• Journal of Digital Convergence
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• v.10 no.10
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• pp.187-195
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• 2012

By using smartphones more generally, people's lives become more convenient. However, many people complain of stress caused by the use of smartphones, further, the tendencies to reject it are appearing. In this paper, new conceptual word, antismart-resistance consciousness gained by experience before and after introduction of smart devices - is newly proposed as a research variable. In addition, we have studied to identify the relationship affecting continuous use of smartphones with technostress and antismart. To achieve this, a research model and hypotheses were presented and verified by using questionnaires data. The result showed that users who actively embrace innovative technologies were highly tolerant of technostress, whereas knowledge or experience of IT trends did not affect technostress or antismart tendencies.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.923-926
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• 2012

안드로이드는 스마트폰에서 프로그램을 실행하도록 하는 구글에서 개발한 모바일 전용 운영체제로써 현재 수백만 대의 스마트폰, 태블릿PC에 탑재되어 있다. 안드로이드는 빠른 속도의 웹브라우저, 멀티 태스킹, 클라우드 컴퓨팅 기능, 다른 장치와 쉽게 연결하여서 공유하는 기능 등을 제공하고 있다. 이에 따라 많은 스마트폰 제품들이 안드로이드 운영체제를 탑재하여 출시하고 있으며, 안드로이드는 전 세계 스마트폰 운영체제 점유율의 절반가량을 차지하고 있다. 하지만 안드로이드 운영체제가 많이 사용됨에 따라 그에 따른 안드로이드 악성코드 또한 급격하게 증가하고 있다. 따라서 본 논문에서는 안드로이드 악성코드를 탐지 및 차단할 때 분석 비용을 감소시킬 수 있는 권한정보 관리를 통한 안드로이드 안티바이러스 어플리케이션을 제안한다.

• Review of KIISC
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• v.32 no.6
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• pp.17-22
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• 2022

스마트폰 어플리케이션 데이터는 사용자와 밀접한 데이터를 포함하고 있기 때문에 디지털 포렌식 수사에서 매우 중요하게 수집되어야 할 대상이다. 하지만 어떤 어플리케이션은 암호화 기법을 활용하여 사용자 데이터를 포함한 어플리케이션 데이터를 보호한다. 데이터 암호화는 데이터 보호에 효율적이지만, 디지털 포렌식에서는 안티 포렌식으로 작용하여 어플리케이션 데이터 분석을 어렵게 한다. 따라서, 효율적인 디지털 포렌식 수사를 위해서는 암호화된 스마트폰 어플리케이션 데이터에 복호화에 대한 선제 연구가 필요하다. 본 논문에서는 최근 발표된 스마트폰 어플리케이션의 암호화된 데이터에 대한 분석 결과를 수집하여, 암호화 키 생성 및 데이터 암호화 방법에 대해 분류하였다. 이를 통해 스마트폰 어플리케이션 데이터의 암호화 방식을 습득하여 추후 또다른 어플리케이션 효율적인 분석에 활용할 수 있을 것으로 기대한다.

• Journal for History of Mathematics
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• v.32 no.1
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• pp.27-44
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• 2019

This study analyses and discusses on the characteristic and the origin of the exhaustion method caused by the controversy over whether that method succeeded to the Antiphone's complete exhaustion idea and whether that method is similar to the method of limits. First, this study analyses 'principle of exhaustion method' which play an important role in that method in order to grasp the local characteristic of it. And this study speculates the origin of the exhaustion method by considering the time and situation of appearance and looking through the local characteristic of it. Also, this study takes a view of the overall characteristic of the exhaustion method by inquiring into the process of actual application of 'principle of exhaustion method' in a proof. As these results, this study reveals that the exhaustion method uprose not as a succession of Antiphone's idea but as a reaction to its idea, and that the exhaustion method has the recognized character of 'finitude' as distinct from the method of limits.

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.61-70
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• 2022

General users who use smartphone apps often use the Vault app to protect personal information such as photos and videos owned by individuals. However, there are increasing cases of criminals using the Vault app function for anti-forensic purposes to hide illegal videos. These apps are one of the apps registered on Google Play. This paper proposes a methodology for extracting feature points through XML-based keyword frequency analysis to explore Vault apps used by criminals, and text mining techniques are applied to extract feature points. In this paper, XML syntax was compared and analyzed using strings.xml files included in the app for 15 hidden Vault anti-forensics apps and non-hidden Vault apps, respectively. In hidden Vault anti-forensics apps, more hidden-related words are found at a higher frequency in the first and second rounds of terminology processing. Unlike most conventional methods of static analysis of APK files from an engineering point of view, this paper is meaningful in that it approached from a humanities and sociological point of view to find a feature of classifying anti-forensics apps. In conclusion, applying text mining techniques through XML parsing can be used as basic data for exploring hidden Vault anti-forensics apps.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.907-913
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• 2022

Approximately 70% of smartphone users around the world use Android operating system-based smartphones, and malicious apps targeting these Android platforms are constantly increasing. Google has provided "Google Play Protect" to respond to the increasing number of Android targeted malware, preventing malicious apps from being installed on smartphones, but many malicious apps are still normal. It threatens the smartphones of ordinary users registered in the Google Play store by disguising themselves as apps. However, most people rely on antivirus programs to detect malicious apps because the average user needs a great deal of expertise to check for malicious apps. Therefore, in this paper, we propose a method to classify unnecessary malicious permissions of apps by using only the categories and permissions that can be easily confirmed by the app, and to easily detect malicious apps through the classified permissions. The proposed method is compared and analyzed from the viewpoint of undiscovered rate and false positives with the "commercial malicious application detection program", and the performance level is presented.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.1057-1059
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• 2012

스마트폰이 대중화되면서 안드로이드 애플리케이션의 보안문제가 대두되고 있다. PC환경의 소프트웨어는 개발단계에서부터 시큐어코딩을 통해 안전성을 확보하고 있으나 안드로이드 애플리케이션의 경우는 연구가 더 필요한 상황이다. 본 논문에서는 CWE(Common Weakness Enumeration)의 취약점 분류 체계와 CAPEC(Common Attack Pattern Enumeration and Classification)의 공격 패턴 분류 체계와 CERT(Computer Emergency Response Team)의 취약점 발생 예방을 위한 정책들을 통해 안드로이드 애플리케이션의 최신화된 취약점 목록을 도출하고 카테고리별로 분류하여 취약점을 효율적으로 분석하는 기법을 제안한다.

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

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.583-592
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• 2020

With the popularization of smartphones, Social Networking Service (SNS) has become the means of communication for modern people. Due to the nature of the means of communication, SNS generates a variety of archive and preservation evidence. Therefore, it is a major analysis target in terms of digital forensic investigation. An application that provides SNS stores data in a central server or database in a smartphone inside for user convenience. Some applications provide encryption for privacy, which can be anti-forensic in terms of digital forensic investigation. Therefore, the study of the encryption method should be continuously preceded. In this paper, we analyzed two applications that provide SQLite-based database encryption through SQLCipher module. Each database was decrypted and key data was identified.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.6
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• pp.1341-1351
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• 2015

As the popularization of smartphone increases the number of various applications, the number of malicious applications also grows rapidly through the third party App Market or black market. This paper suggests an investigation filter, Androfilter, that detects the fabrication of APK file effectively. Whereas the most of antivirus software uses a separate server to collect, analyze, and update malicious applications, Androfilter assumes Google Play as the trusted party and verifies integrity of an application through a simple query to Google Play. Experiment results show that Androfilter blocks brand new malicious applications that have not been reported yet as well as known malicious applications.