• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.3199-3218
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• 2019

Location-based services (LBSs) have become popular in recent years due to the ever-increasing usage of smart mobile devices and mobile applications through networks. Although LBS application provides great benefits to mobile users, it also raises a sever privacy concern of users due to the untrusted service providers. In the lack of privacy enhancing mechanisms, most applications of the LBS may discourage the user's acceptance of location services in general, and endanger the user's privacy in particular. Therefore, it is a great interest to discuss on the recent privacy-preserving mechanisms in LBSs. Many existing location-privacy protection-mechanisms (LPPMs) make great efforts to increase the attacker's uncertainty on the user's actual whereabouts by generating a multiple of fake-locations together with user's actual positions. In this survey, we present a study and analysis of existing LPPMs and the state-of-art privacy measures in service quality aware LBS applications. We first study the general architecture of privacy qualification system for LBSs by surveying the existing framework and outlining its main feature components. We then give an overview of the basic privacy requirements to be considered in the design and evaluation of LPPMs. Furthermore, we discuss the classification and countermeasure solutions of existing LPPMs for mitigating the current LBS privacy protection challenges. These classifications include anonymization, obfuscation, and an encryption-based technique, as well as the combination of them is called a hybrid mechanism. Finally, we discuss several open issues and research challenges based on the latest progresses for on-going LBS and location privacy research.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.1
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• pp.103-110
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• 2019

Electronic voting has been followed by a lot of research as it provides convenience to voters and increases participation rates. Nevertheless, electronic voting has not been widespread yet. The existing electronic voting system does not guarantee credibility, and there arises a question on the security that the voting could be forged or altered by the attack to the central server. In this paper, we proposed blockchain based systems to solve the problems in electronic voting. Although the blockchain may guarantee the security of transaction data, there have been only a few electronic voting systems implemented using the blockchain. We developed blockchain enabled voting and brought out some of its related legal, technical and operational challenges to enforce more security in voting. Unlike centralized voting, the systems could enforce security and solve the problems such as forgery or alteration of transaction data caused by hacking or any attempts to gain control of the central server system.

• Smart Structures and Systems
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• v.22 no.6
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• pp.675-687
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• 2018

In the previous studies on the porous rock strength the effect of pore number and its diameter is not explicitly defined. In this paper crack initiation, propagation and coalescence in Brazilian model disc containing a single cylindrical hole and or multiple holes have been studied numerically using PFC3D. In model with internal hole, the ratio of hole diameter to model diameter was varied between 0.03, 0.17, 0.25, 0.33, and 0.42. In model with multiple hole number of holes was different in various model, i.e., one hole, two holes, three holes, four holes, five holes, six holes, seven holes, eight holes and nine holes. Diameter of these holes was 5 mm, 10 mm and 12 mm. The pre-holed Brazilian discs are numerically tested under Brazilian test. The breakage load in the ring type disc specimens containing an internal hole with varying diameters is measured. The mechanism of cracks propagation in the wall of the ring type specimens is also studied. In the case of multi-hole Brazilian disc, the cracks propagation and b cracks coalescence are also investigated. The results shows that breaking of the pre-holed disc specimens is due to the propagation of radially induced tensile cracks initiated from the surface of the central hole and propagating toward the direction of diametrical loading. In the case of disc specimens with multiple holes, the cracks propagation and cracks coalescence may occur simultaneously in the breaking process of model under diametrical compressive loading. Finally the results shows that the failure stress and crack initiation stress decreases by increasing the hole diameter. Also, the failure stress decreases by increasing the number of hole which mobilized in failure. The results of these simulations were comprised with other experimental and numerical test results. It has been shown that the numerical and experimental results are in good agreement with each other.

• Smart Structures and Systems
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• v.24 no.1
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• pp.127-139
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• 2019

Residual drifts after an earthquake can incur huge repair costs and might need to replace the infrastructure because of its non-reparability. Proper functioning of bridges is also essential in the aftermath of an earthquake. In order to mitigate pounding and unseating damage of bridges subjected to earthquakes, a self-adaptive Ni-Ti shape memory alloy (SMA)-cable-based frictional sliding bearing (SMAFSB) is proposed considering self-adaptive centering, high energy dissipation, better fatigue, and corrosion resistance from SMA-cable component. The developed novel bearing is associated with the properties of modularity, replaceability, and earthquake isolation capacity, which could reduce the repair time and increase the resilience of highway bridges. To evaluate the super-elasticity of the SMA-cable, pseudo-static tests and numerical simulation on the SMA-cable specimens with a diameter of 7 mm are conducted and one dimensional (1D) constitutive hysteretic model of the SMAFSB is developed considering the effects of gap, self-centering, and high energy dissipation. Two types of the SMAFSB (i.e., movable and fixed SMAFSBs) are applied to a two-span continuous reinforced concrete (RC) bridge. The seismic vulnerabilities of the RC bridge, utilizing movable SMAFSB with the constant gap size of 60 mm and the fixed SMAFSBs with different gap sizes (e.g., 0, 30, and 60 mm), are assessed at component and system levels, respectively. It can be observed that the fixed SMAFSB with a gap of 30 mm gained the most retrofitting effect among the three cases.

• Journal of Korea Multimedia Society
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• v.22 no.5
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• pp.613-625
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• 2019

The rise of the Internet of Things (IoT) devices have greatly influenced many industries and one of them is healthcare where wearable devices started to track all your daily activities for better health monitoring accuracy and even down to tracking daily food intake in some cases. With the amounts of data that are being tracked and shared between from these devices, questions were raised on how to uphold user's data privacy when data is shared between these IoT devices and third party. With the blockchain platforms started to mature since its inception, the technology can be implemented according to a variety of use case scenarios. In this paper, we present a system architecture based on the healthcare system and IoT network by leveraging on multiple blockchain networks as the medium in between that should enable users to have direct authority on data accessibility of their shared data. We provide proof of concept implementation and highlight the results from our testing to show how the efficiency and scalability of the healthcare system improved without having a significant impact on the performance of the Electronic Medical Record (EMR) that mostly affected by the previous solution since these solutions directly connected to a public blockchain network and which resulted in significant delays and high cost of operation when a large amount of data or complicated functions are involved.

• Journal of Information Technology Services
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• v.18 no.2
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• pp.143-159
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• 2019

Machine learning (ML) is a method of fitting given data to a mathematical model to derive insights or to predict. In the age of big data, where the amount of available data increases exponentially due to the development of information technology and smart devices, ML shows high prediction performance due to pattern detection without bias. The feature engineering that generates the features that can explain the problem to be solved in the ML process has a great influence on the performance and its importance is continuously emphasized. Despite this importance, however, it is still considered a difficult task as it requires a thorough understanding of the domain characteristics as well as an understanding of source data and the iterative procedure. Therefore, we propose methods to apply deep learning for solving the complexity and difficulty of feature extraction and improving the performance of ML model. Unlike other techniques, the most common reason for the superior performance of deep learning techniques in complex unstructured data processing is that it is possible to extract features from the source data itself. In order to apply these advantages to the business problems, we propose deep learning based methods that can automatically extract features from transaction data or directly predict and classify target variables. In particular, we applied techniques that show high performance in existing text processing based on the structural similarity between transaction data and text data. And we also verified the suitability of each method according to the characteristics of transaction data. Through our study, it is possible not only to search for the possibility of automated feature extraction but also to obtain a benchmark model that shows a certain level of performance before performing the feature extraction task by a human. In addition, it is expected that it will be able to provide guidelines for choosing a suitable deep learning model based on the business problem and the data characteristics.

• Journal of IKEEE
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• v.23 no.3
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• pp.934-940
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• 2019

In this paper, we propose a Reverse Differential Chaos Shift Keying (RE-DCSK) system for low cost, high reliability and high data rate non-coherent chaos communication .In RE-DCSK, reference signals are transmitted in the first slot as in the conventional differential chaos shift modulation scheme (DCSK) and in the second slot a time inversion block strengthens the autocorrelation of the chaos signal and uses the orthogonality of the two signals to obtain the information signal. RE-DCSK enables relatively double the data rate compared to DCSK and also improves the security of communications without any additional cost of system complexity.To prove its effectiveness, we analyze it through Rayleigh fading channel and additional white Gaussian noise (AWGN) channel based on the derived BER expression. The BER performance of the proposed system is improved when compared with the CDSK and DCSK system using AWGN channel.

• Convergence Security Journal
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• v.18 no.2
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• pp.49-58
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• 2018

As the demand for Internet of Things(IoT) increases, the need for the security of IoT devices is increasing steadily. It is difficult to apply the conventional security theory to IoT devices because IoT devices are subject to be constrained by some factors such as hardware, processor, and energy. Nowadays we have several security guidelines and related documents on IoT device. Most of them, however, do not consider the characteristics of specific IoT devices. Since they describes the security issues comprehensively, it is not easy to explain the specific security level reflecting each characteristics of IoT devices. In addition, most existing guidelines and related documents are described in view of developers and service proposers, and thus ordinary users are not able to assess whether a specific IoT device can protect their information securely or not. We propose an security evaluation model, based on the existing guidelines and related documents, for more specific IoT devices and prove that this approach is more convenient to ordinary users by creating checklists for the smart watch.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.63-68
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• 2019

Emerging applications such as Smart factory, in-car network, wide area power network require strict bounds on the end-to-end network delays. Flow-based scheduler in traditional Integrated Services (IntServ) architecture could be possible solution, yet its complexity prohibits practical implementation. Sub-optimal class-based scheduler cannot provide guaranteed delay since the burst increases rapidly as nodes are passed by. Therefore a leaky-bucket type regulator placed next to the scheduler is being considered widely. This paper proposes a simple server that achieves both fair scheduling and traffic regulation at the same time. The performance of the proposed server is investigated, and it is shown that a few msec delay bound can be achieved even in large scale networks.

• Smart Structures and Systems
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• v.23 no.5
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• pp.449-466
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• 2019

Cable-stayed bridges are attractive due to their beauty, reducing material consumption, less harm to the environment and so on, in comparison with other kinds of bridges. As a massive structure with long period and low damping (0.3 to 2%) under many dynamic loads, these bridges are susceptible to fatigue, serviceability disorder, damage or even collapse. Tuned Mass Damper (TMD) is a suitable controlling system to reduce the vibrations and prevent the threats in such bridges. In this paper, Multi Tuned Mass Damper (MTMD) system is added to the Ahvaz cable stayed Bridge in Iran, to reduce its seismic vibrations. First, the bridge is modeled in SAP2000 followed with result verification. Dead and live loads and the moving loads have been assigned to the bridge. Then the finite element model is developed in OpenSees, with the goal of running a nonlinear time-history analysis. Three far-field and three near-field earthquake records are imposed to the model after scaling to the PGA of 0.25 g, 0.4 g, 0.55 g and 0.7 g. Two MTMD systems, passive and active, with the number of TMDs from 1 to 8, are placed in specific points of the main span of bridge, adding a total mass ratio of 1 to 10% to the bridge. The parameters of the TMDs are optimized using Genetic Algorithm (GA). Also, the optimum force for active control is achieved by Fuzzy Logic Control (FLC). The results showed that the maximum displacement of the center of the bridge main span reduced 33% and 48% respectively by adding passive and active MTMD systems. The RMS of displacement reduced 37% and 47%, the velocity 36% and 42% and also the base shear in pylons, 27% and 47%, respectively by adding passive and active systems, in the best cases.