Korea University Research and Business Foundation

Other

Apptest.ai

Ju Hyeon Lee

Kyung Ho Lee

Chang Yeon Kim

Jae Hee Lee

Won Sun Park

Sung Sun Park

Young In You

Vladimir Vlaskin

Il Chae Jung

Da Hee Choi

Youngin You

Chae Woon Kim

Dahee Choi

Hyun Jin Park

Jun Hyoung Oh

Jae Jun Hwang

In Shik Park

Junhyoung Oh

Sang Gook Park

Provided are a method of detecting abnormal financial transactions and an apparatus thereof. The apparatus includes: a memory in which an abnormal transaction detection program is stored; and a processor configured to execute the program. Upon execution of the program, the processor performs a data preprocessing operation to acquired payment data, extracts at least one feature adaptively determined in advance from results of the preprocessing operation, and uses the extracted feature to determine whether the payment data correspond to an abnormal transaction through a machine learning algorithm adaptively determined in advance.

Apparatus and method of detecting abnormal financial transaction

Provided is a system and method capable of automatically testing a website or application for an error in a user interface without human intervention. As an example, in a system for testing an error in a user interface of an application or website, a user interface system that includes a testable action recognizer that obtains a screenshot of a screen of the application or website, manages a layout and a test action based on user interface (UI) configuration and text recognition information from the screenshot, and a test action generator that receives the layout, selects a test scenario corresponding the layout, and performs a test action according to the test scenario, and in which the testable action recognizer manages whether or not a test is progressed for each screen layout according to the test scenario, is disclosed.

System and method for user interface autonomous testing

Disclosed is an apparatus for managing a risk of a malware behavior in a mobile operating system, which includes: a deducing unit configured to deduce characteristics of a malware from results of a static analysis on mobile malware data and a dynamic analysis thereon under a virtual environment by using a blacklist including an indicator of compromise (IOC) utilized in an existing mobile malware.

Apparatus and method for managing risk of malware behavior in mobile operating system and recording medium for perform the method

The invention relates to an easily fabricated and highly luminous electroluminescence (EL) device, whose front transparent electrode is made by using transparent conductive powder and transparent conductive binder, and a method for making such an EL device. The method comprises the steps of: providing a substrate; forming a metal electrode layer on the substrate, wherein the metal electrode layer reflects light incident thereto; forming a dielectric layer comprising a mixture of dielectric powder and a binder on the metal electrode layer; forming a phosphor layer including phosphor powder and a binder on the dielectric layer; and forming a transparent electrode layer including transparent conductive powder and a transparent conductive binder on the phosphor layer using a spin coating or a screen printing process employed for liquid material.

AC powder electroluminescence device and method for making the same

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Seoul, South Korea

Ju Hyeon Lee