• Informatization Policy
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• v.24 no.4
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• pp.68-78
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• 2017

Malicious codes are currently becoming more complex and diversified, causing various problems spanning from simple information exposure to financial or psychologically critical damages. Even though many researches have studied using reverse engineering to detect these malicious codes, malicious code developers also utilize bypassing techniques against the code analysis to cause obscurity in code understanding. Furthermore, rootkit techniques are evolving to utilize such bypassing techniques, making it even more difficult to detect infection. Therefore, in this paper, we design the analysis process as a more agile countermeasure to malicious codes that bypass analysis techniques. The proposed analysis process is expected to be able to detect these malicious codes more efficiently.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.2
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• pp.431-438
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• 2019

Fileless malware uses memory injection attacks to hide traces of payloads to perform malicious works. During the memory injection attack, an attack named "process hollowing" is a method of creating paused benign process like system processes. And then injecting a malicious payload into the benign process allows malicious behavior by pretending to be a normal process. In this paper, we propose a method to detect the memory injection regardless of whether or not the malicious action is actually performed when a process hollowing attack occurs. The replication process having same execution condition as the process of suspending the memory injection is executed, the data set belonging to each process virtual memory area is compared using the fuzzy hash, and the similarity is calculated.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.1
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• pp.75-86
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• 2020

With the recent advancement of malware, the actors performing malicious tasks are often not processes. Malicious code injected into the process that is installed by default in the operating system works thread by thread in the same way as DLL / code injection. In this case, diagnosing and blocking the process as malicious can cause serious problems with system operation. This white paper lists the problems of how to use process-based monitoring information to identify and block the malicious state of a process and presents an improved solution.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.3
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• pp.501-514
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• 2013

A grouping process through the similarity comparison is required to effectively classify and respond a malicious code. When we have a use of the past similarity criteria to be used in the comparison method or properties it happens a increased problem of false negatives and false positives. Therefore, in this paper we apply to choose variety of properties to complement the problem of behavior analysis on the heuristic-based of 2nd step in malicious code auto analysis system, and we suggest a similarity comparison method applying AHP (analytic hierarchy process) for properties weights that reflect the decision-making technique. Through the similarity comparison of malicious code, configured threshold is set to the optimum point between detection rates and false positives rates. As a grouping experiment about unknown malicious it distinguishes each group made by malicious code generator. We expect to apply it as the malicious group information which includes a tracing of hacking types and the origin of malicious codes in the future.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.2
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• pp.397-405
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• 2018

Blacklist-based tools are most commonly used to effectively detect suspected malicious processes. The blacklist-based tool compares the malicious code extracted from the existing malicious code with the malicious code. Therefore, it is most effective to detect known malicious codes, but there is a limit to detecting malicious code variants. In order to solve this problem, the necessity of a white list-based tool, which is the opposite of black list, has emerged. Whitelist-based tools do not extract features of malicious code processes, but rather collect reliable processes and verify that the process that checks them is a trusted process. In other words, if malicious code is created using a new vulnerability or if variant malicious code appears, it is not in the list of trusted processes, so it can effectively detect malicious code. In this paper, we propose a method for effectively building a whitelist through research that collects reliable processes in the macOS operating system.

• Journal of Internet Computing and Services
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• v.14 no.2
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• pp.61-71
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• 2013

Until now, there have been various studies against Internet worms. Most of intrusion detection and prevention systems against Internet worms use detection rules, but these systems cannot respond to new Internet worms. For this reason, a malicious process control system which uses the fact that Internet worms multicast malicious packets was proposed. However, the greater the number of servers to be protected increases the cost of the malicious process control system, and the probability of detecting Internet worms attacking only some predetermined IP addresses is low. This paper presents a security framework that can reduce the cost of the malicious process control system and increase the probability of detecting Internet worms attacking only some predetermined IP addresses. In the proposed security framework, virtual machines are used to reduce the cost of control servers and unused IP addresses are used to increase the probability of detecting Internet worms attacking only some predetermined IP addresses. Therefore the proposed security framework can effectively respond to a variety of new Internet worms at lower cost.

• Journal of Advanced Navigation Technology
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• v.16 no.1
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• pp.41-53
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• 2012

The technologies used by the malicious codes have been being advanced and complicated through a merge of the existing techniques, while the damages by the malicious codes are moving from individuals and industries to organizations and countries. In this situation, the security experts are corresponding with the static analysis and the dynamic analysis such as signature searching and reverse engineering, respectively. However, they have had a hard time to respond against the obfuscated intelligent new zero day malicious codes. Therefore, it is required to prepare a process for a preliminary investigation and consequent detailed investigation on the infection sequence and the hiding mechanism to neutralize the malicious code. In this paper, we studied the formalization of the process against the infection sequence and the file hiding techniques with an empirical application to the Rustock malicious code that is most notorious as a spammer. Using the result, it is expected to promptly respond to newly released malicious codes.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.3
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• pp.617-623
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• 2018

This study focuses on detection of malicious code through AndroidManifest permissoion feature extracted based on Android static analysis. Features are built on the permissions of AndroidManifest, which can save resources and time for analysis. Malicious app detection model consisted of SVM (support vector machine), NB (Naive Bayes), Gradient Boosting Classifier (GBC) and Logistic Regression model which learned 1,500 normal apps and 500 malicious apps and 98% detection rate. In addition, malicious app family identification is implemented by multi-classifiers model using algorithm SVM, GPC (Gaussian Process Classifier) and GBC (Gradient Boosting Classifier). The learned family identification machine learning model identified 92% of malicious app families.

• 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.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.1
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• pp.213-219
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• 2011

Due to the rapid growth of smartphone market, the security threats are also increased. One of the smartphone security threats is that w1Verified applications are distributed on the smartphone market. In the case of Andoroid market, Google have no Application Approval Process that can detect malicious android application so many malicious android applications are distributed in the Android market. To reduce this security threat, it is essential the skill to detect the malicious activities of application. In this paper, we propose the android application analysis method for malicious activity detection and we introduce the implementation of our method which can automatically analyze the android application.