• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2188-2203
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• 2021

With the rapid development of mobile Internet, smart phones have been widely popularized, among which Android platform dominates. Due to it is open source, malware on the Android platform is rampant. In order to improve the efficiency of malware detection, this paper proposes deep learning Android malicious detection system based on behavior features. First of all, the detection system adopts the static analysis method to extract different types of behavior features from Android applications, and extract sensitive behavior features through Term frequency-inverse Document Frequency algorithm for each extracted behavior feature to construct detection features through unified abstract expression. Secondly, Long Short-Term Memory neural network model is established to select and learn from the extracted attributes and the learned attributes are used to detect Android malicious applications, Analysis and further optimization of the application behavior parameters, so as to build a deep learning Android malicious detection method based on feature analysis. We use different types of features to evaluate our method and compare it with various machine learning-based methods. Study shows that it outperforms most existing machine learning based approaches and detects 95.31% of the malware.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.4
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• pp.1471-1492
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• 2015

The rapid development of smartphone technologies have resulted in the evolution of mobile botnets. The implications of botnets have inspired attention from the academia and the industry alike, which includes vendors, investors, hackers, and researcher community. Above all, the capability of botnets is uncovered through a wide range of malicious activities, such as distributed denial of service (DDoS), theft of business information, remote access, online or click fraud, phishing, malware distribution, spam emails, and building mobile devices for the illegitimate exchange of information and materials. In this study, we investigate mobile botnet attacks by exploring attack vectors and subsequently present a well-defined thematic taxonomy. By identifying the significant parameters from the taxonomy, we compared the effects of existing mobile botnets on commercial platforms as well as open source mobile operating system platforms. The parameters for review include mobile botnet architecture, platform, target audience, vulnerabilities or loopholes, operational impact, and detection approaches. In relation to our findings, research challenges are then presented in this domain.

• Journal of Advanced Navigation Technology
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• v.20 no.4
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• pp.374-379
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• 2016

Recently, IoT(Internet of Things) to connect the objects and people has attracted attention. And it is rapidly developing. IoT is to develop, experts are predicting that the device is connected to the Internet to break through around 100 billion within 10 years. However, the current IoT companies are having a difficult state to the other each other IoT platform for interaction between data silos effects. These silos effects will limit the IoT grow to a larger market. Thus, the IoT service supplier shall develop an open platform for interaction IoT data between each IoT platform. These web technologies for current open IoT platform has emerged. If developers are using familiar, easy-to-learn Web technologies, developers can take advantage of a variety of services for the collected data, and found the IoT devices can be bypassed if there is a problem on the network. In this paper, we investigate the data communications technology that can be used in WoT environment to overcome these silos effects. As a result, the polling method that can simply send the IoT information the fastest.

• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.77-86
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• 2018

For the past few years, KISTI has been servicing an online simulation execution platform, called EDISON, allowing users to conduct simulations on various scientific applications supplied by diverse computational science and engineering disciplines. Typically, these simulations accompany large-scale computation and accordingly produce a huge volume of output data. One critical issue arising when conducting those simulations on an online platform stems from the fact that a number of users simultaneously submit to the platform their simulation requests (or jobs) with the same (or almost unchanging) input parameters or files, resulting in charging a significant burden on the platform. In other words, the same computing jobs lead to duplicate consumption computing and storage resources at an undesirably fast pace. To overcome excessive resource usage by such identical simulation requests, in this paper we introduce a novel framework, called IceSheet, to efficiently manage simulation data based on execution metadata, that is, provenance. The IceSheet framework captures and stores each provenance associated with a conducted simulation. The collected provenance records are utilized for not only inspecting duplicate simulation requests but also performing search on existing simulation results via an open-source search engine, ElasticSearch. In particular, this paper elaborates on the core components in the IceSheet framework to support the search and reuse on the stored simulation results. We implemented as prototype the proposed framework using the engine in conjunction with the online simulation execution platform. Our evaluation of the framework was performed on the real simulation execution-provenance records collected on the platform. Once the prototyped IceSheet framework fully functions with the platform, users can quickly search for past parameter values entered into desired simulation software and receive existing results on the same input parameter values on the software if any. Therefore, we expect that the proposed framework contributes to eliminating duplicate resource consumption and significantly reducing execution time on the same requests as previously-executed simulations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.430-432
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• 2022

With the recent increase in interest in the open science movement in science and technology fields such as open access, open data, and open source, the movement to share and utilize publicly funded research products is materializing and revitalizing. In line with this trend, many efforts are being made to establish and revitalize a system for sharing and utilizing research data, which is a key resource for research in Korea. These efforts are mainly focused on collecting research data by field and institution, and linking it with DataON, a national research data platform, to search and utilize it. However, developed countries are building a system that can share and utilize not only such research data but also various types of R&D-related computing resources such as IaaS, PaaS, SaaS, and MLaaS. EOSC (European Open Science Cloud), ARDC (Australian Research Data Commons), and CSTCloud (China S&T Cloud) are representative examples. In Korea, the Korea Research Data Commons (KRDC) is designed and a core framework is being developed to facilitate the sharing of these computing resources. In this study, the necessity, concept, composition, and future plans of KRDC are introduced.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.6
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• pp.73-79
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• 2010

The number of electronic embedded software in vehicle system is ever increasing for years. As a result, the electronic control units have been growing dramatically, and it is required to mutual link between these units. Due to separate API each and every embedded platform, it is difficult to develop and integrate in automotive industry. The AUTOSAR project consists suppliers and manufacturers, and the partnership is a standardized platform to establish and develop an industry standard. On the previous works, we implemented the RTE generated module design based on AUTOSAR architecture. This paper specifically focuses on the testing of the development tool that generates RTE source code. The result satisfied a need for a RTE requirements and AUTOSAR methodology in a vehicle applications.

• Journal of Advanced Navigation Technology
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• v.20 no.6
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• pp.562-567
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• 2016

IoT is attracting attention as the development of the Internet and the spread of smart devices are rapidly increasing worldwide. As IoT is integrated into everyday life, the market is getting bigger. So, experts predict that IoT devices will grow to more than one trillion in a decade. Techniques related to IoT are also being developed steadily, and studies are underway to develop IoT in various fields. However, vendors launching IoT services do not interact with data from other platforms. Therefore, it is limited to growing into a big market by facing the obstacle called the silo phenomenon. To solve this problem, web technology attracts attention. Web technology can interact with data regardless of platform, and it can not only develop various services using the data, but also reduce unnecessary costs for developers. In this paper, we have studied a web - based open IoT system that can transmit data independently in real time to the IoT platform.

• Journal of Distribution Science
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• v.22 no.5
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• pp.81-91
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• 2024

Purpose: Edutech, which is the application of information and communication technology to education, is being introduced in various ways across all levels, from primary and secondary education to lifelong education. The purpose of this study was to present metadata about Edutech tools to provide the method for providing various Edutech tools. Research design, data, and methodology: To achieve the research purpose, the necessary elements for the metadata of Edutech tools were first derived based on a literature review. A focus group interview (FGI) with experts was conducted to gather opinions on the developed metadata, further validating its appropriateness. Results: The metadata area consisted of "Basic Information", "Product Information", and "Utilization Information". The "Basic Information" section had 9 items, "Product Information" had 8 items, and "Utilization Information" was presented with 4 items. Conclusions: This study proposed metadata for Edutech tools, which can be utilized to develop distribution system to proliferate and harness various Edutech tools in the educational setting. For the future establishment of an Edutech tool distribution system based on this metadata, it's imperative to operate a credible platform to ensure a stable distribution framework.

• The Journal of Society for e-Business Studies
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• v.27 no.1
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• pp.43-62
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• 2022

This paper is a study to analyze when ISV(independent software company) has more active participation in the platform ecosystem. According to previous studies, companies are active in technological innovation when they can appropriate the outcome of innovation and when they have complementary assets (marketing, manufacturing capabilities, etc.) that can convert the innovation into value. The effect of these two conditions to join platform ecosystem is investigated. The duplication between the ISV's product portfolio and platform service is also included as an independent variable. The two sample groups are composed of independent SW companies that signed a partner agreement with platform companies and non-participating companies in the platform. As a result of empirical study, it is found that the patent rights do not affect participation in the platform. The ISVs might have believed that the benefits from cooperation with platform companies are greater than the risks of exposure to innovative technologies and unique Biz models. On the other hand, downstream's capability and the duplication of product portfolio affect participation in the platform. If ISVs have the downstream capability to transform cooperation into value creation, ISVs are actively participating in the platform. In addition, cooperation is active when the product portfolio is complementary to platform service rather than competition. This study is the empirical study of open innovation between Korean independent software companies and digital platform companies. There are similar prior studies abroad, but there are no similar studies in Korea. It is meaningful in that the determinants of platform ecosystem participation were investigated through empirical analysis by composing a sample group of companies participating in the platform ecosystem and companies not participating in the platform ecosystem.

• Journal of Sensor Science and Technology
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• v.16 no.4
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• pp.247-253
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• 2007

Low power consumption sensor network platform (sensor node) for sensor networking with IEEE 802.15.4 protocol was fabricated. The sensor node used ceramic bar type antenna for increasing RF signal performance and decreasing PCB size occupied by antenna. The communication range of the fabricated sensor node was about $20{\sim}30$ m in open environment with 915 MHz frequency bandwidth and well supported by Tiny OS. The sensor node have good connectivity with various external devices by RS-232, I2C, analogue and digital expansion board, hence, this sensor node can be applied to various applications in wireless sensor network and ubiquitous sensor network.