• Journal of information and communication convergence engineering
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• v.20 no.4
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• pp.280-287
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• 2022

Recently, the number of mobile ransomware types has increased. Moreover, the number of cases of damage caused by mobile ransomware is increasing. Representative damage cases include encrypting files on the victim's smart device or making them unusable, causing financial losses to the victim. This study classifies ransomware apps by analyzing several representative ransomware apps to identify trends in the malicious behavior of ransomware. We present a technique for recovering from the damage, from a digital forensic perspective, using reverse engineering ransomware apps to analyze vulnerabilities in malicious functions applied with various cryptographic technologies. Our study found that ransomware applications are largely divided into three types: locker, crypto, and hybrid. In addition, we presented a method for recovering the damage caused by each type of ransomware app using an actual case. This study is expected to help minimize the damage caused by ransomware apps and respond to new ransomware apps.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.6
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• pp.1457-1465
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• 2017

With the growing of smart devices market, malicious behavior has gradually expanded its scope. Accordingly, many studies have been conducted to analyze malicious apps and automated analysis tools have been released. However these tools cause the side effects that the application protection tools such as ProGuard, DexGuard become vulnerable to analyzers or attackers. This paper suggests the protection mechanism to apply to the Android apps using security token, rather than general-purpose protection solutions that can be applied in malicious apps. The main features of this technique are that Android app is not properly loaded in the memory when the security token is abnormal or is not inserted and protected parts using the technique are not exposed.

• 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.

• Journal of KIISE
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• v.42 no.12
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• pp.1611-1622
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• 2015

Although Android systems provide a permission-based access control mechanism and demand a user to decide whether to install an app based on its permission list, many users tend to ignore this phase. Thus, an improved method is necessary for users to intuitively make informed decisions when installing a new app. In this paper, with regard to the permission-based access control system, we present a novel approach based on a machine-learning technique in order to support a user decision-making on the fly. We apply the K-NN (K-Nearest Neighbors) classification algorithm with necessary weighted modifications for malicious app classification, and use 152 Android permissions as features. Our experiment shows a superior classification result (93.5% accuracy) compared to other previous work. We expect that our method can help users make informed decisions at the installation step.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.3
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• pp.643-653
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• 2018

Xamarin is a representative cross-platform development framework that allows developers to write mobile apps in C# for multiple mobile platforms, such as Android, iOS, or Windows Phone. Using Xamarin, mobile app developers can reuse existing C# code and share significant code across multiple platforms, reducing development time and maintenance costs. Meanwhile, malware authors can also use Xamarin to spread malicious apps on more platforms, minimizing the time and cost of malicious app creation. In order to cope with this problem, it is necessary to analyze and detect malware written with Xamarin. However, little studies have been conducted on static analysis methods of the apps written in Xamarin. In this paper, we examine the structure of Android apps written with Xamarin and propose a static analysis technique for the apps. We also demonstrate how to statically reverse-engineer apps that have been transformed using code obfuscation. Because the Android apps written with Xamarin consists of Java bytecode, C# based DLL libraries, and C/C++ based native libraries, we have studied static reverse engineering techniques for these different types of code.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.1
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• pp.73-81
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• 2021

When downloading files using an app or web-based application on the user's mobile phone, the path is set to be saved in the pre-defined default directory. Many applications requiring access to storage, including file managers, require a write or read permission of storage to provide numerous functions and services. This means that the application will have direct access to the download folder where the numerous files downloaded. In this paper, to prove our feasibility of attack using the security vulnerabilities mentioned above, we developed a file hacking function disguised as an encryption function in the file management application. The file that encrypted will be sent to hackers via E-mail simultaneously on the background. The developed application was evaluated from VirusTotal, a malicious analysis engine, was not detected as a malicious application in all 74 engines. Finally, in this paper, we propose a defense technique and an algorithm based on the Trusted Execution Environment (TEE) to supplement these storage vulnerabilities.

• Journal of Internet Computing and Services
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• v.20 no.4
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• pp.13-19
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• 2019

In order to register an application with Apple's App Store, it must pass a rigorous verification process through the Apple verification center. That's why spyware applications are difficult to get into the App Store. However, malicious code can also be executed through normal application vulnerabilities. To prevent such attacks, research is needed to detect and analyze early to patch potential vulnerabilities in applications. To prove a potential vulnerability, it is necessary to identify the root cause of the vulnerability and analyze the exploitability. A tool for analyzing iOS applications is the debugger named LLDB, which is built into Xcode, the development tool. There are various functions in the LLDB, and these functions are also available as APIs and are also available in Python. Therefore, in this paper, we propose a method to efficiently analyze potential vulnerabilities of iOS application by using LLDB API.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.568-571
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• 2013

스마트 폰의 보급량이 증가함에 따라 모바일 악성코드의 위협도 높아졌다. 여러 스마트 폰 플랫폼 중 안드로이드 플랫폼은 높은 점유율과 개방형 플랫폼이라는 특성상 다른 플랫폼에 비해 악의적인 공격에 취약하다. 안드로이드 앱이 스마트 폰에 설치, 실행되기 위해서는 개발자의 서명이 요구된다. 안드로이드 서명체계는 다중 서명을 허용하는데, 다중서명 체계상 악용될 수 있는 취약점이 존재한다. 본 연구에서는 안드로이드 코드서명의 취약점을 이용하여 악성코드를 실행시키고 다른 앱을 감염시키는 악성 앱을 개발하여 취약점의 악용 가능성에 대해 연구하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.902-904
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• 2022

스마트폰 사용자 수가 증가함에 따라 스미싱, 몸캠피싱, 메신저 피싱과 같은 정보통신망을 이용한 범죄가 큰 폭으로 증가하고 있다. 이러한 범죄 피해는 다양한 연령층에서 발생하고 있다. 본 논문에서는 국내 모바일 운영체제 점유율이 가장 높은 안드로이드 운영체제를 대상으로 하는 패킹된 악성 앱 언패킹을 수행하고 시그니처 기반 탐지 도구인 Yara 를 통해 악성 앱에 사용된 패커를 식별하는 통합 악성 앱 언패킹 시스템을 제공하여 악성 앱을 이용한 범죄 대응에 도움을 줄 수 있을 것으로 기대된다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.1
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• pp.250-256
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• 2017

Recently, the use of mobile devices has increased in order to provide a variety of services, and thus there has been a surge in the number of application malicious attacks on the Android platform. To resolve the problem, the domestic financial sector has been introducing the app anti-tamper solution based on cryptographic algorithms. However, since the capacity of apps installed in smartphones continues to increase and environments with limited resources as wearables and IoTs spread, there are limitations to the processing speed of the anti-tamper solutions. In this paper, we propose a novel anti-tamper solution by using lightweight hash function LEA and LSH. We also present the test results of a simulation program that implements this method and compare the performance with anti-tamper solutions based on the previous cryptographic algorithms.