• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.1-9
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• 2023

Malware files containing concealed malicious scripts have recently been identified within MS Office documents frequently. In response, this paper describes the design and implementation of a system that automatically detects malicious digital files using machine learning techniques. The system is proficient in identifying malicious scripts within MS Office files that exploit the OLE VBA macro functionality, detecting malicious scripts embedded within the CDH/LFH/ECDR internal field values through OOXML structure analysis, and recognizing abnormal CDH/LFH information introduced within the OOXML structure, which is not conventionally referenced. Furthermore, this paper presents a mechanism for utilizing the VirusTotal malicious script detection feature to autonomously determine instances of malicious tampering within MS Office files. This leads to the design and implementation of a machine learning-based integrated software. Experimental results confirm the software's capacity to autonomously assess MS Office file's integrity and provide enhanced detection performance for arbitrary MS Office files when employing the optimal machine learning model.

• Journal of Advanced Navigation Technology
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• v.28 no.1
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• pp.27-36
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• 2024

In this paper, we analyze the unified requirements of international association of classification societies - cyber resilience of ships, ahead of implementation of the agreement on July 1, 2024, and respond to ship cyber security and resilience programs based on 5 requirements, 17 details, and documents that must be submitted or maintained according to the ship's cyber resilience,. Measures include document management such as classification certification documents and design documents, configuration of a network with enhanced security, establishment of processes for accident response, configuration management using software tools, integrated network management, malware protection, and detection of ship network security threats with security management solutions. proposed a technology capable of real-time response.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.125-139
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• 2013

Distribution of malicious applications developed by attackers is increasing along with general normal applications due to the openness of the Android-based open market. Mechanism that allows more accurate ways to distinguish normal apps and malicious apps for common mobile devices should be developed in order to reduce the damage caused by the rampant malicious applications. This paper analysed the normal event pattern from the most highly used game apps in the Android open market to analyse the event pattern from normal apps and malicious apps of mobile devices that are based on the Android platform, and analysed the malicious event pattern from the malicious apps and the disguising malicious apps in the form of a game app among 1260 malware samples distributed by Android MalGenome Project. As described, experiment that extracts normal app and malicious app events was performed using Strace, the Linux-based system call extraction tool, targeting normal apps and malicious apps on Android-based mobile devices. Relevance analysis for each event set was performed on collected events that occurred when normal apps and malicious apps were running. This paper successfully extracted event similarity through this process of analyzing the event occurrence characteristics, pattern and distribution on each set of normal apps and malicious apps, and lastly suggested a mechanism that determines whether any given app is malicious.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.2
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• pp.295-310
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• 2014

DCS (Distributed Control System), the main control system of power plants, is an automated system for enhancing operational efficiency by monitoring, tuning and real-time operation. DCS is becoming more intelligent and open systems as Information technology are evolving. In addition, there are a large amount of investment to enable proactive facility management, maintenance and risk management through the predictive diagnostics. However, new upcoming weaponized malware, such as Stuxnet designed for disrupting industrial control system(ICS), become new threat to the main control system of the power plant. Even though these systems are not connected with any other outside network. The main control systems used in the power plant usually have been used for more than 10 years. Also, this system requires the extremely high availability (rapid recovery and low failure frequency). Therefore, installing updates including security patches is not easy. Even more, in some cases, installing security updates can break the warranty by the vendor's policy. If DCS is exposed a potential vulnerability, serious concerns are to be expected. In this paper, we conduct the penetration test by using NESSUS, a general-purpose vulnerability scanner under the simulated environment configured with the Ovation version 1.5. From this result, we suggest a log analysis method to detect the security infringement and react the incident effectively.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.657-667
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• 2020

The Android framework allows apps to take full advantage of personal information through granting single permission, and does not determine whether the data being leaked is actual personal information. To solve these problems, we propose a tool with static/dynamic analysis. The tool analyzes the Source and Sink used by the target app, to provide users with information on what personal information it used. To achieve this, we extracted the Source and Sink through Control Flow Graph and make sure that it leaks the user's privacy when there is a Source-to-Sink flow. We also used the sensitive permission information provided by Google to obtain information from the sensitive API corresponding to Source and Sink. Finally, our dynamic analysis tool runs the app and hooks information from each sensitive API. In the hooked data, we got information about whether user's personal information is leaked through this app, and delivered to user. In this process, an automated Source/Sink classification model was applied to collect latest Source/Sink information, and the we categorized latest release version of Android(9.0) with 88.5% accuracy. We evaluated our tool on 2,802 APKs, and found 850 APKs that leak personal information.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.5
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• pp.871-883
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• 2014

New types of attacks that mainly compromise the public, portal and financial websites for the purpose of economic profit or national confusion are being emerged and evolved. In addition, in case of 'drive by download' attack, if a host just visits the compromised websites, then the host is infected by a malware. Website falsification detection system is one of the most powerful solutions to cope with such cyber threats that try to attack the websites. Many domestic CERTs including NCSC (National Cyber Security Center) that carry out security monitoring and response service deploy it into the target organizations. However, the existing techniques for the website falsification detection system have practical problems in that their time complexity is high and the detection accuracy is not high. In this paper, we propose website falsification detection system based on image and code analysis for improving the performance of the security monitoring and response service in CERTs. The proposed system focuses on improvement of the accuracy as well as the rapidity in detecting falsification of the target websites.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.4
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• pp.61-75
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• 2011

Recently, there is significant increasing of massive attacks, which try to infect PCs that visit websites containing pre-implanted malicious code. When visiting the websites, these hidden malicious codes can gain monetary profit or can send various cyber attacks such as BOTNET for DDoS attacks, personal information theft and, etc. Also, this kind of malicious activities is continuously increasing, and their evasion techniques become professional and intellectual. So far, the current signature-based detection to detect websites, which contain malicious codes has a limitation to prevent internet users from being exposed to malicious codes. Since, it is impossible to detect with only blacklist when an attacker changes the string in the malicious codes proactively. In this paper, we propose a novel approach that can detect unknown malicious code, which is not well detected by a signature-based detection. Our method can detect new malicious codes even though the codes' signatures are not in the pattern database of Anti-Virus program. Moreover, our method can overcome various obfuscation techniques such as the frequent change of the included redirection URL in the malicious codes. Finally, we confirm that our proposed system shows better detection performance rather than MC-Finder, which adopts pattern matching, Google's crawling based malware site detection, and McAfee.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.3
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• pp.499-510
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• 2023

Recently, an intelligent and advanced cyber attack attacks a computer network of a public institution using a file containing malicious code or leaks information, and the damage is increasing. Even in public institutions with various information protection systems, known attacks can be detected, but unknown dynamic and encryption attacks can be detected when existing signature-based or static analysis-based malware and ransomware file detection methods are used. vulnerable to The detection method proposed in this study extracts the detection result data of the system that can detect malicious code and ransomware among the information protection systems actually used by public institutions, derives various attributes by combining them, and uses a machine learning classification algorithm. Results are derived through experiments on how the derived properties are classified and which properties have a significant effect on the classification result and accuracy improvement. In the experimental results of this paper, although it is different for each algorithm when a specific attribute is included or not, the learning with a specific attribute shows an increase in accuracy, and later detects malicious code and ransomware files and abnormal behavior in the information protection system. It is expected that it can be used for property selection when creating algorithms.

• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.7
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• pp.1-8
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• 2017

As the IT environment becomes more sophisticated, various threats and their associated serious risks are increasing. Threats such as DDoS attacks, malware, worms, and APT attacks can be a very serious risk to enterprises and must be efficiently managed in a timely manner. Therefore, the government has designated the important system as the main information communication infrastructure in consideration of the impact on the national security and the economic society according to the 'Information and Communication Infrastructure Protection Act', which, in particular, protects the main information communication infrastructure from cyber infringement. In addition, it conducts management supervision such as analysis and evaluation of vulnerability, establishment of protection measures, implementation of protection measures, and distribution of technology guides. Even now, security consulting is proceeding on the basis of 'Guidance for Evaluation of Technical Vulnerability Analysis of Major IT Infrastructure Facilities'. There are neglected inspection items in the applied items, and the vulnerability of APT attack, malicious code, and risk are present issues that are neglected. In order to eliminate the actual security risk, the security manager has arranged the inspection and ordered the special company. In other words, it is difficult to check against current hacking or vulnerability through current system vulnerability checking method. In this paper, we propose an efficient method for extracting diagnostic data regarding the necessity of upgrading system vulnerability check, a check item that does not reflect recent trends, a technical check case for latest intrusion technique, a related study on security threats and requirements. Based on this, we investigate the security vulnerability management system and vulnerability list of domestic and foreign countries, propose effective security vulnerability management system, and propose further study to improve overseas vulnerability diagnosis items so that they can be related to domestic vulnerability items.