In this work we propose a two-party anonymous authenticated key exchange protocol that provides a communication binding property. The proposed protocol makes use of a compact structure to ensure key exchange and anonymity by adopting an anonymous implicit proof on the possession of a credential. We formally prove that the proposed protocol achieves anonymity, AKE-security, and a communication binding property. The protocol yields short communication messages and runs in two rounds. We show that our protocol is efficient via a comparison analysis with best-known anonymous authenticated key exchange protocols.

This paper reviews several trials of re-designing conventional communication medium, i.e., characters, for enriching their functions by using data-embedding techniques. For example, characters are re-designed to have better machine-readability even under various geometric distortions by embedding a geometric invariant into each character image to represent class label of the character. Another example is to embed various information into handwriting trajectory by using a new pen device, called a data-embedding pen. An experimental result showed that we can embed 32-bit information into a handwritten line of 5 cm length by using the pen device. In addition to those applications, we also discuss the relationship between data-embedding and pattern recognition in a theoretical point of view. Several theories tell that if we have appropriate supplementary information by data-embedding, we can enhance pattern recognition performance up to 100%.

Our society has been getting more privacy-sensitive. Diverse information is given by users to information and communications technology (ICT) systems such as IC cards benefiting them. The information is stored as so-called big data, and there is concern over privacy violation. Visual information such as images and videos is also considered privacy-sensitive. The growing deployment of surveillance cameras and social network services has caused a privacy problem of information given from various sensors. To protect privacy of subjects presented in visual information, their face or figure is processed by means of pixelization or blurring. As image analysis technologies have made considerable progress, many attempts to automatically process flexible privacy protection have been made since 2000, and utilization of privacy information under some restrictions has been taken into account in recent years. This paper addresses the recent progress of privacy protection for visual information, showing our research projects: PriSurv, Digital Diorama (DD), and Mobile Privacy Protection (MPP). Furthermore, we discuss Harmonized Information Field (HIFI) for appropriate utilization of protected privacy information in a specific area.

Password-protected secret sharing (PPSS, for short) schemes were proposed by Bagherzandi, Jarecki, Saxena and Lu. In this paper, we consider another attack for PPSS schemes which is based on public parameters and documents. We show that the protocol proposed by Bagherzandi et al. is broken with the attack. We then propose an enhanced protocol which is secure against the attack.

Program slicing is an important approach for debugging, program comprehension, impact analysis, etc. There are various program slicing techniques ranging from the lightweight to the more accurate but heavyweight. Comparative analyses are important for selecting the most appropriate technique. This paper presents a comparative study of four backward program slicing techniques for Java. The results show the scalability and precision of these techniques. We develop guidelines that indicate which slicing techniques are appropriate for different situations, based on the results.

This paper proposes a new accurate evaluation method for examining the resistance of cryptographic implementations against access-driven cache attacks (CAs). We show that a mathematical correlation method between the sets of measured access time and the ideal data, which depend on the guessed key, can be utilized to evaluate quantitatively the correct key in access-driven CAs. We show the effectiveness of the proposed method using the access time measured in noisy environments. We also estimate the number of key candidates based on mathematical proof while considering memory allocation. Furthermore, based on the proposed method, we analyze quantitatively how the correlation values change with the number of plaintexts for a successful attack.

A multi-port device is characterized using measurement results of a two-port Vector Network Analyzer (VNA) with four different structures. The loads used as terminations are open-, or short-circuited transmission lines (TLs), which are characterized along with Ground-Signal-Ground pads based on L-2L de-embedding method. A new characterization method for a four-port device is introduced along with its theory. The method is validated using simulation and measurement results. The characterized four-port device is a Crossing Transmission Line (CTL), mainly used for over-pass or under-pass of RF signals. Four measurement results are used to characterize the CTL. The S-parameter response of the CTL is found. To compare the results, reconstructed responses compared with the measurements. Results show good agreement between the measured and modeled results from 1 GHz to 110 GHz.

This letter studies the problem of cooperative spectrum sensing in wideband cognitive radio networks. Based on the basis expansion model (BEM), the problem of estimation of power spectral density (PSD) is transformed to estimation of BEM coefficients. The sparsity both in frequency domain and space domain is used to construct a sparse estimation structure. The theory of L1/2 regularization is used to solve the compressed sensing problem. Simulation results demonstrate the effectiveness of the proposed method.

This paper proposes a disaster recovery method for transport networks. In a scenario of recovery from a disaster, a network is repaired through multiple restoration stages because repair resources are limited. In a practical case, a network should provide the reachability of important traffic in transient stages, even as service interruption risks and/or operational overheads caused by transport paths switching are suppressed. Then, we define the multi-objective optimization problem: maximizing the traffic recovery ratio and minimizing the number of switched transport paths at each stage. We formulate our problem as linear programming, and show that it yields pareto-optimal solutions of traffic recovery versus the number of switched paths. We also propose a heuristic algorithm for applying to networks consisting of a few hundred nodes, and show that it can produce sub-optimal solutions that differ only slightly from optimal solutions.

Resonant scattering of flexural waves in acoustic waveguide is analysed by using the recursive transfer method (RTM). Because flexural waves are governed by a fourth-order differential equation, a localized wave tends to be induced around the scattering region and dampening wave tails from the localized wave may reach the ends of a simulation domain. A notable feature of RTM is its ability to extract the localized wave even if the dampening tail reaches the end of the simulation domain. Using RTM, the enhanced reflection caused by a localized wave is predicted and the shape of the localized wave is explored at its resonance with the incident wave.

Cognitive radio has been developed recently as a promising solution to tackle the spectrum related issues such as spectrum scarcity and spectrum underutilization. Cognitive spectrum assignment is necessary for allocating spectrum bands to secondary users in order to avoid conflicts among secondary users and maximize the total network performance under a given set of conditions. In most spectrum assignment schemes, throughput is considered as the main criterion for spectrum selection or spectrum assignment. In this paper, we propose a distortion-aware channel allocation scheme for multiple secondary users who compete for primary channels to transmit multimedia data. In the proposed scheme, idle spectrum bands are assigned to the multimedia secondary users that attain the highest video distortion reduction. The scheme is expected to mitigate the selfish behaviors of users in competing channels. The performance effectiveness of our proposed channel allocation scheme is demonstrated through simulation by comparing with a benchmark of two reference spectrum assignment schemes.

Subcarrier pairing (SP) and power allocation (PA) can improve the channel capacity of the OFDM multi-hop relay system. Due to limitations of processing complexity and energy consumption, symbol-level relaying, which only regenerates the constellation symbols at relay nodes, is more practical than code-level relaying that requires full decoding and encoding. By modeling multi-hop symbol-level relaying as a multi-staged parallel binary symmetric channel, this paper introduces a jointly optimal SP and PA scheme which maximizes the end to end data rate. Analytical arguments are given to reveal the structures and properties of the optimal solution, and simulation results are presented to illustrate and justify the optimality.

Industrial applications such as automotive ones require a cheap communication mechanism to send out communication messages from node to node by their deadline time. This paper presents a design paradigm in which we optimize both assignment of a network node to a bus and slot multiplexing of a FlexRay network system under hard real-time constraints so that we can minimize the cost of wire harness for the FlexRay network system. We present a cost minimization problem as a non-linear model. We developed a network synthesis tool which was based on simulated annealing. Our experimental results show that our design paradigm achieved a 50.0% less cost than a previously proposed approach for a virtual cost model.

The Hierarchical Memory Machine (HMM) is a theoretical parallel computing model that captures the essence of computation on CUDA-enabled GPUs. The offline permutation is a task to copy numbers stored in an array a of size n to an array b of the same size along a permutation P given in advance. A conventional algorithm can complete the offline permutation by executing b[p[i]] ← a[i] for all i in parallel, where an array p stores the permutation P. We first present that the conventional algorithm runs $D_w(P)+2{nover w}+3L-3$ time units using n threads on the HMM with width w and latency L, where Dw(P) is the distribution of P. We next show that important regular permutations including transpose, shuffle, and bit-reversal permutations run $2{nover w}+2{nover kw}+2L-2$ time units on the HMM with k DMMs. We have implemented permutation algorithms for these regular permutations on GeForce GTX 680 GPU. The experimental results show that these algorithms run much faster than the conventional algorithm. We also present an offline permutation algorithm for any permutation running in $16{nover w}+16{nover kw}+16L-16$ time units on the HMM with k DMMs. Quite surprisingly, our offline permutation algorithm on the GPU achieves better performance than the conventional algorithm in random permutation, although the running time has a large constant factor. We can say that the experimental results provide a good example of GPU computation showing that a complicated but ingenious implementation with a larger constant factor in computing time can outperform a much simpler conventional algorithm.

In this paper, a novel high-performance heuristic algorithm, named relay-race algorithm (RRA), which was proposed to approach a global optimal solution by exploring similar local optimal solutions more efficiently within shorter runtime for NP-hard problem is investigated. RRA includes three basic parts: rough search, focusing search and relay. The rough search is designed to get over small hills on the solution space and to approach a local optimal solution as fast as possible. The focusing search is designed to reach the local optimal solution as close as possible. The relay is to escape from the local optimal solution in only one step and to maintain search continuity simultaneously. As one of typical applications, multi-objective placement problem in physical design optimization is solved by the proposed RRA. In experiments, it is confirmed that the computational performance is considerably improved. RRA achieves overall Pareto improvement of two conflicting objectives: power consumption and maximal delay. RRA has its potential applications to improve the existing search methods for more hard problems.

This paper proposes a mixed-grained reconfigurable architecture consisting of fine-grained and coarse-grained fabrics, each of which can be configured for different levels of reliability depending on the reliability requirement of target applications, e.g. mission-critical applications to consumer products. Thanks to the fine-grained fabrics, the architecture can accommodate a state machine, which is indispensable for exploiting C-based behavioral synthesis to trade latency with resource usage through multi-step processing using dynamic reconfiguration. In implementing the architecture, the strategy of dynamic reconfiguration, the assignment of configuration storage and the number of implementable states are key factors that determine the achievable trade-off between used silicon area and latency. We thus split the configuration bits into two classes; state-wise configuration bits and state-invariant configuration bits for minimizing area overhead of configuration bit storage. Through a case study, we experimentally explore the appropriate number of implementable states. A proof-of-concept VLSI chip was fabricated in 65nm process. Measurement results show that applications on the chip can be working in a harsh radiation environment. Irradiation tests also show the correlation between the number of sensitive bits and the mean time to failure. Furthermore, the temporal error rate of an example application due to soft errors in the datapath was measured and demonstrated for reliability-aware mapping.

For compressed sensing, to address problems which do not involve reconstruction, a correlation analysis between measurements and the transform coefficients is proposed. It is shown that there is a linear relationship between them, which indicates that we can abstract the inner property of images directly in the measurement domain.

To achieve more high speed and high quality systems of wireless communications, orthogonal frequency division multiple access (OFDMA) has been proposed. Moreover, OFDMA considering the multiuser diversity (MUDiv) has been also proposed to achieve more high system performance. On the other hand, the conventional MUDiv/OFDMA requires large complexity to select the subcarrier of each user. To solve this problem, we have proposed a MUDiv/OFDMA based on the low granularity block (LGB). However, it degrades the system performance in the environment which contains many deep faded subcarrier channels. Therefore, in this paper, we propose a cooperative LGB-MUDiv/OFDMA to mitigate the influence due to the deep faded subcarrier channel.

Misbehaving nodes intrinsic to the physical vulnerabilities of ad-hoc sensor networks pose a challenging constraint on the designing of data fusion. To address this issue, a statistics-based reputation method for reliable data fusion is proposed in this study. Different from traditional reputation methods that only compute the general reputation of a node, the proposed method modeled by negative binomial reputation consists of two separated reputation metrics: fusion reputation and sensing reputation. Fusion reputation aims to select data fusion points and sensing reputation is used to weigh the data reported by sensor nodes to the fusion point. So, this method can prevent a compromised node from covering its misbehavior in the process of sensing or fusion by behaving well in the fusion or sensing. To tackle the unexpected facts such as packet loss, a discounting factor is introduced into the proposed method. Additionally, Local Outlier Factor (LOF) based outlier detection is applied to evaluate the behavior result of sensor nodes. Simulations show that the proposed method can enhance the reliability of data fusion and is more accurate than the general reputation method when applied in reputation evaluation.

In this paper, we propose a new structure for a compact matched filter bank for a mutually orthogonal zero-correlation zone (MO-ZCZ) sequence set consisting of ternary sequence pairs obtained by Hadamard and binary ZCZ sequence sets; this construction reduces the number of two-input adders and delay elements. The matched filter banks are implemented on a field-programmable gate array (FPGA) with 51,840 logic elements (LEs). The proposed matched filter bank for an MO-ZCZ sequence set of length 160 can be constructed by a circuit size that is about 8.6% that of a conventional matched filter bank.