• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.26 no.5
• /
• pp.1161-1170
• /
• 2016

In this paper, we provide an authentication technology for verifying dynamic signature made by finger on smart phone. In the proposed method, we are using the Auto-Encoder-based 1 class model in order to effectively distinguish skilled forgery signature. In addition to the basic dynamic signature characteristic information such as appearance and velocity of a signature, we use accelerometer value supported by most of the smartphone. Signed data is re-sampled to give the same length and is normalized to a constant size. We built a test set for evaluation and conducted experiment in three ways. As results of the experiment, the proposed acceleration sensor value and 1 class model shows 6.9% less EER than previous method.

• Journal of Digital Forensics
• /
• v.12 no.3
• /
• pp.39-54
• /
• 2018

Recently, discussions for the eradication of illegal shooting have been carried out in a socially-oriented way. The government has established comprehensive measures to eradicate cyber sexual violence crimes such as illegal shooting. Although the social interest in illegal shooting has increased, the illegal film shooting case is evolving more and more due to the development of information and communication technology. Applications that can hide confused videos are constantly circulating around the market and community sites. As a result, field investigators and professional analysts are experiencing difficulties in collecting and analyzing evidence. In this paper, we propose an evidence collection and analysis framework for illegal shooting cases in order to give practical help to illegal shooting investigation. We also proposed a system that can detect hidden applications, which is one of the main obstacles in evidence collection and analysis. We developed a detection tool to evaluate the effectiveness of the proposed system and confirmed the feasibility and scalability of the system through experiments using commercially available concealed apps.

• International Journal of Internet, Broadcasting and Communication
• /
• v.12 no.2
• /
• pp.8-14
• /
• 2020

Recently, there was an increasing demand for an integrated access control system which is capable of user recognition, door control, and facility operations control for smart buildings automation. The market available door lock access control solutions need to be improved from the current level security of door locks operations where security is compromised when a password or digital keys are exposed to the strangers. At present, the access control system solution providers focusing on developing an automatic access control system using (RF) based technologies like bluetooth, WiFi, etc. All the existing automatic door access control technologies required an additional hardware interface and always vulnerable security threads. This paper proposes the user identification and authentication solution for automatic door lock control operations using camera based visible light communication (VLC) technology. This proposed approach use the cameras installed in building facility, user smart devices and IoT open source controller based LED light sensors installed in buildings infrastructure. The building facility installed IoT LED light sensors transmit the authorized user and facility information color grid code and the smart device camera decode the user informations and verify with stored user information then indicate the authentication status to the user and send authentication acknowledgement to facility door lock integrated camera to control the door lock operations. The camera based VLC receiver uses the artificial intelligence (AI) methods to decode VLC data to improve the VLC performance. This paper implements the testbed model using IoT open-source based LED light sensor with CCTV camera and user smartphone devices. The experiment results are verified with custom made convolutional neural network (CNN) based AI techniques for VLC deciding method on smart devices and PC based CCTV monitoring solutions. The archived experiment results confirm that proposed door access control solution is effective and robust for automatic door access control.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.27 no.5
• /
• pp.1087-1097
• /
• 2017

As the penetration rate of smartphones increases, the number of malicious codes targeting smartphones is increasing. I 360 Security 's smartphone malware statistics show that malicious code increased 437 percent in the first quarter of 2016 compared to the fourth quarter of 2015. In particular, malicious applications, which are the main means of distributing malicious code on smartphones, are aimed at leakage of user information, data destruction, and money withdrawal. Often, it is operated by an API, which is an interface that allows you to control the functions provided by the operating system or programming language. In this paper, we propose a mechanism to detect malicious application based on the similarity of API pattern in normal application and malicious application by learning pattern of API in application derived from static analysis. In addition, we show a technique for improving the detection rate and detection rate for each label derived by using the corresponding mechanism for the sample data. In particular, in the case of the proposed mechanism, it is possible to detect when the API pattern of the new malicious application is similar to the previously learned patterns at a certain level. Future researches of various features of the application and applying them to this mechanism are expected to be able to detect new malicious applications of anti-malware system.

• Journal of Convergence for Information Technology
• /
• v.10 no.6
• /
• pp.19-27
• /
• 2020

In this study, Developing high resolution camera and Social Network Service sharing image can be easily getting images, it cause about taking fingerprints to easy from images. So I present solution about prevent to taking fingerprints. this technology is develop python using to opencv, blur libraries. First of all 'Hand Key point Detection' algorithm is used to locate the hand in the image. Using this algorithm can be find finger joints that can be protected while minimizing damage in the original image by using the coordinates of separate blurring the area of fingerprints in the image. from now on the development of accurate finger tracking algorithms, fingerprints will be protected by using technology as an internal option for smartphone camera apps from high resolution images.

• Journal of Digital Convergence
• /
• v.11 no.11
• /
• pp.795-801
• /
• 2013

As the life which existed only offline has changed into a life part of which is led online, it is an important problem to identify whether an online user is legitimate one or not. Biometric authentication technology was developed to identify the user more correctly either online or in offline daily life. Biometric authentication is a technology where a person is identified by his or her unique characteristics, and is highlighted as a next-generation authentication technology replacing password. There are various kinds of traits unique to each individual, and biometric authentication technologies drawing on such traits use various devices and algorithms. Firstly, this paper classified such various biometric authentication technologies, and analyzed the effects of them when they are applied on smartphone, smartwatch and M2M of the different devices platforms. Secondly, it suggested the effectiveness-based AIB(Authentication for Integrated Biometrics) authentication technique, a comprehensive authentication technique, which can be used in different devices platforms. We have successfully included the establishment scheme of the effectiveness authentication using biometrics.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.11
• /
• pp.3916-3936
• /
• 2014

Smartphone applications like games, image processing, e-commerce and social networking are gaining exponential growth, with the ubiquity of cellular services. This demands increased computational power and storage from mobile devices with a sufficiently high bandwidth for mobile internet service. But mobile nodes are highly constrained in the processing and storage, along with the battery power, which further restrains their dependability. Adopting the unlimited storage and computing power offered by cloud servers, it is possible to overcome and turn these issues into a favorable opportunity for the growth of mobile cloud computing. As the mobile internet data traffic is predicted to grow at the rate of around 65 percent yearly, even advanced services like 3G and 4G for mobile communication will fail to accommodate such exponential growth of data. On the other hand, developers extend popular applications with high end graphics leading to smart phones, manufactured with multicore processors and graphics processing units making them unaffordable. Therefore, to address the need of resource constrained mobile nodes and bandwidth constrained cellular networks, the computations can be migrated to resourceful servers connected to cloud. The server now acts as a bridge that should enable the participating mobile nodes to offload their computations through Wi-Fi directly to the virtualized server. Our proposed model enables an on-demand service offloading with a decision support system that identifies the capabilities of the client's hardware and software resources in judging the requirements for offloading. Further, the node's location, context and security capabilities are estimated to facilitate adaptive migration.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.7
• /
• pp.15-21
• /
• 2015

Due to the appearance of various mobile terminals like smartphone, smartpad, and smartwatch and tremendous development of WiFi technology, data utilization rate on WiFi network is significantly increasing. As a result, users are wanting to use WiFi network using only a simple identification at a visited place as if they are at their home institute. In this paper, we review the domestic status of eduroam service which supports global extension of wireless network access environment and present the future development perspective of the service in Korea. Besides, we shed light on the current status of WiFi sharing service between domestic universities and propose some methods to facilitate the join of domestic universities in eduroam service.

• Journal of Advanced Navigation Technology
• /
• v.23 no.5
• /
• pp.473-480
• /
• 2019

The smart home is a technology that can monitor and control by connecting everything to a communication network in various fields such as home appliances, energy consumers, and security devices. The Smart home is developing not only automatic control but also learning situation and user's taste and providing the result accordingly. This paper proposes a model that can provide a comfortable indoor environment control service for the user's characteristics by detecting the user's behavior as well as the automatic remote control service. The whole system consists of ESP 8266 with sensor and Wi-Fi, Firebase as a real-time database, and a smartphone application. This model is divided into functions such as learning mode when the home appliance is operated, learning control through learning results, and automatic ventilation using indoor and outdoor sensor values. The study used moving averages for temperature and humidity in the control of home appliances such as air conditioners, humidifiers and air purifiers. This system can provide higher quality service by analyzing and predicting user's characteristics through various machine learning and deep learning.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.37 no.7
• /
• pp.1000-1014
• /
• 2013

This study identifies the determinants that influence attitude toward and the intention to use mobile shopping services through fashion applications (apps) based on the technology acceptance model. In addition, gender and age group differences were examined. Data were collected from subjects who have used smartphone fashion related apps; subsequently, a total of 327 data were analyzed. About 46% of respondents were males, with a mean age of 34.4 years that ranged from 20 to 49 years old. Multiple regression models were developed based on the research model. Perceived usefulness, perceived ease of use, perceived enjoyment, perceived risks (security risk and quality risk), fashion involvement, and fashion app attributes (product attributes and service attributes) were employed as predictors of attitudes towards mobile shopping. Attitudes towards mobile shopping and subjective norms with the aforementioned variables measured the intention to use. Attitudes towards mobile shopping were predicted by perceived enjoyment, perceived usefulness, and service attributes. Attitudes toward mobile shopping and subjective norms were the most important predictors of the intention to use. Gender differences were found in that service attributes were significant for attitudes towards mobile shopping only in the male model. Age differences were also found and perceived usefulness was the most important predictor of attitudes toward mobile shopping among those in their 20's; however, perceived enjoyment was the most important among those in their 30's and 40's. Quality risk was only significant to explain intention to use among those in their 40's. The findings of this study are useful to understand the possibility of the adoption of mobile shopping though fashion apps and provide basic insight into market segmentation.