By exploiting the reciprocity and randomness properties of wireless channels, physical-layer-based key generation provides a stable secrecy channel even when the main channel suffers from a bad condition. Even though the channel variation due to the mobility of nodes in wireless channels provides an improvement of key generation rate (KGR), it decreases the key consistency probability (KCP) between the node pairs. Inspired by the received signal strength(RSS)-angle of arrival(AoA)-based geolocation research, in this work, we analyze the performance of the key extraction using the RSS and AoA. We aim to identify a way to utilize the high KGR of the AoA-based method to overcome the major drawback of having a low KGR in the most common RSS-based scheme. Specifically, we derive the KCP and KGR of the RSS-AoA-based key generation scheme. Further, we propose a new performance metric called effective key generation rate (EKGR), to evaluate the designed key generation scheme in practical scenarios. Finally, we provide numerical results to verify the accuracy of the presented theoretical analysis.

With the increasing demand of Internet-of-Things applicability in various devices and location-based services (LBSs) with positioning capabilities, we proposed simple and effective post-processing techniques to reduce positioning error and provide more precise navigation to users in a pedestrian environment in this letter. The proposed positioning error reduction techniques (Technique 1-minimum range securement and bounce elimination, Technique 2-direction vector-based error correction) were studied considering low complexity and wide applicability to various types of positioning systems, e.g., global positioning system (GPS). Through the real field tests in urban areas, we have verified that an average positioning error of the proposed techniques is significantly decreased compared to that of a GPS-only environment.

A novel element is proposed for manipulating two orthogonally-polarized electromagnetic waves, resulting in a polarization-reconfigurable flat transmitarray. This element consists of four identical metallic patterns, including a square frame loaded with short stubs and an internal crossed dipole, which are printed on the two sides of three identical flat dielectric slabs, with no air gap among them. With a linearly-polarized (LP) feeder, the flat transmitarray can transform the LP incident wave into a circular, horizontal or vertical polarization wave in a convenient way. By rotating the LP feeder so that the polarization angle is 0°, 45°, 90° or 135°, the waves of linear horizontal, right-handed circular, linear vertical or left-handed circular polarization can be obtained alternately. Simulations and experiments are conducted to validate the performance. The measured axial ratio bandwidths for RHCP and LHCP transmitarrays are about 7.1% and 5.1%, respectively, the 3dB gain bandwidths are 16.19% and 22.4%, and the peak gains are 25.56dBi and 24.2dBi, respectively.

In this paper, we propose a design method of compact multi-way Wilkinson power divider with a multiband operation for size reduction and band broadening. The proposed divider consists of multisection LC-ladder circuits in the division arms and isolation circuits between the output ports. To validate design procedures, we fabricated a trial divider at VHF band. The circuit layout of the trial divider was decided by using an electromagnetic simulator (Sonnet EM). Because the proposed divider consists of lumped element circuits, we can realize great miniaturization of a circuit area compared to that of the conventional Wilkinson power divider. The circuit size of the trial divider is 35 mm square. The measurement results for the trial divider by using a vector network analyzer indicates a relative bandwidth of about 60% under -17 dB reflection, flat power division within ±0.1 dB, and very low phase imbalances under 1.0 degree over the wide frequency range.

Improving energy efficiency is critical for embedded systems in our rapidly evolving information society. Near real-time data processing tasks, such as multimedia streaming applications, exhibit a common fact that their deadline periods are longer than their input intervals due to buffering. In general, executing tasks at lower performance is more energy efficient. On the other hand, higher performance is necessary for huge tasks to meet their deadlines. To minimize the energy consumption while meeting deadlines strictly, adaptive task scheduling including dynamic performance mode selection is very important. In this work, we propose an energy efficient slack-based task scheduling algorithm for such tasks by adapting to task size variations and applying DVFS with the help of statistical analysis. We confirmed that our proposal can further reduce the energy consumption when compared to oracle frame-based scheduling.

This paper presents a low-latency, low-cost architecture for computing square and cube roots in the fixed-point format. The proposed architecture is designed based on a non-iterative root calculation scheme to achieve fast computations. While previous non-iterative root calculators are restricted to a square-root operation due to the limitation of their mathematical property, the root computation is generalized in this paper to apply an approximation method to the non-iterative scheme. On top of that, a recurrent method is proposed to select parameters, which enables us to reduce the table size while keeping the maximum relative error value low. Consequently, the proposed root calculator can support both square and cube roots at the expense of small delay and low area overheads. This extension can be generalized to compute the nth roots, where n is a positive integer.

In our previous work, we introduced new concepts of secure scan design; shift register equivalent circuits (SR-equivalents, for short) and strongly secure circuits, and also introduced generalized shift registers (GSRs, for short) to apply them to secure scan design. In this paper, we combine both concepts of SR-equivalents and strongly secure circuits and apply them to GSRs, and consider the synthesis problem of strongly secure SR-equivalents using GSRs. We also consider the enumeration problem of GSRs that are strongly secure and SR-equivalent, i.e., the cardinality of the class of strongly secure SR-equivalent GSRs to clarify the security level of the secure scan architecture.

This paper proposes a read-only memory driving circuit for RFID tags based on a-IGZO thin-film transistors. The circuit consists of a Johnson counter and monotype complementary gates. By utilizing complementary signals to drive a decoder based on monotype complementary gates, the propagation delay can be decreased and the redundant current can be reduced. The Johnson counter reduces the number of registers. The new circuit can effectively avoid glitch generation, and reduce circuit power consumption and delay.

Cayley hash functions are a family of cryptographic hash functions constructed from Cayley graphs, with appealing properties such as a natural parallelism and a security reduction to a clean, well-defined mathematical problem. As this problem involves non-Abelian groups, it is a priori resistant to quantum period finding algorithms and Cayley hash functions may therefore be a good foundation for post-quantum cryptography. Four particular parameter sets for Cayley hash functions have been proposed in the past, and so far dedicated preimage algorithms have been found for all of them. These algorithms do however not seem to extend to generic parameters, and as a result it is still an open problem to determine the security of Cayley hash functions in general. In this paper, we study the case of Chiu's Ramanujan graphs. We design a polynomial time preimage attack against the resulting Cayley hash function, showing that these particular parameters like the previous ones are not suitable for the construction. We extend our attacks on hash functions based on similar Cayley graphs as Chiu's Ramanujan graphs. On the positive side, we then suggest some possible ways to construct the Cayley hashes that may not be affected by this type of attacks. Our results contribute to a better understanding of the hard problems underlying the security of Cayley hash functions.

At the present time, as downsizing of connectors causes thin gold plated layer and low contact load, serious problem of degradation of contact resistance property is induced. For these contacts, corrosion of the contacts surface under environment and high temperature as soldering and reflow process should be existed. Oxidation of base metal atoms which are diffused from under layer and additives occurs. Contact resistance increases for both surface contamination and low contact load. In order to resolve these problems and wear of surface, application of contact lubricants is useful and effective. However, degradation of the lubricants under such reflow process as high temperature possibly occurs. Therefore, in this study, from view point of change of lubricant quality as viscosity, weight loss, polymerization, oxidation and molecular orientation were clarified. For increase in contact resistance, orientation of lubricant molecular acts as important factor was found. The other factors of the lubricant hardly does not effect on contact resistance.

While conventional studies on real-time systems have mostly considered the real-time constraint of real-time systems only, recent research initiatives are trying to incorporate a security constraint into real-time scheduling due to the recognition that the violation of either of two constrains can cause catastrophic losses for humans, the system, and even environment. The focus of most studies, however, is the single-criticality systems, while the security of mixed-criticality systems has received scant attention, even though security is also a critical issue for the design of mixed-criticality systems. In this paper, we address the problem of the information leakage that arises from the shared resources that are used by tasks with different security-levels of mixed-criticality systems. We define a new concept of the security constraint employing a pre-flushing mechanism to cleanse the state of shared resources whenever there is a possibility of the information leakage regarding it. Then, we propose a new non-preemptive real-time scheduling algorithm and a schedulability analysis, which incorporate the security constraint for mixed-criticality systems. Our evaluation demonstrated that a large number of real-time tasks can be scheduled without a significant performance loss under a new security constraint.

With the in-depth development of service computing, it has become clear that when constructing service applications in an open dynamic network environment, greater attention must be paid to trustworthiness under the premise of functions' realization. Trustworthy computing requires theories for business process modeling in terms of both behavior and trustworthiness. In this paper, a calculus for ensuring the satisfaction of trustworthiness requirements in service-oriented systems is proposed. We investigate a calculus called QPi, for representing both the behavior and the trustworthiness property of concurrent systems. QPi is the combination of pi-calculus and a constraint semiring, which has a feature when problems with multi-dimensional properties must be tackled. The concept of the quantified bisimulation of processes provides us a measure of the degree of equivalence of processes based on the bisimulation distance. The QPi related properties of bisimulation and bisimilarity are also discussed. A specific modeling example is given to illustrate the effectiveness of the algebraic method.

Aiming at detecting pronunciation errors produced by second language learners and providing corrective feedbacks related with articulation, we address effective articulatory models based on deep neural network (DNN). Articulatory attributes are defined for manner and place of articulation. In order to efficiently train these models of non-native speech without such data, which is difficult to collect in a large scale, several transfer learning based modeling methods are explored. We first investigate three closely-related secondary tasks which aim at effective learning of DNN articulatory models. We also propose to exploit large speech corpora of native and target language to model inter-language phenomena. This kind of transfer learning can provide a better feature representation of non-native speech. Related task transfer and language transfer learning are further combined on the network level. Compared with the conventional DNN which is used as the baseline, all proposed methods improved the performance. In the native attribute recognition task, the network-level combination method reduced the recognition error rate by more than 10% relative for all articulatory attributes. The method was also applied to pronunciation error detection in Mandarin Chinese pronunciation learning by Japanese native speakers, and achieved the relative improvement up to 17.0% for detection accuracy and up to 19.9% for F-score, which is also better than the lattice-based combination.

Structured signatures are digital signatures where relationship between signers is guaranteed in addition to the validity of individually generated data for each signer, and have been expected for the digital right management. Nevertheless, we mention that there is no scheme with a tight security reduction, to the best of our knowledge. Loosely speaking, it means that the security is downgraded against an adversary who obtains a large amount of signatures. Since contents are widely utilized in general, achieving a tighter reduction is desirable. Based on this background, we propose the first structured signature scheme with a tight security reduction in the conventional public key cryptography and the one with a rigorous reduction proof in the ID-based cryptography via our new proof method. Moreover, the security of our schemes can be proven under the CDH assumption which is the most standard. Our schemes are also based on bilinear maps whose implementation can be provided via well-known cryptographic libraries.

In a speech enhancement system for impact noise, it is important for any impact noise activity to be detected. However, because impact noise occurs suddenly, it is not always easy to detect. We propose a method for impact noise activity detection based on the kurtosis of an instantaneous power spectrum. The continuous duration of a generalized impact noise is shorter than that of speech, and the power of such impact noise varies dramatically. Consequently, the distribution of the instantaneous power spectrum of impact noise is different from that of speech. The proposed detection takes advantage of kurtosis, which depends on the sharpness and skirt of the distribution. Simulation results show that the proposed noise activity detection improves the performance of the speech enhancement system.

In both theoretical analysis and practical use for an antidictionary coding algorithm, an important problem is how to encode an antidictionary of an input source. This paper presents a proposal for a compact tree representation of an antidictionary built from a circular string for an input source. We use a technique for encoding a tree in the compression via substring enumeration to encode a tree representation of the antidictionary. Moreover, we propose a new two-pass universal antidictionary coding algorithm by means of the proposal tree representation. We prove that the proposed algorithm is asymptotic optimal for a stationary ergodic source.

Scalar multiplication over higher degree rational point groups is often regarded as the bottleneck for faster pairing based cryptography. This paper has presented a skew Frobenius mapping technique in the sub-field isomorphic sextic twisted curve of Kachisa-Schaefer-Scott (KSS) pairing friendly curve of embedding degree 18 in the context of Ate based pairing. Utilizing the skew Frobenius map along with multi-scalar multiplication procedure, an efficient scalar multiplication method for KSS curve is proposed in the paper. In addition to the theoretic proposal, this paper has also presented a comparative simulation of the proposed approach with plain binary method, sliding window method and non-adjacent form (NAF) for scalar multiplication. The simulation shows that the proposed method is about 60 times faster than plain implementation of other compared methods.

Identity-based encryption (IBE) is an advanced form of public key encryption and one of the most important cryptographic primitives. Of the many constructions of IBE schemes, the one proposed by Boneh and Boyen (in Eurocrypt 2004) is quite important from both practical and theoretical points of view. The scheme was standardized as IEEE P1363.3 and is the basis for many subsequent constructions. In this paper, we investigate its multi-challenge security, which means that an adversary is allowed to query challenge ciphertexts multiple times rather than only once. Since single-challenge security implies multi-challenge security, and since Boneh and Boyen provided a security proof for the scheme in the single-challenge setting, the scheme is also secure in the multi-challenge setting. However, this reduction results in a large security loss. Instead, we give tight security reduction for the scheme in the multi-challenge setting. Our reduction is tight even if the number of challenge queries is not fixed in advance (that is, the queries are unbounded). Unfortunately, we are only able to prove the security in a selective setting and rely on a non-standard parameterized assumption. Nevertheless, we believe that our new security proof is of interest and provides new insight into the security of the Boneh-Boyen IBE scheme.

Conventional feature-rich parsers based on manually tuned features have achieved state-of-the-art performance. However, these parsers are not good at handling long-term dependencies using only the clues captured by a prepared feature template. On the other hand, recurrent neural network (RNN)-based parsers can encode unbounded history information effectively, but they perform not well for small tree structures, especially when low-frequency words are involved, and they cannot use prior linguistic knowledge. In this paper, we propose a simple but effective framework to combine the merits of feature-rich transition-based parsers and RNNs. Specifically, the proposed framework incorporates RNN-based scores into the feature template used by a feature-rich parser. On English WSJ treebank and SPMRL 2014 German treebank, our framework achieves state-of-the-art performance (91.56 F-score for English and 83.06 F-score for German), without requiring any additional unlabeled data.

In this paper, we propose a novel gate delay time mismatch tolerant time-mode signal accumulator whose input and output are represented by a time difference of two digital signal transitions. Within the proposed accumulator, the accumulated value is stored as the time difference between the two pulses running around the same ring of a delay line, so that there is no mismatch between the periods of the two pulses, thus the output drift of the accumulator is suppressed in principle without calibrating mismatch of two rings, which is used to store the accumulated value in the conventional one. A prototype of the proposed accumulator was fabricated in 180nm CMOS. The accumulating operation is confirmed by both time and frequency domain experiments. The standard deviation of the error of the accumulating operation is 9.8ps, and compared with the previous work, the peak error over full-scale is reduced by 46% without calibrating the output drift.