• Title/Summary/Keyword: 차단앱

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A Guidelines for Establishing Mobile App Management System in Military Environment - focus on military App store and verification system - (국방환경에서 모바일 앱 관리체계 구축방안 제시 - 국방 앱스토어 및 검증시스템 중심으로 -)

  • Lee, Gab-Jin;Goh, Sung-Cheol
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.3
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    • pp.525-532
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    • 2013
  • Recently. smartphones have been popularized rapidly and now located deep in our daily life, providing a variety of services from banking, SNS (Social Network Service), and entertainment to smart-work mobile office through apps. Such smartphone apps can be easily downloaded from what is known as app store which, however, bears many security issues as software developers can just as easily upload to it. Military apps will be exposed to a myriad of security threats if distributed through internet-basis commercial app store. In order to mitigate such security concerns, this paper suggests a security guidelines for establishing a military-excusive app store and security verification system which prevent the security hazards that can occur during the process of development and distribution of military-use mobile apps.

App Store security policy trends (앱스토어 보안정책 동향)

  • Bae, Jung-Min;Bae, Yu-Mi;Jung, Sung-Jae;Jang, Rea-Young;Soh, Woo-Young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2014.05a
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    • pp.587-590
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    • 2014
  • Spread of smart devices increases, the App Store market is formed so huge, even at this point, every day the scale is increasing now. As a result, for the benefit of companies and private individuals, malicious apps that threaten the security of smart devices, have appeared occasionally in the App Store. Security of the terminal, has issued various solutions through research at many universities and companies, and country. However, solutions for research and policy approaches that are blocking the procedure to register the application malicious app, so that it is not registered in the App Store, Only company that operates the app store is doing it. And the reference is also insufficient, various problems have occurred. In this study, after analyzing the problem of the security policy of the current App Store, presenting the breaking point.

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Advanced Feature Selection Method on Android Malware Detection by Machine Learning (악성 안드로이드 앱 탐지를 위한 개선된 특성 선택 모델)

  • Boo, Joo-hun;Lee, Kyung-ho
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.30 no.3
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    • pp.357-367
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    • 2020
  • According to Symantec's 2018 internet security threat report, The number of new mobile malware variants increased by 54 percent in 2017, as compared to 2016. And last year, there were an average of 24,000 malicious mobile applications blocked each day. Existing signature-based technologies of malware detection have limitations. So, malware detection technique through machine learning is being researched to detect malware variant. However, even in the case of applying machine learning, if the proper features of the malware are not properly selected, the machine learning cannot be shown correctly. We are focusing on feature selection method to find the features of malware variant in this research.

A Study of Negative App Detection from Active Pattern Anlysis in Android Platform (안드로이드 플랫폼에서 활성 패턴 분석을 통한 부정 앱 검출에 관한 연구)

  • Lee, Chang-Soo;Hwang, Jin-Wook
    • Proceedings of the KAIS Fall Conference
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    • 2012.05b
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    • pp.835-838
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    • 2012
  • 최근 스마트폰의 폭팔적인 증가와 함께 사용 환경개선도 이루어 지고 있다. 또한 Wi-Fi 존의 증가와 LTE같은 빠른 네트워크 환경은 사용자 중심의 수 많은 앱을 탄생시키고 있다. 안드로이드는 애플의 iOS와는 다른 오픈소스 정책으로 플랫폼 소스가 공개되어 있어 많은 개발자가 쉽게 접근이 가능하다. 그러나 안드로이드는 앱(App) 검증 체계가 미흡하기 때문에 악성코드 등으로 인한 위협요소가 존재하고 있다. 또한 파일 시스템은 임의적 접근제어방식으로 공격자가 취약점을 통해 관리자 권한을 얻어 시스템 자원을 제어할 수 있기 때문에 위협요소가 다분하다. 본 논문에서는 스마트폰 앱이 호출하는 시스템 API 및 네트워크 자원사용 패턴을 분석하여 부정 앱을 차단하는 방법을 제안하였다. 제안 방법으로 실험한 결과 API호출 빈도 및 자원 사용률이 최소 기준치 이하로 검출된 경우를 제외한 평가대상은 모두 검출하여 보안성 강화에 효과적인 것으로 실험을 통하여 검증하였다.

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A Exploring the impact of malware on mobile devices (모바일 장치에 대한 멀웨어의 영향 탐색)

  • Jun-ho Lee;Jae-kyung Park
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.07a
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    • pp.611-613
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    • 2023
  • 모바일 멀웨어는 민감한 데이터의 도용, 기기 성능 저하, 금전적 피해 유발 등 다양한 위협을 내포하고 있으며 특히 피싱, 앱 기반 공격 및 네트워크 기반 공격과 같은 기술을 통해 모바일 장치를 악용할 수 있다. 이를 해결하기 위해 바이러스 백신 소프트웨어 및 강력한 암호 사용과 같은 보안 기술을 구현하면 모바일 멀웨어의 영향을 방지하고 완화하는 데 도움이 될 수 있다. 추가적으로 개인과 조직이 모바일 멀웨어와 관련된 위험을 인식하고 불리한 결과를 피하기 위해 이를 차단하기 위한 사전 조치를 취하는 것이 중요하다. 본 논문에서는 이러한 조치에 대한 보안 예방책을 제안하고자 하며 이를 통해 보다 안전한 모바일 환경을 갖출 수 있을 것이라 판단한다.

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Content Analysis of Smartphone Addiction Management Applications: Self-Determination Theory Perspective (스마트폰 중독방지 앱의 자기결정적 동기화 속성에 관한 내용분석: 자기결정성 이론을 중심으로)

  • Lee, Sook-Jung
    • The Journal of the Korea Contents Association
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    • v.16 no.4
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    • pp.12-22
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    • 2016
  • The present study aims to evaluate the self-determined motivational features of smartphone addiction management apps. This study analyzed whether smartphone addiction management apps have features to support adolescent users' basic needs, that is, autonomy, competence, and relatedness. 26 apps were analyzed. Among them, 8 apps were parental management apps installed on a parent's phone and a child's phone, and 18 apps were self-management apps installed on a child's phone. According to a content analysis, only 3 of 26 apps addressed all three basic needs. Overall, the functions to support users' competence and relatedness were rarely found. Particularly, parental management apps had a high level of controlingness. The results suggest that the addiction management apps have limitations in stimulating adolescent users' self-determined motivation to manage their phone use.

Identification of Counterfeit Android Malware Apps using Hyperledger Fabric Blockchain (블록체인을 이용한 위변조 안드로이드 악성 앱 판별)

  • Hwang, Sumin;Lee, Hyung-Woo
    • Journal of Internet Computing and Services
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    • v.20 no.2
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    • pp.61-68
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    • 2019
  • Although the number of smartphone users is continuously increasing due to the advantage of being able to easily use most of the Internet services, the number of counterfeit applications is rapidly increasing and personal information stored in the smartphone is leaked to the outside. Because Android app was developed with Java language, it is relatively easy to create counterfeit apps if attacker performs the de-compilation process to reverse app by abusing the repackaging vulnerability. Although an obfuscation technique can be applied to prevent this, but most mobile apps are not adopted. Therefore, it is fundamentally impossible to block repackaging attacks on Android mobile apps. In addition, personal information stored in the smartphone is leaked outside because it does not provide a forgery self-verification procedure on installing an app in smartphone. In order to solve this problem, blockchain is used to implement a process of certificated application registration and a fake app identification and detection mechanism is proposed on Hyperledger Fabric framework.

A String Analysis based System for Classifying Android Apps Accessing Harmful Sites (유해 사이트를 접속하는 안드로이드 앱을 문자열 분석으로 검사하는 시스템)

  • Choi, Kwang-Hoon;Ko, Kwang-Man;Park, Hee-Wan;Youn, Jong-Hee
    • The KIPS Transactions:PartA
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    • v.19A no.4
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    • pp.187-194
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    • 2012
  • This paper proposes a string analysis based system for classifying Android Apps that may access so called harmful sites, and shows an experiment result for real Android apps on the market. The system first transforms Android App binary codes into Java byte codes, it performs string analysis to compute a set of strings at all program points, and it classifies the Android App as bad ones if the computed set contains URLs that are classified because the sites provide inappropriate contents. In the proposed approach, the system performs such a classification in the stage of distribution before installing and executing the Apps. Furthermore, the system is suitable for the automatic management of Android Apps in the market. The proposed system can be combined with the existing methods using DNS servers or monitoring modules to identify harmful Android apps better in different stages.

AI Security Plan for Public Safety Network App Store (재난안전통신망 앱스토어를 위한 AI 보안 방안 마련)

  • Jung, Jae-eun;Ahn, Jung-hyun;Baik, Nam-kyun
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.458-460
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    • 2021
  • The provision and application of public safety network in Korea is still insufficient for security response to the mobile app of public safety network in the stages of development, initial construction, demonstration, and initial service. The available terminals on the Disaster Safety Network (PS-LTE) are open, Android-based, dedicated terminals that potentially have vulnerabilities that can be used for a variety of mobile malware, requiring preemptive responses similar to FirstNet Certified in U.S and Google's Google Play Protect. In this paper, before listing the application service app on the public safety network mobile app store, we construct a data set for malicious and normal apps, extract features, select the most effective AI model, perform static and dynamic analysis, and analyze Based on the result, if it is not a malicious app, it is suggested to list it in the App Store. As it becomes essential to provide a service that blocks malicious behavior app listing in advance, it is essential to provide authorized authentication to minimize the security blind spot of the public safety network, and to provide certified apps for disaster safety and application service support. The safety of the public safety network can be secured.

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Harmful Image Detection Method Using Skin and Non-Skin Features (피부 특징과 비 피부 특징을 이용한 유해 이미지 탐지 방법)

  • Jun, Jae-Hyun;Jung, Min-Suk;Jang, Yong-Suk;Ahn, Cheol-Woong;Kim, Sung-Ho
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.15 no.4
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    • pp.55-61
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    • 2015
  • Today, IT technology provide convenience to many people. Smartphone era is opened, and market environment is changing rapidly. Pornography market is active by using smartphone use free internet. Many people access mobile harmful site of USA and Japan. App store of the apple has been cut off the porn service, but access block to mobile Web page is an impossible situation. In this paper, we proposed the harmful image detection method of using skin and non skin features to detect harmful image. Our proposed method can provide enough performance than previous method.