• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.377-380
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• 2022

An application called an app can be downloaded and used on mobile devices. Among them, Android-based apps have the disadvantage of being implemented on an open source basis and can be exploited by anyone, but unlike iOS, which discloses only a small part of the source code, Android is implemented as an open source, so it can analyze the code. However, since anyone can participate in changing the source code of open source-based Android apps, the number of malicious codes increases and types are bound to vary. Malicious codes that increase exponentially in a short period of time are difficult for humans to detect one by one, so it is efficient to use a technique to detect malicious codes using AI. Most of the existing malicious app detection methods are to extract Features and detect malicious apps. Therefore, three ways to select the optimal feature to be used for learning after feature extraction are proposed. Finally, in the step of modeling with optimal features, ensemble techniques are used in addition to a single model. Ensemble techniques have already shown results beyond the performance of a single model, as has been shown in several studies. Therefore, this paper presents a plan to select the optimal feature and implement a learning model for Android app-based malicious code detection.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.31-43
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• 2014

Large number of Android mobile application has been developed and deployed through the Android open market by increasing android-based smart work device users recently. But, it has been discovered security vulnerabilities on malicious applications that are developed and deployed through the open market or 3rd party market. There are issues to leak user's personal and financial information in mobile devices to external server without the user's knowledge in most of malicious application inserted Trojan Horse forms of malicious code. Therefore, in order to minimize the damage caused by malignant constantly increasing malicious application, it is required a proactive detection mechanism development. In this paper, we analyzed the existing techniques' Pros and Cons to detect a malicious application and proposed discrimination and detection result using malicious application discrimination mechanism based on Jaccard similarity after collecting events occur in real-time execution on android-mobile devices.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.306-308
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• 2018

This paper proposes a variant malicious code detection algorithm in a mobile environment using a deep learning algorithm. In order to solve the problem of malicious code detection method based on Android, we have proved high detection rate through signature based malicious code detection method and realtime malicious file detection algorithm using machine learning method.

• Journal of Internet Computing and Services
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• v.14 no.3
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• pp.35-46
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• 2013

As mobile terminal environment gets matured, the use of Android platform based mobile terminals has been growing high. Recently, the number of attacks by malicious application is also increasing as Android platform is vulnerable to private information leakage in nature. Most of these malicious applications are easily distributed to general users through open market or internet and an attacker inserts malicious code into malicious app which could be harmful tool to steal private data and banking data such as SMS, contacts list, and public key certificate to a remote server. To cope with these security threats more actively, it is necessary to develop countermeasure system that enables to detect security vulnerability existing in mobile device and take an appropriate action to protect the system against malicious attacks. In this sense, this paper aggregates diverse system events from multiple mobile devices and also implements a system to detect attacks by malicious application.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.1
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• pp.45-55
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• 2019

DEX file and share objects (also known as the SO file) are important components that define the behaviors of an Android application. DEX file is implemented in Java code, whereas SO file under ELF file format is implemented in native code(C/C++). The two layers - Java and native can communicate with each other at runtime. Malicious applications have become more and more prevalent in mobile world, they are equipped with different evasion techniques to avoid being detected by anti-malware product. To avoid static analysis, some applications may perform malicious behavior in native code that is difficult to analyze. Existing researches fail to extract the call relationship which includes both Java code and native code, or can not analyze multi-DEX application. In this study, we design and implement a system that effectively extracts the call relationship between Java code and native code by analyzing DEX file and SO file of Android application.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.223-226
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• 2013

Information security breaches caused by malicious code is arising in various forms with exponential growth. The latest information security threats on computers are increasing, especially on smartphone, which has enabled malicious code to quickly surge. As a result, the leakage of personal information, such as billing information, is under threat. Meanwhile the attack vector o smartphone malware is difficult to detect. In this paper, we propose a smartphone security system to respond to the spread of malicious code by iPhone and Android OS-based malware analysis.

• Journal of the Korea Convergence Society
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• v.8 no.3
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• pp.49-61
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• 2017

Recently, convenience and usability are increasing with the development and deployment of various mobile applications on the Android platform. However, important information stored in the smartphone is leaked to the outside without knowing the user since the malicious mobile application is continuously increasing. A variety of mobile vaccines have been developed for the Android platform to detect malicious apps. Recently discovered server-based polymorphic(SSP) malicious mobile apps include obfuscation techniques. Therefore, it is not easy to detect existing mobile vaccines because some other form of malicious app is newly created by using SSP mechanism. In this paper, we analyze the correlation between the similarity of the method in the DEX file constituting the core malicious code and the permission similarity measure through APK de-compiling process for the SSP malicious app. According to the analysis results of DEX method similarity and permission similarity, we could extract the characteristics of SSP malicious apps and found the difference that can be distinguished from the normal app.

• International journal of advanced smart convergence
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• v.6 no.1
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• pp.1-8
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• 2017

Diverse types of malicious code such as evasive Server-side Polymorphic are developed and distributed in third party open markets. The suspicious new type of polymorphic malware has the ability to actively change and morph its internal data dynamically. As a result, it is very hard to detect this type of suspicious transaction as an evidence of Server-side polymorphic mobile malware because its C&C server was shut downed or an IP address of remote controlling C&C server was changed irregularly. Therefore, we implemented Simulated C&C Server to aggregate activated events perfectly from various Server-side polymorphic mobile malware. Using proposed Simulated C&C Server, we can proof completely and classify veiled server-side polymorphic malicious code more clearly.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.666-668
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• 2013

Recently, the kind and number of malicious code, which operates in Operation System of smart devices, are rapidly increasing along with the fast supplement of smart devices. Especially, smart devices based on Android OS have high potential of danger to expose to malicious code as it has an easy access to system authority. When using intent, the global message system provided from Android, inter approach between applications is available, and possible to access to created data by the device. Intent provides convenience to application development in the aspect of reusability of component however, it could be appointed as a risk element in security-wise. Therefore, if intent is used in malicious purpose, it is easy to lead the condition where is weak on security. That is, it is possible to control as accessing to resources which application is carrying to operate by receiving intents as making smart device uncontrollable or consuming system resources. Especially, in case of system authority is achieved, the risks such as smart device control or personal information exposure become bigger when misusing broadcast intent through malicious code. This paper proposes a corresponding method of security vulnerability of Android intent that monitors the appearance of intent with intent pattern inspection, detects and blocks unidentified pattern intent.

• Journal of Korea Multimedia Society
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• v.19 no.10
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• pp.1792-1807
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• 2016

Android application is vulnerable to reverse engineering attack. And by this, it is easy to extract significant module from source code and repackage it. To prevent this problem, dynamic class loading technique, which is able to exclude running code from distributed source code and is able to load running code dynamically during runtime can be used. Recently, this technique was adapted on variety of fields and applications like updating pre-loaded android application, preventing from repacking malicious application, etc. Despite the fact that this technique is used on variety of fields and applications, there is fundamental lack on the study of potential weakness or related secure coding. This paper would deal with potential weaknesses during the implementation of dynamic class loading technique with analysing related international/domestic standard of weaknesses and suggest a secure way for the implementation of dynamic class loading technique. Finally, we believe that this technique described here could increase the level of trust by decreasing the weakness related to dynamic class loading technique.