著者
Asuka NAKAJIMA Takuya WATANABE Eitaro SHIOJI Mitsuaki AKIYAMA Maverick WOO
出版者
The Institute of Electronics, Information and Communication Engineers
雑誌
IEICE Transactions on Information and Systems (ISSN:09168532)
巻号頁・発行日
vol.E103.D, no.7, pp.1524-1540, 2020-07-01 (Released:2020-07-01)
参考文献数
40

With our ever increasing dependence on computers, many governments around the world have started to investigate strengthening the regulations on vulnerabilities and their lifecycle management. Although many previous works have studied this problem space for mainstream software packages and web applications, relatively few have studied this for consumer IoT devices. As our first step towards filling this void, this paper presents a pilot study on the vulnerability disclosures and patch releases of three prominent consumer IoT vendors in Japan and three in the United States. Our goals include (i) characterizing the trends and risks in the vulnerability lifecycle management of consumer IoT devices using accurate long-term data, and (ii) identifying problems, challenges, and potential approaches for future studies of this problem space. To this end, we collected all published vulnerabilities and patches related to the consumer IoT products by the included vendors between 2006 and 2017; then, we analyzed our dataset from multiple perspectives, such as the severity of the included vulnerabilities and the timing of the included patch releases with respect to the corresponding disclosures and exploits. Our work has uncovered several important findings that may inform future studies. These findings include (i) a stark contrast between how the vulnerabilities in our dataset were disclosed in the two markets, (ii) three alarming practices by the included vendors that may significantly increase the risk of 1-day exploits for customers, and (iii) challenges in data collection including crawling automation and long-term data availability. For each finding, we also provide discussions on its consequences and/or potential migrations or suggestions.
著者
Daiki CHIBA Ayako AKIYAMA HASEGAWA Takashi KOIDE Yuta SAWABE Shigeki GOTO Mitsuaki AKIYAMA
出版者
The Institute of Electronics, Information and Communication Engineers
雑誌
IEICE Transactions on Information and Systems (ISSN:09168532)
巻号頁・発行日
vol.E103.D, no.7, pp.1493-1511, 2020-07-01 (Released:2020-07-01)
参考文献数
70

Internationalized domain names (IDNs) are abused to create domain names that are visually similar to those of legitimate/popular brands. In this work, we systematize such domain names, which we call deceptive IDNs, and analyze the risks associated with them. In particular, we propose a new system called DomainScouter to detect various deceptive IDNs and calculate a deceptive IDN score, a new metric indicating the number of users that are likely to be misled by a deceptive IDN. We perform a comprehensive measurement study on the identified deceptive IDNs using over 4.4 million registered IDNs under 570 top-level domains (TLDs). The measurement results demonstrate that there are many previously unexplored deceptive IDNs targeting non-English brands or combining other domain squatting methods. Furthermore, we conduct online surveys to examine and highlight vulnerabilities in user perceptions when encountering such IDNs. Finally, we discuss the practical countermeasures that stakeholders can take against deceptive IDNs.
著者
Daisuke OKU Kotaro TERADA Masato HAYASHI Masanao YAMAOKA Shu TANAKA Nozomu TOGAWA
出版者
The Institute of Electronics, Information and Communication Engineers
雑誌
IEICE TRANSACTIONS on Information and Systems (ISSN:09168532)
巻号頁・発行日
vol.E102-D, no.9, pp.1696-1706, 2019-09-01
被引用文献数
2

Combinatorial optimization problems with a large solution space are difficult to solve just using von Neumann computers. Ising machines or annealing machines have been developed to tackle these problems as a promising Non-von Neumann computer. In order to use these annealing machines, every combinatorial optimization problem is mapped onto the physical Ising model, which consists of spins, interactions between them, and their external magnetic fields. Then the annealing machines operate so as to search the ground state of the physical Ising model, which corresponds to the optimal solution of the original combinatorial optimization problem. A combinatorial optimization problem can be firstly described by an ideal fully-connected Ising model but it is very hard to embed it onto the physical Ising model topology of a particular annealing machine, which causes one of the largest issues in annealing machines. In this paper, we propose a fully-connected Ising model embedding method targeting for CMOS annealing machine. The key idea is that the proposed method replicates every logical spin in a fully-connected Ising model and embeds each logical spin onto the physical spins with the same chain length. Experimental results through an actual combinatorial problem show that the proposed method obtains spin embeddings superior to the conventional de facto standard method, in terms of the embedding time and the probability of obtaining a feasible solution.
著者
Graham NEUBIG Masato MIMURA Shinsuke MORI Tatsuya KAWAHARA
出版者
一般社団法人 電子情報通信学会
雑誌
IEICE Transactions on Information and Systems (ISSN:09168532)
巻号頁・発行日
vol.E95.D, no.2, pp.614-625, 2012-02-01 (Released:2012-02-01)
参考文献数
40
被引用文献数
6 16 6

We propose a novel scheme to learn a language model (LM) for automatic speech recognition (ASR) directly from continuous speech. In the proposed method, we first generate phoneme lattices using an acoustic model with no linguistic constraints, then perform training over these phoneme lattices, simultaneously learning both lexical units and an LM. As a statistical framework for this learning problem, we use non-parametric Bayesian statistics, which make it possible to balance the learned model's complexity (such as the size of the learned vocabulary) and expressive power, and provide a principled learning algorithm through the use of Gibbs sampling. Implementation is performed using weighted finite state transducers (WFSTs), which allow for the simple handling of lattice input. Experimental results on natural, adult-directed speech demonstrate that LMs built using only continuous speech are able to significantly reduce ASR phoneme error rates. The proposed technique of joint Bayesian learning of lexical units and an LM over lattices is shown to significantly contribute to this improvement.
著者
Kei SAWADA Akira TAMAMORI Kei HASHIMOTO Yoshihiko NANKAKU Keiichi TOKUDA
出版者
The Institute of Electronics, Information and Communication Engineers
雑誌
IEICE TRANSACTIONS on Information and Systems (ISSN:09168532)
巻号頁・発行日
vol.E99-D, no.12, pp.3119-3131, 2016-12-01

This paper proposes a Bayesian approach to image recognition based on separable lattice hidden Markov models (SL-HMMs). The geometric variations of the object to be recognized, e.g., size, location, and rotation, are an essential problem in image recognition. SL-HMMs, which have been proposed to reduce the effect of geometric variations, can perform elastic matching both horizontally and vertically. This makes it possible to model not only invariances to the size and location of the object but also nonlinear warping in both dimensions. The maximum likelihood (ML) method has been used in training SL-HMMs. However, in some image recognition tasks, it is difficult to acquire sufficient training data, and the ML method suffers from the over-fitting problem when there is insufficient training data. This study aims to accurately estimate SL-HMMs using the maximum a posteriori (MAP) and variational Bayesian (VB) methods. The MAP and VB methods can utilize prior distributions representing useful prior information, and the VB method is expected to obtain high generalization ability by marginalization of model parameters. Furthermore, to overcome the local maximum problem in the MAP and VB methods, the deterministic annealing expectation maximization algorithm is applied for training SL-HMMs. Face recognition experiments performed on the XM2VTS database indicated that the proposed method offers significantly improved image recognition performance. Additionally, comparative experiment results showed that the proposed method was more robust to geometric variations than convolutional neural networks.
著者
Kazuhiro NAKAMURA Kei HASHIMOTO Yoshihiko NANKAKU Keiichi TOKUDA
出版者
The Institute of Electronics, Information and Communication Engineers
雑誌
IEICE TRANSACTIONS on Information and Systems (ISSN:09168532)
巻号頁・発行日
vol.E97-D, no.6, pp.1438-1448, 2014-06-01

This paper proposes a novel approach for integrating spectral feature extraction and acoustic modeling in hidden Markov model (HMM) based speech synthesis. The statistical modeling process of speech waveforms is typically divided into two component modules: the frame-by-frame feature extraction module and the acoustic modeling module. In the feature extraction module, the statistical mel-cepstral analysis technique has been used and the objective function is the likelihood of mel-cepstral coefficients for given speech waveforms. In the acoustic modeling module, the objective function is the likelihood of model parameters for given mel-cepstral coefficients. It is important to improve the performance of each component module for achieving higher quality synthesized speech. However, the final objective of speech synthesis systems is to generate natural speech waveforms from given texts, and the improvement of each component module does not always lead to the improvement of the quality of synthesized speech. Therefore, ideally all objective functions should be optimized based on an integrated criterion which well represents subjective speech quality of human perception. In this paper, we propose an approach to model speech waveforms directly and optimize the final objective function. Experimental results show that the proposed method outperformed the conventional methods in objective and subjective measures.
著者
Tomo NIIZUMA Hideaki GOTO
出版者
一般社団法人 電子情報通信学会
雑誌
IEICE Transactions on Information and Systems (ISSN:09168532)
巻号頁・発行日
vol.E100.D, no.3, pp.511-519, 2017-03-01 (Released:2017-03-01)
参考文献数
24
被引用文献数
3

Wireless LAN (WLAN) roaming systems, such as eduroam, enable the mutual use of WLAN facilities among multiple organizations. As a consequence of the strong demand for WLAN roaming, it is utilized not only at universities and schools but also at the venues of large events such as concerts, conferences, and sports events. Moreover, it has also been reported that WLAN roaming is useful in areas afflicted by natural disasters. This paper presents a novel WLAN roaming system over Wireless Mesh Networks (WMNs) that is useful for the use cases shown above. The proposed system is based on two methods as follows: 1) Automatic authentication path generation method decreases the WLAN roaming system deployment costs including the wiring cost and configuration cost. Although the wiring cost can be reduced by using WMN technologies, some additional configurations are still required if we want to deploy a secure user authentication mechanism (e.g. IEEE 802.1X) on WLAN systems. In the proposed system, the Access Points (APs) can act as authenticators automatically using RadSec instead of RADIUS. Therefore, the network administrators can deploy 802.1X-based authentication systems over WMNs without additional configurations on-site. 2) Local authentication method makes the system deployable in times of natural disasters, in particular when the upper network is unavailable or some authentication servers or proxies are down. In the local authentication method, users and APs can be authenticated at the WMN by locally verifying the digital certificates as the authentication credentials.
著者
Pilsung KANG
出版者
The Institute of Electronics, Information and Communication Engineers
雑誌
IEICE Transactions on Information and Systems (ISSN:09168532)
巻号頁・発行日
vol.E102.D, no.8, pp.1565-1568, 2019-08-01 (Released:2019-08-01)
参考文献数
15
被引用文献数
1

We present an OpenACC-based parallelization implementation of stochastic algorithms for simulating biochemical reaction networks on modern GPUs (graphics processing units). To investigate the effectiveness of using OpenACC for leveraging the massive hardware parallelism of the GPU architecture, we carefully apply OpenACC's language constructs and mechanisms to implementing a parallel version of stochastic simulation algorithms on the GPU. Using our OpenACC implementation in comparison to both the NVidia CUDA and the CPU-based implementations, we report our initial experiences on OpenACC's performance and programming productivity in the context of GPU-accelerated scientific computing.
著者
POLIKOVSKY Senya KAMEDA Yoshinari OHTA Yuichi
出版者
電子情報通信学会
雑誌
IEICE transactions on information and systems (ISSN:09168532)
巻号頁・発行日
vol.E96.D, no.1, pp.81-92, 2013-01
被引用文献数
20 1

Facial micro-expressions are fast and subtle facial motions that are considered as one of the most useful external signs for detecting hidden emotional changes in a person. However, they are not easy to detect and measure as they appear only for a short time, with small muscle contraction in the facial areas where salient features are not available. We propose a new computer vision method for detecting and measuring timing characteristics of facial micro-expressions. The core of this method is based on a descriptor that combines pre-processing masks, histograms and concatenation of spatial-temporal gradient vectors. Presented 3D gradient histogram descriptor is able to detect and measure the timing characteristics of the fast and subtle changes of the facial skin surface. This method is specifically designed for analysis of videos recorded using a hi-speed 200fps camera. Final classification of micro expressions is done by using a k-mean classifier and a voting procedure. The Facial Action Coding System was utilized to annotate the appearance and dynamics of the expressions in our new hi-speed micro-expressions video database. The efficiency of the proposed approach was validated using our new hi-speed video database.
著者
Takashi NOSE Yuhei OTA Takao KOBAYASHI
出版者
The Institute of Electronics, Information and Communication Engineers
雑誌
IEICE TRANSACTIONS on Information and Systems (ISSN:09168532)
巻号頁・発行日
vol.E93-D, no.9, pp.2483-2490, 2010-09-01
被引用文献数
9

We propose a segment-based voice conversion technique using hidden Markov model (HMM)-based speech synthesis with nonparallel training data. In the proposed technique, the phoneme information with durations and a quantized F0 contour are extracted from the input speech of a source speaker, and are transmitted to a synthesis part. In the synthesis part, the quantized F0 symbols are used as prosodic context. A phonetically and prosodically context-dependent label sequence is generated from the transmitted phoneme and the F0 symbols. Then, converted speech is generated from the label sequence with durations using the target speaker's pre-trained context-dependent HMMs. In the model training, the models of the source and target speakers can be trained separately, hence there is no need to prepare parallel speech data of the source and target speakers. Objective and subjective experimental results show that the segment-based voice conversion with phonetic and prosodic contexts works effectively even if the parallel speech data is not available.
著者
Yuki SAITO Kei AKUZAWA Kentaro TACHIBANA
出版者
The Institute of Electronics, Information and Communication Engineers
雑誌
IEICE TRANSACTIONS on Information and Systems (ISSN:09168532)
巻号頁・発行日
vol.E103-D, no.9, pp.1978-1987, 2020-09-01

This paper presents a method for many-to-one voice conversion using phonetic posteriorgrams (PPGs) based on an adversarial training of deep neural networks (DNNs). A conventional method for many-to-one VC can learn a mapping function from input acoustic features to target acoustic features through separately trained DNN-based speech recognition and synthesis models. However, 1) the differences among speakers observed in PPGs and 2) an over-smoothing effect of generated acoustic features degrade the converted speech quality. Our method performs a domain-adversarial training of the recognition model for reducing the PPG differences. In addition, it incorporates a generative adversarial network into the training of the synthesis model for alleviating the over-smoothing effect. Unlike the conventional method, ours jointly trains the recognition and synthesis models so that they are optimized for many-to-one VC. Experimental evaluation demonstrates that the proposed method significantly improves the converted speech quality compared with conventional VC methods.
著者
Tadachika OKI Satoshi TAOKA Toshiya MASHIMA Toshimasa WATANABE
出版者
一般社団法人 電子情報通信学会
雑誌
IEICE Transactions on Information and Systems (ISSN:09168532)
巻号頁・発行日
vol.E95.D, no.3, pp.769-777, 2012-03-01 (Released:2012-03-01)
参考文献数
15
被引用文献数
1

The k-edge-connectivity augmentation problem with bipartition constraints (kECABP, for short) is defined by “Given an undirected graph G=(V,E) and a bipartition π={VB,VW} of V with VB∩VW=∅, find an edge set Ef of minimum cardinality, consisting of edges that connect VB and VW, such that G'=(V,E∪Ef) is k-edge-connected.” The problem has applications for security of statistical data stored in a cross tabulated table, and so on. In this paper we propose a fast algorithm for finding an optimal solution to (σ+1)ECABP in O(|V||E|+|V2|log |V|) time when G is σ-edge-connected (σ > 0), and show that the problem can be solved in linear time if σ ∈ {1,2}.
著者
Hiroki TAMARU Yuki SAITO Shinnosuke TAKAMICHI Tomoki KORIYAMA Hiroshi SARUWATARI
出版者
The Institute of Electronics, Information and Communication Engineers
雑誌
IEICE Transactions on Information and Systems (ISSN:09168532)
巻号頁・発行日
vol.E103.D, no.3, pp.639-647, 2020-03-01 (Released:2020-03-01)
参考文献数
32

This paper proposes a generative moment matching network (GMMN)-based post-filtering method for providing inter-utterance pitch variation to singing voices and discusses its application to our developed mixing method called neural double-tracking (NDT). When a human singer sings and records the same song twice, there is a difference between the two recordings. The difference, which is called inter-utterance variation, enriches the performer's musical expression and the audience's experience. For example, it makes every concert special because it never recurs in exactly the same manner. Inter-utterance variation enables a mixing method called double-tracking (DT). With DT, the same phrase is recorded twice, then the two recordings are mixed to give richness to singing voices. However, in synthesized singing voices, which are commonly used to create music, there is no inter-utterance variation because the synthesis process is deterministic. There is also no inter-utterance variation when only one voice is recorded. Although there is a signal processing-based method called artificial DT (ADT) to layer singing voices, the signal processing results in unnatural sound artifacts. To solve these problems, we propose a post-filtering method for randomly modulating synthesized or natural singing voices as if the singer sang again. The post-filter built with our method models the inter-utterance pitch variation of human singing voices using a conditional GMMN. Evaluation results indicate that 1) the proposed method provides perceptible and natural inter-utterance variation to synthesized singing voices and that 2) our NDT exhibits higher double-trackedness than ADT when applied to both synthesized and natural singing voices.
著者
Sho ENDO Jun SONODA Motoyuki SATO Takafumi AOKI
出版者
The Institute of Electronics, Information and Communication Engineers
雑誌
IEICE TRANSACTIONS on Information and Systems (ISSN:09168532)
巻号頁・発行日
vol.E94-D, no.12, pp.2338-2344, 2011-12-01

Finite difference time domain (FDTD) method has been accelerated on the Cell Broadband Engine (Cell B.E.). However the problem has arisen that speedup is limited by the bandwidth of the main memory on large-scale analysis. As described in this paper, we propose a novel algorithm and implement FDTD using it. We compared the novel algorithm with results obtained using region segmentation, thereby demonstrating that the proposed algorithm has shorter calculation time than that provided by region segmentation.
著者
Mohammed Salah AL-RADHI Tamás Gábor CSAPÓ Géza NÉMETH
出版者
The Institute of Electronics, Information and Communication Engineers
雑誌
IEICE Transactions on Information and Systems (ISSN:09168532)
巻号頁・発行日
vol.E103.D, no.5, pp.1099-1107, 2020-05-01 (Released:2020-05-01)
参考文献数
36

In this article, we propose a method called “continuous noise masking (cNM)” that allows eliminating residual buzziness in a continuous vocoder, i.e. of which all parameters are continuous and offers a simple and flexible speech analysis and synthesis system. Traditional parametric vocoders generally show a perceptible deterioration in the quality of the synthesized speech due to different processing algorithms. Furthermore, an inaccurate noise resynthesis (e.g. in breathiness or hoarseness) is also considered to be one of the main underlying causes of performance degradation, leading to noisy transients and temporal discontinuity in the synthesized speech. To overcome these issues, a new cNM is developed based on the phase distortion deviation in order to reduce the perceptual effect of the residual noise, allowing a proper reconstruction of noise characteristics, and model better the creaky voice segments that may happen in natural speech. To this end, the cNM is designed to keep only voice components under a condition of the cNM threshold while discarding others. We evaluate the proposed approach and compare with state-of-the-art vocoders using objective and subjective listening tests. Experimental results show that the proposed method can reduce the effect of residual noise and can reach the quality of other sophisticated approaches like STRAIGHT and log domain pulse model (PML).
著者
Yuki SAITO Kei AKUZAWA Kentaro TACHIBANA
出版者
The Institute of Electronics, Information and Communication Engineers
雑誌
IEICE Transactions on Information and Systems (ISSN:09168532)
巻号頁・発行日
vol.E103.D, no.9, pp.1978-1987, 2020-09-01 (Released:2020-09-01)
参考文献数
53

This paper presents a method for many-to-one voice conversion using phonetic posteriorgrams (PPGs) based on an adversarial training of deep neural networks (DNNs). A conventional method for many-to-one VC can learn a mapping function from input acoustic features to target acoustic features through separately trained DNN-based speech recognition and synthesis models. However, 1) the differences among speakers observed in PPGs and 2) an over-smoothing effect of generated acoustic features degrade the converted speech quality. Our method performs a domain-adversarial training of the recognition model for reducing the PPG differences. In addition, it incorporates a generative adversarial network into the training of the synthesis model for alleviating the over-smoothing effect. Unlike the conventional method, ours jointly trains the recognition and synthesis models so that they are optimized for many-to-one VC. Experimental evaluation demonstrates that the proposed method significantly improves the converted speech quality compared with conventional VC methods.
著者
Yuki SAITO Shinnosuke TAKAMICHI Hiroshi SARUWATARI
出版者
一般社団法人 電子情報通信学会
雑誌
IEICE Transactions on Information and Systems (ISSN:09168532)
巻号頁・発行日
vol.E100.D, no.8, pp.1925-1928, 2017-08-01 (Released:2017-08-01)
参考文献数
20
被引用文献数
10

This paper proposes Deep Neural Network (DNN)-based Voice Conversion (VC) using input-to-output highway networks. VC is a speech synthesis technique that converts input features into output speech parameters, and DNN-based acoustic models for VC are used to estimate the output speech parameters from the input speech parameters. Given that the input and output are often in the same domain (e.g., cepstrum) in VC, this paper proposes a VC using highway networks connected from the input to output. The acoustic models predict the weighted spectral differentials between the input and output spectral parameters. The architecture not only alleviates over-smoothing effects that degrade speech quality, but also effectively represents the characteristics of spectral parameters. The experimental results demonstrate that the proposed architecture outperforms Feed-Forward neural networks in terms of the speech quality and speaker individuality of the converted speech.
著者
Xing Xiaoxiong Dobashi Yoshinori Yamamoto Tsuyoshi Katsura Yosuke Anjyo Ken
出版者
The Institute of Electronics, Information and Communication Engineers (IEICE)
雑誌
IEICE transactions on information and systems (ISSN:17451361)
巻号頁・発行日
vol.E98, no.2, pp.404-411, 2015-02

We present an algorithm for efficient rendering of animated hair under a dynamic, low-frequency lighting environment. We use spherical harmonics (SH) to represent the environmental light. The transmittances between a point on a hair strand and the light sources are also represented by SH functions. Then, a convolution of SH functions and the scattering function of a hair strand is precomputed. This allows us to efficiently compute the intensity at a point on the hair. However, the computation of the transmittance is very time-consuming. We address this problem by using a voxel-based approach: the transmittance is computed by using a voxelized hair model. We further accelerate the computation by sampling the voxels. By using our method, we can render a hair model consisting of tens of thousands of hair strands at interactive frame rates.
著者
CHOI Yunja
出版者
The Institute of Electronics, Information and Communication Engineers
雑誌
IEICE transactions on information and systems (ISSN:09168532)
巻号頁・発行日
vol.96, no.3, pp.735-738, 2013-03-01
被引用文献数
1

An automotive operating system is a typical safety-critical software and therefore requires extensive analysis w.r.t its effect on system safety. Our earlier work [1] reported a systematic model checking approach for checking the safety properties of the OSEK/VDX-based operating system Trampoline. This article reports further performance improvement using embeddedC constructs for efficient verification of the Trampoline model developed in the earlier work. Experiments show that the use of embeddedC constructs greatly reduces verification costs.