The mobile application based on the Android platform is simple to decompile, making it possible to create malicious applications similar to normal ones, and can easily distribute the created malicious apps through the Android third party app store. In this case, the Android malicious application in the smartphone causes several problems such as leakage of personal information in the device, transmission of premium SMS, and leakage of location information and call records. Therefore, it is necessary to select a optimal model that provides the best performance among the machine learning techniques that have published recently, and provide a technique to automatically identify malicious Android apps. Therefore, in this paper, after adopting the feature engineering to Android apps on official test set, a total of four performance evaluation experiments were conducted to select the machine learning model that provides the optimal performance for Android malicious app detection.
Since the end devices of the Internet of Things (IoT) are battery operated products, careful consideration for ultra-low power (ULP) is required. The Micro Controller Unit (MCU) industry has developed very effective functions to save energy, but developers have difficulty in selecting the MCU because various operating modes are applied to reduce energy consumption by manufacturers. Therefore, this paper introduces ULPMark benchmark, a standardized benchmark method that can compare MCUs of various vendors and feature sets, and provides hardware functions for ultra-low-power operation of the two platforms that received the high evaluation scores from ULPMark. In addition, we investigated and analyzed how developers can utilize the functions for ultra low power consumption through driver APIs and detailed register control.
In the present study, using biological information of bacteria and biochemical information of chlorine dioxide gas, Gram-positive bacteria, e.g., Alloiococcus otitis, Erysipelothrix rhusiopathiae, Staphylococcus caprae, Staphylococcus lentus, and gram-negative bacteria, e.g., Acinetobacter baumannii complex, Aeromonas salmonicida, Brucella melitensis, Oligella ureolytica were used whether a plastic kit to release ClO2 gas could inhibit their growth. Overall, chlorine dioxide gas showed about 99% inhibition of bacterial growth, with less than 10 CFU. However, it was found that Gram positive Alloiococcus otitis and Gram negative Aeromonas salmonicida had more than about 50 CFU. When comparing the results of experiments with several bacteria, it suggested that the concentration of chlorine dioxide gas would be at least 10 ppm to 400 ppm for the bacterial inhibition. The results of this study could be used as basic data to evaluate the clinical usefulness of chlorine dioxide gas. If this study helps with prior knowledge to help clinicians to recognize and prevent the presence of micro-organisms that cause infections in hospitals, it would be helpful for activities such as patient care as a convergence field. In the future, it is considered that the research results will be the basis for rapidly inhibiting the microbes infected with patients by utilizing data of the information of the microbes that are inhibited for chlorine dioxide gas.
The elliptic curve crypto-algorithm is widely used in authentication for IoT environment, since it has small key size and low communication overhead compare to the RSA public key algorithm. If the scalar multiplication, a core operation of the elliptic curve crypto-algorithm, is not implemented securely, attackers can find the secret key to use simple power analysis or differential power analysis. In this paper, an elliptic curve scalar multiplication algorithm using a randomized scalar and an elliptic curve point blinding is suggested. It is resistant to power analysis but does not significantly reduce efficiency. Given a random and an elliptic curve random point , the elliptic scalar multiplication is calculated by using the regular variant Shamir's double ladder algorithm, where -bit ≡ mod and ≡ mod using ∓ for the case of the order ±.
The remarkable change in the automobile industry, which is a traditional industrial field, is now evolving into a form of moving toward autonomous functions rather than humans due to various convenience functions and automatic driving or autonomous driving technologies if the person was central when driving the car. This situation is expanding to various industries such as the aviation industry and the drone market, as well as the robot market. The drone market in the aviation industry is being used in various fields due to the unmanned nature of drone operation. Among them, military drones are secret and due to the specificity of technology, details are not disclosed, but as a collection of advanced technologies, they have played a key role in drone development. In this study, the current status of China and the European Union, including the United States, which are major competitors in the drone field, was investigated, and the technologies of major countries were compared and analyzed through the characteristics and operational specifications of the drones currently in operation.
The paper proposed the method of calculating the latest approach angle that can reliably recognize multiple laser images even with the change in separation distance between screen and laser launch device. This method recognizes the angle of the laser pattern angle by using the distance of the laser pattern angle, and the angle extraction of the laser detects the laser image from the acquired image using the labeling algorithm, and performs the huff conversion to extract the angle of the straight line. The distance of the reference angle and angle of the laser image extracted using Euclidean distance among similarity scales is calculated, and the furnace is recognized using the calculated distance result value. Experiments with changing the separation distance to "200 cm to 400 cm" showed 100% recognition of individual strands at all separation distances. The experiment confirmed the reliability of the proposed method.
In this paper, we propose a QoS-based handover management scheme in SDN. Even though there have been lots of recent services such as IoT, the conventional networks provide a monolitic handover method without considerations on flow-specific QoS features. For example, the conventional Internet provides a handover method which only considers IP continuity. On the other hand, 4G and 5G networks use a strict handover method for all kinds of flows with resource reservations. This means that it is difficult to guarantee the QoS requirements for the flow with a strict QoS requirement in Internet and the inefficient resource utilization can occur in the 4G and 5G because of the strict QoS-based handover management. The proposed scheme proposes the flow handover management scheme based on QoS requirements according to the SDN controller’s management. From the network operators’ perspective, the proposed scheme can provide the efficient resource utilization as well as QoS provisioning.
In this paper, we developed a mobile new media solution that enables e-commerce shopping mall operators, band operators, and YouTube creators to create synergies in online and offline promotion by posting related video contents on the media in addition to their own videos. By providing videos in the field of the platform without directly searching for them, it is possible to provide users with a new type of marketing means that can promote their platform while providing interest and information. Prospective creators at home and abroad who produce video can upload their own video in addition to YouTube and afreeca TV, such as the open market for video, and use independent and free charging systems to manage independent customer relationship management(CRM), self-branding, and content management. It will be possible to utilize mobile-based new media equipped with a system.
The purpose of this study was to investigate the smartphone addition, which effects sleep, scholastic achievement and mental health in nursing students. The study subjects consisted of 185 nursing students in grade 2nd, 3rd who completed a informed consent. The date were collected from 13th of May to 3rd of June 2019. Data were analyzed descriptive statistics, Independent t-test, one-way ANOVA, Pearson correlation and stepwise multiple regression using by IBM SPSS/WIN 24.0. The score for Smart Phone addition was 36.99 out of 60. The more addicted a smartphone is, the more likely shows lower score of sleep (r=.19, p=.009), mental health (r=.34, p<.001) was found to be negative. The key variable for effecting nursing students' mental health was smartphone addiction, quality of sleep and time, level of grade. Among them, smartphone addiction (β=.27) was found to have the highest influence for all. Explanation that by influencing factors was 20.4%. Therefore, for the mental health of nursing students, various programs that can reduce smartphone addiction should be applied and sleep management should be done.
The study aims to measure and analysis the spatial equity of Medical welfare facilities for older persons and services, and, based on this, to seek the plan to secure the fairness. To this end, the research was carried out by converging the studies of geography and regional development for the equity of social welfare studies and space arrangement on types and functions of Medical welfare facilities for older persons. The main results of the study showed that, first, in case of the spatial arrangement(desire-to-service), Medical welfare facilities for older persons are located in all areas of cities(Si) and counties(Gun) but mostly existing in cities. Second, in case of the equity of regional distribution of Medical welfare facilities for older persons, it can say the equity in Gun is higher than Si, comparing the regions of Si and Gun. Third, in case of spatial equity of sanatorium for older persons, the spatial equity of care facilities for older persons showed statistical difference depending on the time required to reach the facility, but no difference on distance. This study made various suggestions based on the results of the above research, and suggested the necessity of convergence studies grafting technologies such as AI and the Internet of Things.
This study examines the North Korean defectors' economic and psychological adjustment status in South Korean society focusing on the specificity of North Korean defectors with the social integration perspective. We conducted a questionnaire survey of 225 North Korean defectors in Seoul and Gyeonggi-do and conducted analysis using the SPSS 22.0 program. The results of the study are as follows. First, the economic adaptation of North Korean defectors was evaluated to be generally low. Second, North Korean refugees' psychological and social adjustment status is generally lower than average, especially cultural adaptation stress, friendship, and satisfaction with physical and mental health. Third, the psychological and cultural adaptation strategy and social support of defectors affected the life satisfaction positively and the adaptation stress had significant negative impact on life satisfaction. Therefore, strategies which reducing adaptive stress and enhancing psychological and cultural adaptation strategies are needed to be implemented in South Korean society. Based on results, policy alternatives were discussed.
The surrounding environments in which we live are changing from time to time due to the influence of ICT. At the heart of this change is not only the industrial sector, but it appears in most areas of everyday life. At the center of information and communication technology are software, intelligence, and sensing technology. The government and related organizations are promoting policies to foster various software, and with these policies, the software-related industry is steadily developing. There are positive aspects about software development, but also negative ones. The problems of duplication and progress due to software development have been increasing as the software industry has increased in quantity. In this study, we proposed a more objective method based on software engineering as a solution to problems when problems related to development progress occurred during the software development process.
Although various home services are developed as increasing the number of home devices with wire and wireless connection, privacy infringement and private information leakage are occurred by unauthorized remote connection. It is almost caused by without of device authentication and protection of transmission data. In this paper, the devices' secret value are stored in a safe memory of a smartphone. A smartphone processes device authentication. In order to prevent leakage of a device's password, a shadow password multiplied a password by the private key is stored in a device. It is proposed mutual authentication between a smartphone and a device, and session key agreement for devices using recovered passwords on SRP. The proposed protocol is resistant to eavesdropping, a reply attack, impersonation attack.