• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.29 no.6
• /
• pp.1235-1242
• /
• 2019

While several machine learning technique has been implemented for Android malware categorization, there is still difficulty in analyzing due to overfitting problem and including of un-executable code, etc. In this paper, we introduce our implemented tool to address these problems. Tool is consists of approximately 1,500 lines of Java code, and perform Flow analysis on set of APIs, or on control flow graph. Our tool groups all the API by its relationship and only perform analysis on actually executing code. Using our tool, we grouped 39032 APIs into 4972 groups, and 12123 groups with result of including class names. We collected 7,000 APKs from 7 families and evaluated our feature reduction technique, and we also reduced features again with selecting APIs that have frequency more than 20%. We finally reduced features to 263-numbers of feature for our collected APKs.

• Korean Journal of Remote Sensing
• /
• v.24 no.6
• /
• pp.613-620
• /
• 2008

Web on Web 2.0 paradigm is regarded as a kind of platform. Accordingly, users on web can use almost same applications like using certain applications on personal computer, to given purposes. For Web as platform, it needs web-based or web-recognizable file format to communicate or to exchange various information contents and data among applied applications. Text-based JSON is a practical format directly linked Javascript on Web, so that XML-typed data, being previously built, can be possible for tagging process containing JSON format. However, GeoJSON handling geo-spatial data sets is now fledgling stage in standards. Thus, it is not on the practical applicability level, and there are a few tools or open sources for this format. To adopt GeoJSON for the future Geo-web application, users implement GeoJSON parser or apply the server-based open source GIS for their purpose. In this study, a preliminary work for GeoJSON application in Geo-web service carried out using Google Maps API and openlayers library API.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.31 no.4
• /
• pp.605-616
• /
• 2021

While malwares must be accurately identifiable from arbitrary programs, existing studies using classification techniques have limitations that they can only be applied to limited samples. In this work, we propose a method to utilize API call frequency to detect and classify malware families from arbitrary programs. Our proposed method defines a rule that checks whether the call frequency of a particular API exceeds the threshold, and identifies a specific family by utilizing the rate information on the corresponding rules. In this paper, decision tree algorithm is applied to define the optimal threshold that can accurately identify a particular family from the training set. The performance measurements using 4,443 samples showed 85.1% precision and 91.3% recall rate for family detection, 97.7% precision and 98.1% reproduction rate for classification, which confirms that our method works to distinguish malware families effectively.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.9 no.1
• /
• pp.387-394
• /
• 2019

Recently, the importance of big data has been increased, and demand for data analysis for the big data is also increased. R language is developed for data analysis, and users are analyzing data by using algorithms of various statistics, machine learning and data mining packages in R language. However, it is difficult to develop an application using R. Early study proposed a method to call R script through another language such as PHP, Java, and so on. However, it is troublesome to write such a development method in addition to R in combination with other languages. In this study, we introduce how to write API using only R language without using another language by using Plumber package. We also propose a solution for security issues related with R API. If we use propose technology for developing web application, we can expect high productivity, easy of use, and easy of maintenance.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.27 no.1
• /
• pp.117-123
• /
• 2023

There are casualties due to inundation and flooding due to intensive typhoons or heavy rains in summer. Due to such damage, the biggest disaster is flood, and in order to reduce human damage, this paper proposes a shortest distance algorithm-based pedestrian path search study using Map API. This system selects Map API through comparative analysis and provides the shortest route. The route explored is in JSON format and the data of the shelter is stored in the database. The route search system designed and implemented based on this data locates pedestrians and provides evacuation routes in case of flash floods. In addition, if the route cannot be entered while moving to the evacuation route, the current location of the pedestrian is identified, the route is re-searched, and a new route is provided. Therefore, it is believed that the pedestrian route search system proposed in this paper will prevent negligent accidents.

• Journal of Practical Engineering Education
• /
• v.14 no.1
• /
• pp.99-108
• /
• 2022

As the demand for kiosks increases, more users complain of discomfort. Accordingly, a kiosk that enables easy menu selection and order by producing a voice-based interactive service is produced and provided in the form of a web. It implements voice functions based on the Annyang API and SpeechSynthesis API, and understands the user's intention through Dialogflow. And discuss how to implement this process based on Rest API. In addition, the recommendation system is applied based on collaborative filtering to improve the low consumer accessibility of existing kiosks, and to prevent infection caused by droplets during the use of voice recognition services, it provides the ability to check the wearing of masks before using the service.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.10a
• /
• pp.219-221
• /
• 2022

In recent summer, as it is concentrated, even in mountainous areas, flooding and flooding cause casualties in pedestrian evacuation situations. To compensate for this, a system that detects the occurrence of flooding and allows pedestrians to evacuate safely is required. Therefore, in this paper, we propose a research on pedestrian path search based on the shortest distance algorithm using Map API. The pedestrian route search system outputs a map using the T Map API, selects nearby buildings as shelters, and stores data. A shelter close to the pedestrian's current location is selected, and the shortest route is output and the distance and time are provided. If there is a problem with the current route during evacuation, another shelter route is provided from the current location. Therefore, it is thought that the pedestrian route search evacuation system proposed in this paper will prevent accidents during evacuation.

• Spatial Information Research
• /
• v.20 no.2
• /
• pp.35-44
• /
• 2012

Recently, Web map service is actively accomplished in both private companies and public offices. As a platform, it exists variously from desktop to smartphone. The technology being used has a trend to develop continuously. Also, Web map system provides various open API for people who use geospatial service and data mashup. In this paper, RIA technology which is popularly used recently in web map service w ill be applied to introduce the functions different language map services are mostly using. Based on users' feeling about different web browser's speed, test and analysis have been accomplished. The result is that there are different characteristics according to different functions such as JavaScript, Silverlight, Flex. Actual test has been personally carried out on map service in Seoul GIS portal system. The comprehensive conclusion is that Silverlight has more outstanding function compared with other RIA techniques under the test environment.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.5 no.6
• /
• pp.651-656
• /
• 2010

In the homepage of 16 municipal provincial office of education, school information service displays text-based results through search step or presents the simple information of the selected area when an area is clicked on the static image map. And it has several problems such as server load and slow transfer speed by the search of the synchronous transfer. Thus, in this study, we used the open API of Google map to provide location-based school information and implemented the mash up service for school information with the Ajax program of asynchronous transfer to reduce server load and to increase transmission speed. This service gives the efficiency and convenience to students, teachers, parents and education family members of various levels because it includes the location with school information on a dynamic map.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.11
• /
• pp.41-49
• /
• 2021

All application programs, including malware, call the Application Programming Interface (API) upon execution. Recently, using those characteristics, attempts to detect and classify malware based on API Call information have been actively studied. However, datasets containing API Call information require a large amount of computational cost and processing time. In addition, information that does not significantly affect the classification of malware may affect the classification accuracy of the learning model. Therefore, in this paper, we propose a method of extracting a essential feature set after reducing the dimensionality of API Call information by applying various feature selection methods. We used CICAndMal2020, a recently announced Android malware dataset, for the experiment. After extracting the essential feature set through various feature selection methods, Android malware classification was conducted using CNN (Convolutional Neural Network) and the results were analyzed. The results showed that the selected feature set or weight priority varies according to the feature selection methods. And, in the case of binary classification, malware was classified with 97% accuracy even if the feature set was reduced to 15% of the total size. In the case of multiclass classification, an average accuracy of 83% was achieved while reducing the feature set to 8% of the total size.