• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.3
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• pp.501-511
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• 2022

In 2021, ransomware attacks became popular, and the number is rapidly increasing every year. Since PowerShell is used as the primary ransomware technique, the need for PowerShell-based malware detection is ever increasing. However, the existing detection techniques have limits in that they cannot detect obfuscated scripts or require a long processing time for deobfuscation. This paper proposes a simple and fast deobfuscation method and a deep learning-based classification model that can detect PowerShell-based malware. Our technique is composed of Word2Vec and a convolutional neural network to learn the meaning of a script extracting important features. We tested the proposed model using 1400 malicious codes and 8600 normal scripts provided by the AI-based PowerShell malicious script detection track of the 2021 Cybersecurity AI/Big Data Utilization Contest. Our method achieved 5.04 times faster deobfuscation than the existing methods with a perfect success rate and high detection performance with FPR of 0.01 and TPR of 0.965.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.827-835
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• 2022

In order to use online financial services, user authentication technology is necessary. Password check through keyboard typing is the most common technique. However, since it became known that key stokes on the keyboard can be intercepted easily, many Internet banking services and easy payment services have adopted the virtual keyboard. However, contrary to the expectation that the virtual keyboard will be safe, there is a risk that key strokes on the virtual keyboard can be leaked. In this paper, we analyzed the possibility of password leaking on the virtual keyboard and presented a password leaking method using mouse event hooking and screen capture in PC operating system. In addition, we inspected the possibility of password leak attacks on several famous Korea Internet banking websites and simple payment services, and as a result, we verified that the password input method through the virtual keyboard in the PC operating system is not secure.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.19-26
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• 2023

Critical information infrastructure designations for cloud service providers continue to spread around the world as energy, financial services, health, telecommunications, and transportation sectors move to the cloud. In addition, in the case of Ukraine, the removal of restrictions on the use of cloud for national critical facilities and the rapid transition of critical data to the cloud enabled the country to effectively respond to cyberattacks targeting Russian infrastructure. In Korea, the ISMS-P is operated to implement a systematic and comprehensive information protection management system and to improve the level of information protection and personal information protection management in organizations. Control items considering the cloud environment have been modified and added to the audit of companies. However, due to the different technical levels of clouds between domestic and global, it is not easy to obtain information on the findings of cloud providers such as Microsoft for the training of domestic certification auditors on hyperscale scale. Therefore, this paper analyzes findings in hyperscale clouds and suggests ways to improve cloud-specific control items by considering the compatibility of hyperscale environments with ISO/IEC 27001 and SOC(System and Organization Control) security international standards.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.5
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• pp.165-170
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• 2023

With the recent rise of blockchain technology, cryptocurrency platforms using it are increasing, and currency transactions are being actively conducted. However, crimes that abuse the characteristics of cryptocurrency are also increasing, which is a problem. In particular, phishing scams account for more than a majority of Ethereum cybercrime and are considered a major security threat. Therefore, effective phishing scams detection methods are urgently needed. However, it is difficult to provide sufficient data for supervised learning due to the problem of data imbalance caused by the lack of phishing addresses labeled in the Ethereum participating account address. To address this, this paper proposes a phishing scams detection method that uses both Trans2vec, an effective graph embedding techique considering Ethereum transaction networks, and semi-supervised learning model Tri-training to make the most of not only labeled data but also unlabeled data.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.6A
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• pp.163-177
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• 2008

As many companies are considering to use server virtualization technology to reduce cost, the crime rates in virtual server environment are expected to be increasing rapidly. The server virtualization solution has a basic function to produce virtual machine images without using any other disk imaging tools, so that investigating virtual servers are more efficient because the investigator only has to collect the virtual machine image and submit it to the court. However, the virtual machine image has no admissibility to be the legal evidence because of security, authenticity, procedural problems in collecting virtual machine images on virtual servers. In this research, we are going to provide requirements to satisfy security, authenticity and chain of custody conditions for the admissibility of the virtual machine image in server virtualization environment. Additionally, we suggest definite roles and driving plans for related organizations to produce virtual machine image as a admissible evidence.

• The Journal of Society for e-Business Studies
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• v.26 no.4
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• pp.37-52
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• 2021

Due to the spread of COVID-19, it is rapidly changing from face-to-face to non-face-to-face work environments and is changing to a digital work environment that can be accessed anytime, anywhere, providing convenience to all lives. However, the number of breaches, personal information leakage, and technology leakage targeting SMEs that are vulnerable to security continues to increase. Accordingly, the government has been continuously promoting the information security consulting support project for SMEs every year since 2014. Therefore, this study intends to develop a performance model and measurement methodology for continuous and more systematic support and efficient management of information protection support projects in consideration of the importance of information security for SMEs. It is intended to be used as basic data when setting future operational directions and goals. The main method of this study is to derive performance models and indicators for SME information security support projects based on domestic literature, case studies, and survey results, utilize expert advice to verify the developed performance measurement indicators, and use pilot-test questionnaires. Conduct evaluation through surveys. Based on the verified indicators, we would like to present a performance model and measurement index for the information security support project for SMEs.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.317-326
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• 2024

Biometric recognition is a technology that determines whether a person is identified by extracting information on a person's biometric and behavioral characteristics with a specific device. Cyber threats such as forgery, duplication, and hacking of biometric characteristics are increasing in the field of biometrics. In response, the security system is strengthened and complex, and it is becoming difficult for individuals to use. To this end, multiple biometric models are being studied. Existing studies have suggested feature fusion methods, but comparisons between feature fusion methods are insufficient. Therefore, in this paper, we compared and evaluated the fusion method of multiple biometric models using fingerprint, face, and iris images. VGG-16, ResNet-50, EfficientNet-B1, EfficientNet-B4, EfficientNet-B7, and Inception-v3 were used for feature extraction, and the fusion methods of 'Sensor-Level', 'Feature-Level', 'Score-Level', and 'Rank-Level' were compared and evaluated for feature fusion. As a result of the comparative evaluation, the EfficientNet-B7 model showed 98.51% accuracy and high stability in the 'Feature-Level' fusion method. However, because the EfficietnNet-B7 model is large in size, model lightweight studies are needed for biocharacteristic fusion.

• Journal of Navigation and Port Research
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• v.46 no.6
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• pp.554-561
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• 2022

Technology development related to maritime autonomous surface ships (MASS) is actively progressing around the world. However, since there are still many technically unresolved problems such as communication, cybersecurity, and emergency response capabilities, it is expected that it will take a lot of time for MASS to be commercialized. In this study, we proposed a ship group navigation system in which one leader ship and several follower ship are grouped into one group. In this system, when the leader ship begins to navigate, the follower ship autonomously follows the path of the leader ship. For path following, PD (proportional-derivative) control is applied. In addition, each ship navigates in a straight line shape while maintaining a safe distance to prevent collisions. Speed control was implemented to maintain a safe distance between ships. Simulations were performed to verify the ship group navigation system. The ship used in the simulation is the L-7 model of KVLCC2, which has related data disclosed. And the MMG (Maneuvering Modeling Group) standard method proposed by the Japan Society of Naval Architects and Ocean Engineering (JASNAOE) was used as a model of ship maneuvering motion. As a result of the simulation, the leader ship navigated along a predetermined route, and the follower ship navigated along the leader ship's path. During the simulation, it was found that the three ships maintained a straight line shape and a safe distance between them. The ship group navigation system is expected to be used as a navigation system to solve the problems of MASS.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.3
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• pp.585-600
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• 2012

Security issues in online games are increasing as the online game industry grows. Real money trading (RMT) by online game users has become a security issue in several countries including Korea because RMT is related to criminal activities such as money laundering or tax evasion. RMT-related activities are done by professional work forces, namely gold-farmers, and many of them employ the automated program, bot, to gain cyber asset in a quick and efficient way. Online game companies try to prevent the activities of gold-farmers using game bots detection algorithm and block their accounts or IP addresses. However, game bot detection algorithm can detect a part of gold-farmer's network and IP address blocking also can be detoured easily by using the virtual private server or IP spoofing. In this paper, we propose a method to detect gold-farmer groups by analyzing their connection patterns to the online game servers, particularly information on their routing and source locations. We verified that the proposed method can reveal gold-farmers' group effectively by analyzing real data from the famous MMORPG.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.4
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• pp.785-802
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• 2017

As cyber threats using malicious code continue to increase, many security and vaccine companies are putting a lot of effort into analysis and detection of malicious codes. However, obfuscation techniques that make software analysis more difficult are applied to malicious codes, making it difficult to respond quickly to malicious codes. In particular, commercial obfuscation tools can quickly and easily generate new variants of malicious codes so that malicious code analysts can not respond to them. In order for analysts to quickly analyze the actual malicious behavior of the new variants, reverse obfuscation(=de-obfuscation) is needed to disable obfuscation. In this paper, general analysis methodology is proposed to de-obfuscate the software used by a commercial obfuscation tool, Themida. First, We describe operation principle of Themida by analyzing obfuscated executable file using Themida. Next, We extract original code and data information of executable from obfuscated executable using Pintool, DBI(Dynamic Binary Instrumentation) framework, and explain the implementation results of automated analysis tool which can deobfuscate to original executable using the extracted original code and data information. Finally, We evaluate the performance of our automated analysis tool by comparing the original executable with the de-obfuscated executable.