYPTO 2014) by applying our scheme. Our optimization decreases the lattice approximation factor from Õ(n3) to Õ(n2.5). By taking a lattice dimension as a larger polynomial in a security parameter, we can also obtain the same approximation factor as the best known one of standard lattice-based public-key encryption without successive dimension-modulus reduction, which was essential for achieving the best factor in prior works on bootstrapping of standard lattice-based FHE.

Personal e-healthcare service is growing significantly. A large number of personal e-health measuring and monitoring devices are now in the market. However, to achieve better health outcome, various devices or services need to work together. This coordination among services remains challenge, due to their variations and complexities. To address this issue, we have proposed an ontology-based framework for interactive self-assessment of RESTful e-health services. Unlike existing e-health service frameworks where they had tightly coupling between services, as well as their data schemas were difficult to change and extend in the future. In our work, the loosely coupling among services and flexibility of each service are achieved through the design and implementation based on HYDRA vocabulary and REST principles. We have implemented clinical knowledge through the combination of OWL-DL and SPARQL rules. All of these services evolve independently; their interfaces are based on REST principles, especially HATEOAS constraints. We have demonstrated how to apply our framework for interactive self-assessment in e-health applications. We have shown that it allows the medical knowledge to drive the system workflow according to the event-driven principles. New data schema can be maintained during run-time. This is the essential feature to support arriving of IoT (Internet of Things) based medical devices, which have their own data schema and evolve overtime.

The conventional non-negative matrix factorization (NMF)-based speech enhancement is accomplished by updating iteratively with the prior knowledge of the clean speech and noise spectra bases. With the probabilistic estimation of whether the speech is present or not in a certain frame, this letter proposes a speech enhancement algorithm incorporating the speech presence probability (SPP) obtained via noise estimation to the NMF process. To take advantage of both the NMF-based and statistical model-based approaches, the final enhanced speech is achieved by applying a statistical model-based filter to the output of the SPP weighted NMF. Objective evaluations using perceptual evaluation of speech quality (PESQ) on TIMIT with 20 noise types at various signal-to-noise ratio (SNR) levels demonstrate the superiority of the proposed algorithm over the conventional NMF and statistical model-based baselines.

Camellia is a block cipher jointly developed by Mitsubishi and NTT of Japan. It is designed suitable for both software and hardware implementations. One of the design-for-test techniques using scan chains is called scan-path test, in which testers can observe and control the registers inside the LSI chip directly in order to check if the LSI chip correctly operates or not. Recently, a scan-based side-channel attack is reported which retrieves the secret information from the cryptosystem using scan chains. In this paper, we propose a scan-based attack method on the Camellia cipher using scan signatures. Our proposed method is based on the equivalent transformation of the Camellia algorithm and the possible key candidate reduction in order to retrieve the secret key. Experimental results show that our proposed method sucessfully retrieved its 128-bit secret key using 960 plaintexts even if the scan chain includes the Camellia cipher and other circuits and also sucessfully retrieves its secret key on the SASEBO-GII board, which is a side-channel attack standard evaluation board.