Group signatures are signatures providing signer anonymity where signers can produce signatures on behalf of the group that they belong to. Although such anonymity is quite attractive considering privacy issues, it is not trivial to check whether a signer has been revoked or not. Thus, how to revoke the rights of signers is one of the major topics in the research on group signatures. In particular, scalability, where the signing and verification costs and the signature size are constant in terms of the number of signers N, and other costs regarding signers are at most logarithmic in N, is quite important. In this paper, we propose a revocable group signature scheme which is currently more efficient compared to previous all scalable schemes. Moreover, our revocable group signature scheme is secure under simple assumptions (in the random oracle model), whereas all scalable schemes are secure under q-type assumptions. We implemented our scheme by employing a Barreto-Lynn-Scott curve of embedding degree 12 over a 455-bit prime field (BLS-12-455), and a Barreto-Naehrig curve of embedding degree 12 over a 382-bit prime field (BN-12-382), respectively, by using the RELIC library. We showed that the online running times of our signing algorithm were approximately 14msec (BLS-12-455) and 11msec (BN-12-382), and those of our verification algorithm were approximately 20msec (BLS-12-455) and 16msec (BN-12-382), respectively. Finally, we showed that our scheme (with a slight extension) is applied to an identity management system proposed by Isshiki et al.

Chosen-ciphertext security is a central goal in designing a secure public-key encryption scheme, and it is also important that the chosen-ciphertext security is tightly reduced to some well-established hard problem. Moreover, it is more important to have a tight reduction in the multi-user multi-challenge setting, since a tight security reduction in the single-user single-challenge setting generally does not imply a tight reduction to the multi-user multi-challenge setting. We propose the first fully tightly secure and practical public-key encryption scheme which is chosen-ciphertext secure in the multi-user multi-challenge setting in the random oracle model. The scheme is proven secure under the decisional Diffie-Hellman assumption in a pairing-free group. The ciphertext overhead of our scheme is two group elements and two exponents.

We present a constant-size signature scheme under the CDH assumption. It has a tighter security reduction than any other constant-size signature scheme with a security reduction to solving some intractable search problems. Hofheinz, Jager, and Knapp (PKC 2012) presented a constant-size signature scheme under the CDH assumption with a reduction loss of O(q), where q is the number of signing queries. They also proved that the reduction loss of O(q) is optimal in a black-box security proof. To the best of our knowledge, no constant-size signature scheme has been proposed with a tighter reduction (to the hardness of a search problem) than that proposed by Hofheinz et al., even if it is not re-randomizable. We remark that our scheme is not re-randomizable. We achieve the reduction loss of O(q/d), where d is the number of group elements in a public key.

Homomorphic encryption allows computation over encrypted data, and can be used for delegating computation: data providers encrypt their data and send them to an aggregator, who can then perform computation over the encrypted data on behalf of a client, without the underlying data being exposed to the aggregator. However, since the aggregator is merely a third party, it may be malicious, and in particular, may submit an incorrect aggregation result to the receiver. Ohara et al. (APKC2014) studied secure aggregation of time-series data while enabling the correctness of aggregation to be verified. However, they only provided a concrete construction in the smart metering system and only gave an intuitive argument of security. In this paper, we define verifiable homomorphic encryption (VHE) which generalizes their scheme, and introduce formal security definitions. Further, we formally prove that Ohara et al.'s VHE scheme satisfies our proposed security definitions.

In this paper, we revisit related-key security of TWINE block cipher with 80-bit and 128-bit keys. Using an MILP-aided automatic search algorithm, we point out the previous evaluation of TWINE with a 80-bit key is wrong, and give a corrected evaluation result. Besides, we show a first security evaluation of TWINE with a 128-bit key in the related-key setting, which was infeasible due to the high computation cost in the original proposal.

Promoting the use of public transport (PT) is considered to be an effective way to reduce the number of passenger cars. The concept of Mobility-as-a-Service (MaaS), which began in Europe and is now spreading rapidly around the world, is expected to help to improve the convenience of PT on the viewpoint of users, using the latest information communication technology and Internet of Things technologies. This paper outlines the concept of MaaS in Europe and the efforts made at the policy level. It also focuses on the development of MaaS from the viewpoint of promoting the use of PT in Japan.

A light field, which is equivalent to a dense set of multi-view images, has various applications such as depth estimation and 3D display. One of the essential problems in light field applications is light field interpolation, i.e., view interpolation. The interpolation accuracy is enhanced by exploiting an inherent property of a light field. One example is that an epipolar plane image (EPI), which is a 2D subset of the 4D light field, consists of many lines, and these lines have almost the same slope in a local region. This structure induces a sparse representation in the frequency domain, where most of the energy resides on a line passing through the origin. On the basis of this observation, we propose a group sparsity prior suitable for light fields to exploit their line structure fully for interpolation. Specifically, we designed the directional groups in the discrete Fourier transform (DFT) domain so that the groups can represent the concentration of the energy, and we thereby formulated an LF interpolation problem as an overlapping group lasso. We also introduce several techniques to improve the interpolation accuracy such as applying a window function, determining group weights, expanding processing blocks, and merging blocks. Our experimental results show that the proposed method can achieve better or comparable quality as compared to state-of-the-art LF interpolation methods such as convolutional neural network (CNN)-based methods.

Because of its high throughput potentiality on short-range communications and inherent superiority of high precision on ranging and localization, ultra-wideband (UWB) technology has been attracting attention continuously in research and development (R&D) as well as in commercialization. The first domestic regulation admitting indoor UWB in Japan was released by the Ministry of Internal Affairs and Communications (MIC) in 2006. Since then, several revisions have been made in conjunction with UWB commercial penetration, emerging new trends of industrial demands, and coexistence evaluation with other wireless systems. However, it was not until May 2019 that MIC released a new revision to admit outdoor UWB. Meanwhile, the IEEE 802 LAN/MAN Standards Committee has been developing several UWB related standards or amendments accordingly for supporting different use cases. At the time when this paper is submitted, a new amendment known as IEEE 802.15.4z is undergoing drafting procedure which is expected to enhance ranging ability for impulse radio UWB (IR-UWB). In this paper, we first review the domestic UWB regulation and some of its revisions to get a picture of the domestic regulation transition from indoor to outdoor. We also foresee some anticipating changes in future revisions. Then, we overview several published IEEE 802 standards or amendments that are related to IR-UWB. Some features of IEEE 802.15.4z in drafting are also extracted from open materials. Finally, we show with our recent research results that time bias internal a transceiver becomes important for increasing localization accuracy.

Visible light communication (VLC) will play a wide variety of important roles in future communication services. This paper deals with color shift keying (CSK) for the modulation of visible light communications. There are some previous studies about psychological and physiological effects of colors. These studies implied that color offset CSKs have psychological and physiological effects, which normal CSK doesn't have. This paper evaluates the psychological and physiological effects of color offset CSKs compared with normal CSK based on interviews and electroencephalogram (alpha wave, beta wave, and P300) measurements. This study evaluates the feasibility of visible light communication providing added value by measuring arousal, rest, visual attraction, task performance, capacity of working memory, and response for the CSK codes. The results showed that red-, green- and blue-offset CSK have specific features. Red-offset CSK induces excitement and increasing wakefulness levels, attracts attention, enlarges capacity of working memory, raises task performance, and induces fast responses. Green-offset CSK maintains rest levels, elevates relaxation levels, reduces stress, raises task performance, and induces fast responses. Blue-offset CSK maintains rest levels and induces fast responses. It is thought that we can use color offset CSK appropriately and provide added value to their application by considering the results of psychological and physiological investigations. Red-offset CSK is thought to be suitable for commercial advertisements. Green- and blue-offset CSK are thought to be suitable for wireless communication environments in hospitals. Red- and green-offset CSK are thought to be suitable for wireless communication environments in business. Red-, green- and blue-offset CSK are thought to be suitable for use in intelligent transportation systems (ITS).

In this paper, we analyze the security of an end-to-end encryption scheme (E2EE) of LINE, a.k.a Letter Sealing. LINE is one of the most widely-deployed instant messaging applications, especially in East Asia. By a close inspection of their protocols, we give several attacks against the message integrity of Letter Sealing. Specifically, we propose forgery and impersonation attacks on the one-to-one message encryption and the group message encryption. All of our attacks are feasible with the help of an end-to-end adversary, who has access to the inside of the LINE server (e.g. service provider LINE themselves). We stress that the main purpose of E2EE is to provide a protection against the end-to-end adversary. In addition, we found some attacks that even do not need the help of E2E adversary, which shows a critical security flaw of the protocol. Our results reveal that the E2EE scheme of LINE do not sufficiently guarantee the integrity of messages compared to the state-of-the-art E2EE schemes such as Signal, which is used by WhatApp and Facebook Messenger. We also provide some countermeasures against our attacks. We have shared our findings with LINE corporation in advance. The LINE corporation has confirmed our attacks are valid as long as the E2E adversary is involved, and officially recognizes our results as a vulnerability of encryption break.

In this article, we propose a data framework for edge computing that allows developers to easily attain efficient data transfer between mobile devices or users. We propose a distributed key-value storage platform for edge computing and its explicit data distribution management method that follows the publish/subscribe relationships specific to applications. In this platform, edge servers organize the distributed key-value storage in a uniform namespace. To enable fast data access to a record in edge computing, the allocation strategy of the record and its cache on the edge servers is important. Our platform offers distributed objects that can dynamically change their home server and allocate cache objects proactively following user-defined rules. A rule is defined in a declarative manner and specifies where to place cache objects depending on the status of the target record and its associated records. The system can reflect record modification to the cached records immediately. We also integrate a push notification system using WebSocket to notify events on a specified table. We introduce a messaging service application between mobile appliances and several other applications to show how cache rules apply to them. We evaluate the performance of our system using some sample applications.

In this paper, we propose an adaptive fusion successive cancellation list decoder (ADF-SCL) for polar codes with single cyclic redundancy check. The proposed ADF-SCL decoder reasonably avoids unnecessary calculations by selecting the successive cancellation (SC) decoder or the adaptive successive cancellation list (AD-SCL) decoder depending on a log-likelihood ratio (LLR) threshold in the decoding process. Simulation results show that compared to the AD-SCL decoder, the proposed decoder can achieve significant reduction of the average complexity in the low signal-to-noise ratio (SNR) region without degradation of the performance. When Lmax=32 and Eb/N0=0.5dB, the average complexity of the proposed decoder is 14.23% lower than that of the AD-SCL decoder.

The spectrum sensing of the orthogonal frequency division multiplexing (OFDM) system in cognitive radio (CR) has always been challenging, especially for user terminals that utilize the full-duplex (FD) mode. We herein propose an advanced FD spectrum-sensing scheme that can be successfully performed even when severe self-interference is encountered from the user terminal. Based on the “classification-converted sensing” framework, the cyclostationary periodogram generated by OFDM pilots is exhibited in the form of images. These images are subsequently plugged into convolutional neural networks (CNNs) for classifications owing to the CNN's strength in image recognition. More importantly, to realize spectrum sensing against residual self-interference, noise pollution, and channel fading, we used adversarial training, where a CR-specific, modified training database was proposed. We analyzed the performances exhibited by the different architectures of the CNN and the different resolutions of the input image to balance the detection performance with computing capability. We proposed a design plan of the signal structure for the CR transmitting terminal that can fit into the proposed spectrum-sensing scheme while benefiting from its own transmission. The simulation results prove that our method has excellent sensing capability for the FD system; furthermore, our method achieves a higher detection accuracy than the conventional method.

We propose the design method of a compact long-wavelength-pass filter implemented in a two-dimensional metal-dielectric-metal (MDM) waveguide with three stubs using a transmission line model based on a low-pass prototype filter, and present the wavelength characteristics for filters in an MDM waveguide based on 0.5- and 3.0-dB equal-ripple low-pass prototype filters.

With massive utilization of video in every aspect of our daily lives, managing videos is crucial and demanding. The rich literature of data embedding has proven its viability in managing as well as enriching videos and other multimedia contents, but conventional methods are designed to operate in the media/compression layer. In this work, the synchronization between the audio-video and subtitle tracks within an MP4 format container is manipulated to insert data. Specifically, the data are derived from the statistics of the audio samples and video frames, and it serves as the authentication data for verification purpose. When needed, the inserted authentication data can be extracted and compared against the information computed from the received audio samples and video frames. The proposed method is lightweight because simple statistics, i.e., ‘0’ and ‘1’ at the bit stream level, are treated as the authentication data. Furthermore, unlike conventional MP4 container format-based data insertion technique, the bit stream size remains unchanged before and after data insertion using the proposed method. The proposed authentication method can also be deployed for joint utilization with any existing authentication technique for audio / video as long as these media can be multiplexed into a single bit stream and contained within an MP4 container. Experiments are carried out to verify the basic functionality of the proposed technique as an authentication method.

(k,n)-visual secret sharing scheme ((k,n)-VSSS) is a method to divide a secret image into n images called shares that enable us to restore the original image by only stacking at least k of them without any complicated computations. In this paper, we consider (2,2)-VSSS to share two secret images at the same time only by two shares, and investigate the methods to improve the quality of decoded images. More precisely, we consider (2,2)-VSSS in which the first secret image is decoded by stacking those two shares in the usual way, while the second one is done by stacking those two shares in the way that one of them is used reversibly. Since the shares must have some subpixels that inconsistently correspond to pixels of the secret images, the decoded pixels do not agree with the corresponding pixels of the secret images, which causes serious degradation of the quality of decoded images. To reduce such degradation, we propose several methods to construct shares that utilize 8-neighbor Laplacian filter and halftoning. Then we show that the proposed methods can effectively improve the quality of decoded images. Moreover, we demonstrate that the proposed methods can be naturally extended to (2,2)-VSSS for RGB images.

Blob detection is an important part of computer vision and a special case of region detection with important applications in the image analysis. In this paper, the dilation operator in standard mathematical morphology is firstly extended to the order dilation operator of soft morphology, three soft morphological filters are designed by using the operator, and a novel blob detection algorithm called SMBD is proposed on that basis. SMBD had been proven to have better performance of anti-noise and blob shape detection than similar blob filters based on mathematical morphology like Quoit and N-Quoit in terms of theoretical and experimental aspects. Additionally, SMBD was also compared to LoG and DoH in different classes, which are the most commonly used blob detector, and SMBD also achieved significantly great results.

Thanks to the ability to bring immersive experiences to users, Virtual Reality (VR) technologies have been gaining popularity in recent years. A key component in VR systems is omnidirectional content, which can provide 360-degree views of scenes. However, at a given time, only a portion of the full omnidirectional content, called viewport, is displayed corresponding to the user's current viewing direction. In this work, we first develop Weighted-Viewport PSNR (W-VPSNR), an objective quality metric for quality assessment of omnidirectional content. The proposed metric takes into account the foveation feature of the human visual system. Then, we build a subjective database consisting of 72 stimuli with spatial varying viewport quality. By using this database, an evaluation of the proposed metric and four conventional metrics is conducted. Experiment results show that the W-VPSNR metric well correlates with the mean opinion scores (MOS) and outperforms the conventional metrics. Also, it is found that the conventional metrics do not perform well for omnidirectional content.

This paper proposes a visual analytics (VA) interface for time-series data so that it can solve the problems arising from the property of time-series data: a collision between interaction and animation on the temporal aspect, collision of interaction between the temporal and spatial aspects, and the trade-off of exploration accuracy, efficiency, and scalability between different visualization methods. To solve these problems, this paper proposes a VA interface that can handle temporal and spatial changes uniformly. Trajectories can show temporal changes spatially, of which direct manipulation enables to examine the relationship among objects either at a certain time point or throughout the entire time range. The usefulness of the proposed interface is demonstrated through experiments.

The similarity of words extracted from the rich text relation network is the main way to calculate the semantic similarity. Complex relational information and text content in Wikipedia website, Community Question Answering and social network, provide abundant corpus for semantic similarity calculation. However, most typical research only focused on single relationship. In this paper, we propose a semantic similarity calculation model which integrates multiple relational information, and map multiple relationship to the same semantic space through learning representing matrix and semantic matrix to improve the accuracy of semantic similarity calculation. In experiments, we confirm that the semantic calculation method which integrates many kinds of relationships can improve the accuracy of semantic calculation, compared with other semantic calculation methods.