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Gait and physical fitness are related to cognitive function. A decrease in motor function and physical fitness can serve as an indicator of declining global cognitive function in older adults. This study aims to use machine learning (ML) to identify important features of gait and physical fitness to predict a decline in global cognitive function in older adults. A total of three hundred and six participants aged seventy-five years or older were included in the study, and their gait performance at various speeds and physical fitness were evaluated. Eight ML models were applied to data ranked by the p-value (LP) of linear regression and the importance gain (XI) of XGboost. Five optimal features were selected using elastic net on the LP data for men, and twenty optimal features were selected using support vector machine on the XI data for women. Thus, the important features for predicting a potential decline in global cognitive function in older adults were successfully identified herein. The proposed ML approach could inspire future studies on the early detection and prevention of cognitive function decline in older adults.

Over the last decade, high dimensional data have been popularly paid attention to in bioinformatics. These data increase the likelihood of detecting the most promising novel information. However, there are limitations of high-performance computing and overfitting issues. To overcome the issues, alternative strategies need to be explored for the detection of true important features. A two-stage approach, filtering and variable selection steps, has been receiving attention. Filtering methods are divided into two categories of individual ranking and feature subset selection methods. Both have issues with the lack of consideration for joint correlation among features and computing time of an NP-hard problem. Therefore, we proposed a new filter ranking method (PF) using the elastic net penalty with sure independence screening (SIS) based on resampling technique to overcome these issues. We demonstrated that SIS-LASSO, SIS-MCP, and SIS-SCAD with the proposed filtering method achieved superior performance of not only accuracy, AUROC, and geometric mean but also true positive detection compared to those with the marginal maximum likelihood ranking method (MMLR) through extensive simulation studies. In addition, we applied it in a real application of colon and lung cancer gene expression data to investigate the classification performance and power of detecting true genes associated with colon and lung cancer.

Electric vehicles (EVs) can be considered as a revolution in the combustion industry with significant improvement in fuel utilization and decrease in pollution compared to combustion engines. However, by decreasing the size of the battery to reduce the cost, the frequency of charging EVs in a day increases. Therefore, to reduce the downtime required for charging EVs, wireless charging on the move can be an effective solution. In such a situation, paying for wireless charging on the move is an important issue. However, it can endanger the location privacy of users, since the EVs need to charge frequently in a day. In this paper, we first explain different methods of payment and problems with such payment methods in the case of wireless charging on the move. Then, we propose an efficient payment method based on `tokens' for wireless charging on the move, which minimizes the communications between service providers and users during the charging process. The proposed scheme prevents users and service providers from cheating, and it is robust to support different values for the price. Finally, we compare it with other payment methods that have been proposed for plug-in electric vehicles.

Motivation: The advent of high throughput data has led to a massive increase in the number of hypothesis tests conducted in many types of biological studies and a concomitant increase in stringency of significance thresholds. Filtering methods, which use independent information to eliminate less promising tests and thus reduce multiple testing, have been widely and successfully applied. However, key questions remain about how to best apply them: When is filtering beneficial and when is it detrimental? How good does the independent information need to be in order for filtering to be effective? How should one choose the filter cutoff that separates tests that pass the filter from those that don’t? Result: We quantify the effect of the quality of the filter information, the filter cutoff and other factors on the effectiveness of the filter and show a number of results: If the filter has a high probability (e.g. 70%) of ranking true positive features highly (e.g. top 10%), then filtering can lead to dramatic increase (e.g. 10-fold) in discovery probability when there is high redundancy in information between hypothesis tests. Filtering is less effective when there is low redundancy between hypothesis tests and its benefit decreases rapidly as the quality of the filter information decreases. Furthermore, the outcome is highly dependent on the choice of filter cutoff. Choosing the cutoff without reference to the data will often lead to a large loss in discovery probability. However, naïve optimization of the cutoff using the data will lead to inflated type I error. We introduce a data-based method for choosing the cutoff that maintains control of the family-wise error rate via a correction factor to the significance threshold. Application of this approach offers as much as a several-fold advantage in discovery probability relative to no filtering, while maintaining type I error control. We also introduce a closely related method of P-value weighting that further improves performance. Availability and implementation: R code for calculating the correction factor is available at http://www.stat.uga.edu/people/faculty/paul-schliekelman. Contact: pdschlie@stat.uga.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Users can access their data anywhere, at any time by using outsourced storage. But they cannot know how service provider manage the data. Even user cannot know when data damaged. To solve these problems, the outsourced storage auditing schemes has been proposed. Most proposed schemes are based on Homomorphic Verifiable Tags. But it has computational efficiency limitation because data used to exponent. In this paper, we propose a novel approach to outsourced storage auditing scheme using coefficient matrix. In the proposed scheme, data used to auditing by coefficient matrix form. Auditing procedures are proceed as solving the linear simultaneous equation. The auditor can audit easily by solving the equation using solution vector. The auditor can audit the n size data using sqrt(n) size data through out proposed scheme.

Proxy re-encryption scheme has advantage where plaintext does not get exposed during re-encryption process. This scheme is popular for sharing server-saved data in case of cloud computing or mobile office that uses server to save data. Since previous proxy re-encryption schemes can use re-encryption key over and over again, it may abuse re-encryption. To solve this problem, conditional proxy re-encryption scheme was proposed. But, it is computationally expensive generate the same number of re-encryption key with the number of condition values. In this paper, we propose an efficient conditional proxy re-encryption scheme in terms of re-encryption key generation. The proposed scheme uses only encryption and decryption process. Therefore it has advantage to generate one re-encryption key for one person. The proposed scheme is secure against chosen-ciphertext attack.

Comparable encryption allows a verifier to test whether given two ciphertexts from a probabilistic public key cryptosystem are encryption of the same message without decrypting them. Recently, Yang et al. proposed such scheme and Lee et al. and Tang independently modified Yang et al.`s system to restrict the entity who can perform the verification. However, the original Yang et al.`s scheme has a flaw that enables two ciphertexts which are not encryption of the same message to pass the test. In this paper, we concretely show the faults in all three schemes considered and analyze the effect of this flaw in the use of such schemes in applications.

In this paper, we investigate the effectiveness of speaker adaptation for various essential components in deep neural network based speech synthesis, including acoustic models, acoustic feature extraction, and post-filters. In general, a speaker adaptation technique, e.g., maximum likelihood linear regression (MLLR) for HMMs or learning hidden unit contributions (LHUC) for DNNs, is applied to an acoustic modeling part to change voice characteristics or speaking styles. However, since we have proposed a multiple DNN-based speech synthesis system, in which several components are represented based on feed-forward DNNs, a speaker adaptation technique can be applied not only to the acoustic modeling part but also to other components represented by DNNs. In experiments using a small amount of adaptation data, we performed adaptation based on LHUC and simple additional fine tuning for DNNbased acoustic models, deep auto-encoder based feature extraction, and DNN-based post-filter models and compared them with HMM-based speech synthesis systems using MLLR.

Recently, a new type of Radio Frequency IDentification (RFID) system with mobile readers is introduced. In such a system, it is more desirable for mobile readers to identify tags without a back-end server, and thus it is frequently referred as a serverless mobile RFID system. In this paper, we formalize a serverless mobile RFID system model and propose a new encryption-based system that preserves the privacy of both tags and readers in the model. In addition, we define a new adversary model for the system model and show the security of the proposed system. Throughout comparisons between ours and the other alternatives, we show that our proposed system provides a stronger reader privacy and robustness against a reader forgery attack than the competitors.

Recently, the strategy for N-screen service is in the spotlight along with the consumer`s need to use contents regardless of time and place due to the rapid development of communication technology, which is meshing with the desire of service providers seeking a new business model. N-screen, as a screen-extension-concept service which enables consumers to continuously share and use contents in various equipments such as TV, computer and portable terminals, is an advanced type of 3-screen service strategy initially proposed by AT&T, an American telecommunication company. In the N-screen service for pay-contents, in order to support continuous screen changes to and from various equipments, temporary watching right should be given to the equipment intended for screen change. However, it is impossible to give the temporary watching right in the present broadcasting environment, adopting an access-control system. In this paper, the access-control technology being used for pay-contents in the present broadcasting environment and the reason for not being able to give temporary watching right, will be examined. After the examination, the solution for delegation of watching right by using an additional key on the basis of currently used access-control technology, will be proposed.

In an RFID search protocol, a reader uses a designated query instead of an unspecified query commonly used in RFID authentication protocols. Due to this fundamental difference, techniques used in RFID authentication protocols may not be suitable for RFID search protocols. Tan et al.'s protocol, however, is based on techniques used in previous works such as using random values. In this paper, we propose two RFID search protocols, one based on static ID and the other based on dynamic ID, both which does not require additional measures to satisfy security requirements of RFID protocols. We achieve this by using counters.

In this paper, we investigate a combination of several feedforward deep neural networks (DNNs) for a high-quality statistical parametric speech synthesis system. Recently, DNNs have significantly improved the performance of essential components in the statistical parametric speech synthesis, e.g. spectral feature extraction, acoustic modeling and spectral post-filter. In this paper our proposed technique combines these feed-forward DNNs so that the DNNs can perform all standard steps of the statistical speech synthesis from end to end, including the feature extraction from STRAIGHT spectral amplitudes, acoustic modeling, smooth trajectory generation and spectral post-filter.The proposed DNN-based speech synthesis system is then compared to the state-of-the-art speech synthesis systems, i.e. conventional HMM-based, DNN-based and unit selection ones.

This paper presents a new online check system that solves the reusability problem of refunds in existing systems using the partially blind signature. The clear part of the signature is used to encode the face value of a check. In our system, refunds can be reused in payment in the same way as withdrawn checks without any limitation. We also use a one-time secret key as the serial number of a check to increase the efficiency of payment. The new system provides multiple offline shopping sessions to minimize the number of online messages. During the offline session, we use a one-way accumulator to construct a proof of payment. The security and the atomicity of the system is also discussed.

Inspired by the dramatic evolution of VANE clouds, this paper proposes a new VANET-cloud service called VWaaS (Vehicle Witnesses as a Service) in which vehicles moving on the road serve as anonymous witnesses of designated events such as a terrorist attack or a deadly accident. When confronted the events, a group of vehicles with mounted cameras collaborate with roadside stationary cameras to take pictures of the site of interest (SoI) around them, and send the pictures to the cloud infrastructure anonymously. The pictures are sent to the cloud in a way that the privacy of the senders can be protected, and kept by the cloud for future investigation. However, for the case that the pictures are used as an evidence of court trial, we made the privacy protection to be conditional and thus can be revoked by authorized entity(s) if necessary.

Adaptation and manipulation techniques for creating various characteristics of synthetic speech are important research topics in the speech synthesis field. In this work, we investigate the performance of a DNN-based text-to-speech synthesis system that uses speaker, gender, and age codes as well as the text inputs (1) for modeling speaker-independent models called “average voice models,” (2) for performing speaker adaptation using a small amount of adaptation data, and also (3) for manipulating characteristics of synthetic speech based on the codes. For these purposes, we extracted a set of studio-quality speech data uttered by 68 males and 70 females, whose age vary between 10 and 80, from our large-scale Japanese corpus and carried out the three experiments: (1) We constructed a DNN-based speaker-independent model using one-hot vectors representing a set of the above speakers. (2) We performed speaker adaptation by estimating a code vector for a new speaker via the back-propagation. (3) We performed manual manipulation of the code vector to modify perceived characteristics, gender, and/or age of synthetic speech. Experimental results showed that high-performance speaker-independent models can be constructed using the proposed code vectors and additionally that adaptation and manipulation using the codes can also be performed effectively.

In this paper, we aim at two conflicting goals, privacy and Sybil attacks in Vehicular Ad Hoc NETworks (VANETs). Sybil attack refers to impersonation of one physical entity for many, namely Sybil nodes. Such attacks may cause dire consequences such as traffic jams or even deadly accidents. We leverage pseudonymless beaconing in order to preserve privacy. To cope with the Sybil attack, we put forth a two fold strategy. For scheduled beacons, we mploy TRM (Tamper Resistant Module) to perform a lightweight pre-assembly data analysis on beacons whereas for ERMs (Event Reporting Messages), RSUs distribute authorized tokens among benign vehicular nodes which in turn are consumed to report ERM. Our proposed scheme preserves privacy in both beacons and ERMs, and offers conditional anonymity.

In recent years, various mobile terminals equipped with NFC (Near Field Communication) have been released. The combination of NFC with smart devices has led to widening the utilization range of NFC. It is expected to replace credit cards in electronic payment, especially. In this regard, security issues need to be addressed to vitalize NFC electronic payment. The NFC security standards currently being applied require the use of user's public key at a fixed value in the process of key agreement. The relevance of the message occurs in the fixed elements such as the public key of NFC. An attacker can create a profile based on user's public key by collecting the associated messages. Through the created profile, users can be exposed and their privacy can be compromised. In this paper, we propose conditional privacy protection methods based on pseudonyms to solve these problems. In addition, PDU (Protocol Data Unit) for conditional privacy is defined. Users can inform the other party that they will communicate according to the protocol proposed in this paper by sending the conditional privacy preserved PDU through NFC terminals. The proposed method succeeds in minimizing the update cost and computation overhead by taking advantage of the physical characteristics of NFC1.

In this paper, we propose a key management scheme to protect contents in OPMD (One Person Multi Device) environment where a single user has multiple consumer devices. The proposed scheme using IBTD, a key management scheme that uses a user ID as a public key and the threshold decryption scheme that decrypts secret shares only if n the number of secret public values created by a contents server is more than t. Our proposed scheme enables users in OPMD environment to conveniently and easily use their contents through any of their multiple devices, and allows a contents server can manage keys efficiently in the user-centric key management way rather than in the device-centric key management way.

In this paper, we propose a key management scheme in DRM which supports multi devices by using a secret sharing. The proposed scheme enables playing contents on registered devices only, and additional overheads are not occurring even if the number of registered devices are increased. We measured the overheads occurred by the proposed scheme through a prototype implementation, and showed that the scheme is applicable to consumer devices.

The past decade has witnessed a growing interest in VANET (Vehicular Ad Hoc NETwork) and its myriad potential applications. Nevertheless, despite the surge in VANET research, security and privacy issues have been the root cause of impeded momentum in VANET deployment. In this paper we focus on misbehavior and Sybil attacks from VANET standpoint. With intrusion capabilities in hand, malicious users in VANET can inject false information and launch Sybil attack. Sybil attack refers to pretending one physical node to be many and in worst case almost all kinds of attacks can be launched in the presence of Sybil attack. Misbehavior in VANET can be categorized as a sub-effect of Sybil attack where a malicious vehicular node(s) spoof legitimate identities. There are two main strategies for avoiding misbehavior in VANET; Entity-centric strategies that focus on the revocation of misbehaving nodes by revocation authorities. On the other hand, Data-centric approach mainly focuses on the soundness of information rather than the source of information. We cover both strategies where decision on which strategy to be used, is taken on the basis of traffic situation. In a dense traffic regime, we propose SADS (Sybil Attack Detection Scheme) whereas in sparse traffic regime, we propose LMDS (Location-Based Misbehavior Detection Scheme). Our proposed schemes leverage position verification of the immediate source of warning message. Furthermore, we guarantee security and privacy (conditional anonymity) for both beacons and warning messages.

Route tracing allows authorities to determine the route traversed by a vehicle, which can be used valuably in crime investigations. In VANETs (Vehicular Ad hoc NETwork), a conditional anonymity scheme is normally used to meet the conflicting demands of the government (authentication) and users (privacy). These schemes provide a mechanism to revoke the anonymity of individual beacons sent by vehicles. However, using this mechanism to trace a route of a vehicle violates privacy of many other vehicles. In this paper, we provide a simple route tracing mechanism that reveals only the route of the targeted vehicle. The proposed method can be easily added to any existing VANET solutions and also includes a way to prevent authorities from abusing this new function.

Inspiring from MANET (Mobile Ad hoc NETworks), VANET (Vehicular Ad hoc NETworks) employing vehicles as nodes, provide a wide range of applications in transportation system. The security of VANET has been a hot topic among the research community. VANETs must meet the basic security requirements such as authentication, integrity, confidentiality and privacy. In VANET, vehicles send beacon messages periodically every 100-300ms which carry speed and position information used for safe driving. The privacy of user is abused by profile generation where the adversary makes movement profiles against the vehicle using the identity information in the beacon. We outline the strategies using pseudonyms to provide privacy of user. After finding out deficiencies in pseudonym-based schemes, we propose a pseudonymless strategy to avoid profilation. In our scheme, we assume that each car is equipped with TRH (Tamper-Resistant Hardware) carrying out secure operations. Our proposed scheme assures the avoidance of profile generation without using mix zones and silent periods. We show that our proposed scheme is computationally efficient and less bandwidth consuming than other systems.

The recently proposed Radio Frequency Identification (RFID) authentication protocol based on a hashing function can be divided into two types according to the type of information used for authentication between a reader and a tag: either a value fixed or one updated dynamically in a tag. In this study we classify the RFID authentication protocol into a static ID-based and a dynamic-ID based protocol and then analyze their respective strengths and weaknesses and the previous protocols in the static/dynamic ID-based perspectives. Also, we define four security requirements that must be considered in designing the RFID authentication protocol including mutual authentication, confidentiality, indistinguishability and forward security. Based on these requirements, we suggest a secure and efficient mutual authentication protocol. The proposed protocol is a dynamic ID-based mutual authentication protocol designed to meet requirements of both indistinguishability and forward security by ensuring the unlinkability of tag responses among sessions. Thus, the protocol can provide more strengthened user privacy compared to previous protocols and recognizes a tag efficiently in terms of the operation quantity of tags and database.

People are concerned with spam mails and viruses or worms contained in e-mails. However, people often neglect the security issues concerning the content of e-mails. In this paper, we propose practical and secure e-mail protocols that provide perfect forward secrecy. Unlike previous proposals, our protocols can be deployed without any change to the current infrastructure. Moreover, we provide a way for the sender to securely send an identical e-mail to multiple receivers.

In this paper, we propose a new efficient model for issuing multiple private keys in IBC (identity-based cryptosystem). In our model, the private key of a user is divided into two components: LTK (long-term key) and STK (short-term key). Both are issued separately by different parties. The LTK is issued in a threshold manner by KPAs (key privacy agency). In contrast, the STK is issued by a single authority called KGC (key generation center). A user can efficiently obtain a new private key containing the same identity information by contacting only the KGC and obtaining a new STK. We also give a security proof of the key issuing model and present a new IBE (identity-based encryption) scheme based on our key issuing model.

In UMTS (Universal Mobile Telecommunication System), a protocol called UMTS AKA (Authentication and Key Agreement) is used to securely authenticate an MS (Mobile Station). However, the UMTS AKA has several drawbacks such as network bandwidth consumption and synchronization problem. In this paper, we propose a new authentication protocol for UMTS that overcomes these problems. Moreover, our protocol enhances the security of the protocol by providing better privacy and also provides perfect forward secrecy. Furthermore, our protocol also provides mutual authentication between an MS and its HN (Home Network) and between an MS and the SN (Serving Network).

In 2005, Lee et al. proposed an ID-based 2-party key agreement protocol between users whose private keys were issued by independent PKGs that do not share any system parameters. This work was the first kind that assumes completely independent multiple PKG environment. However, Lee et al. protocol has a flaw that allows attackers to impersonate others without knowing their private keys. In this paper, we propose a modification to the protocol of Lee et al. that prevents impersonation attacks. We also show a simple technique that can improve the efficiency of tripartite key agreement protocol of Lee et al. We also provide analysis of the security and efficiency of the proposed protocols.

Electronic voting schemes must provide universal verifiability and receipt-freeness. However, since their objectives are mutually contradictory, providing both properties are difficult. To date, most electronic voting schemes provide only one of these properties and those few which provide both properties are not practical due to heavy computational requirements. In this paper, we present an efficient electronic voting scheme that provides both properties. The proposed scheme uses a trusted third party called HS (Honest Shuffler) and requires only one-way untappable channels from HSs to voters. Currently, this is the weakest physical assumption required for receipt-freeness. Among the schemes which assume only one-way untappable channels and provide both properties, our scheme requires the least amount of computation.

This paper presents a desktop video conferencing system, called Seodang, for collaborative learning. Seodang enables individuals to participate in telelearning, connecting people together over distances in natural ways for the purpose of learning. The system consists of a video conferencing system and application-specific programs. The video conferencing system provides two-way audio and video communications using MuX. Other application programs include shared electronic whiteboard, query control system, presentation manager and student database manager. Each of these applications provides useful tools that improve the quality of learning, while students are allowed to participate interactively. Design and implementation of the system is presented along with its communication characteristics.