• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.374-376
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• 2022

The Malware App Analysis Tool is a system that analyzes Android-based apps by the AI-based algorithm defined in the tool and detects whether malware code is included. Currently, as the spred of smartphones is activated, crimes using malware apps have increased, and accordingly, security for malware apps is required. Android operating systems used in smartphones have a share of more than 70% and are open-source-based, so not only will there be many vulnerabilities and malware, but also more damage to malware apps, increasing demand for tools to detect and analyze malware apps. However, this paper is proposed because there are many difficulties in designing and developing a malware app analysis tool because the security functional requirements for the malware app analysis tool are not clearly specified. Through the developed protection profile, technology can be improved based on the design and development of malware app analysis tools, safety can be secured by minimizing damage to malware apps, and furthermore, trust in malware app analysis tools can be guaranted through common criteria.

• Journal of Practical Engineering Education
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• v.15 no.3
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• pp.641-647
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• 2023

In the fintech environment, ensuring secure financial transactions with smartphones requires authenticating the device owner. Smartphone authentication techniques encompass a variety of approaches, such as passwords, biometrics, SMS authentication, and more. Among these, password-based authentication is commonly used and highly convenient for user authentication. Although it is a simple authentication mechanism, it is susceptible to eavesdropping and keylogging attacks, alongside other threats. Security keypads have been proposed to address vulnerabilities in password input on smartphones. One such innovation is a group keypad, resistant to attacks that guess characters based on touch location. However, improvements are needed for user convenience. In this study, we aim to propose a method that enhances convenience while being resistant to eavesdropping and recording attacks on the existing group keypad. The proposed method uses new signs to allow users to verify instead of the last character confirmation easily and employs dragging-to-touch for blocking recording attacks. We suggest diverse positioning methods tailored for domestic users, improving efficiency and security in password input compared to existing methods.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.1021-1031
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• 2023

State-sponsored cyber attacks are highly impactful because they are carried out to achieve pre-planned goals. As a defender, it is difficult to respond to them because of the large scale of the attack and the possibility that unknown vulnerabilities may be exploited. In addition, overreacting can reduce the availability of users and cause business disruption. Therefore, there is a need for a response policy that can effectively defend against attacks while ensuring user availability. To solve this problem, this paper proposes a method to collect the number of processes and sessions of defense assets in real time and use them for learning. Using this method to learn reinforcement learning-based policies on a cyber attack simulator, the attack duration based on 100 time-steps was reduced by 27.9 time-steps and 3.1 time-steps for two attacker models, respectively, and the number of "restore" actions that impede user availability during the defense process was also reduced, resulting in an overall better policy.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.147-156
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• 2023

Electronic voting machines (EVMs) are replacing research ballots due to the errors involved in the manual counting process and the lengthy time required to count the votes. Even though these digital recording electronic systems are advancements, they are vulnerable to tampering and electoral fraud. The suspected vulnerabilities in EVMs are the possibility of tampering with the EVM's memory chip or replacing it with a fake one, their simplicity, which allows them to be tampered with without requiring much skill, and the possibility of double voting. The vote data is shared among all network devices, and peer-to-peer verification is performed to ensure the vote data's authenticity. To successfully tamper with the system, all of the data stored in the nodes must be changed. This improves the proposed system's efficiency and dependability. Elections and voting are fundamental components of a democratic system. Various attempts have been made to make modern elections more flexible by utilizing digital technologies. The fundamental characteristics of free and fair elections are intractability, immutability, transparency, and the privacy of the actors involved. This corresponds to a few of the many characteristics of blockchain-like decentralized ownership, such as chain immutability, anonymity, and distributed ledger. This working research attempts to conduct a comparative analysis of various blockchain technologies in development and propose a 'Blockchain-based Electronic Voting System' solution by weighing these technologies based on the need for the proposed solution. The primary goal of this research is to present a robust blockchain-based election mechanism that is not only reliable but also adaptable to current needs.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.1
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• pp.143-156
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• 2024

Federated Learning (FL) has emerged as a potent methodology for decentralized model training across multiple collaborators, eliminating the need for data sharing. Although FL is lauded for its capacity to preserve data privacy, it is not impervious to various types of privacy attacks. Differential Privacy (DP), recognized as the golden standard in privacy-preservation techniques, is widely employed to counteract these vulnerabilities. This paper makes a specific contribution by applying an existing, task-specific adaptive DP mechanism to the FL environment. Our comprehensive analysis evaluates the impact of this mechanism on the performance of a shared global model, with particular attention to varying data distribution and partitioning schemes. This study deepens the understanding of the complex interplay between privacy and utility in FL, providing a validated methodology for securing data without compromising performance.

• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.111-118
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• 2024

In general network-based intrusion detection system is designed to detect malicious behavior directed at a network or its resources. The key goal of this paper is to look at network data and identify whether it is normal traffic data or anomaly traffic data specifically for accounting information systems. In today's world, there are a variety of principles for detecting various forms of network-based intrusion. In this paper, we are using supervised machine learning techniques. Classification models are used to train and validate data. Using these algorithms we are training the system using a training dataset then we use this trained system to detect intrusion from the testing dataset. In our proposed method, we will detect whether the network data is normal or an anomaly. Using this method we can avoid unauthorized activity on the network and systems under that network. The Decision Tree and K-Nearest Neighbor are applied to the proposed model to classify abnormal to normal behaviors of network traffic data. In addition to that, Logistic Regression Classifier and Support Vector Classification algorithms are used in our model to support proposed concepts. Furthermore, a feature selection method is used to collect valuable information from the dataset to enhance the efficiency of the proposed approach. Random Forest machine learning algorithm is used, which assists the system to identify crucial aspects and focus on them rather than all the features them. The experimental findings revealed that the suggested method for network intrusion detection has a neglected false alarm rate, with the accuracy of the result expected to be between 95% and 100%. As a result of the high precision rate, this concept can be used to detect network data intrusion and prevent vulnerabilities on the network.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.4
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• pp.801-809
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• 2024

In the digital age, the importance of personal information has magnified, underscoring the need for enhanced personal information protection, especially within public institutions. Despite ongoing efforts since 2007, significant breaches in public sector information underline persistent vulnerabilities. This study advocates for a transition from a diagnostic to an assessment framework to fortify privacy management in public institutions, as mandated by recent legislative revisions. The amended Personal Information Protection Act introduces an assessment approach, aiming to comprehensively assess and mitigate risks by expanding the scope of evaluation and implementing robust regulatory measures. This study examines the limitations of the current diagnostic practices through literature review and case analysis and proposes a systematic approach to adopting the new assesment system. By enhancing the assessment framework, the study expects to improve the effectiveness of personal information management in public institutions, thereby restoring public trust and ensuring a stable progression into a more secure digital era. The transition to an assessment system is designed not only to address the gaps in the current framework but also to provide a methodical assessment that supports ongoing improvement and compliance with enhanced legal standards.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.4
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• pp.811-831
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• 2024

This paper has two main objectives. The primary objective is to conduct a comprehensive review of existing survey papers on the advantages, disadvantages, taxonomy, and technical vulnerabilities of cryptocurrency custody services. Additionally, we examined recent regulatory developments, the application of existing frameworks, conditions for performing custody services, and service providers' obligations. The secondary objective is to identify DeFi protocols in the regulatory 'grey area' and analyze their technical aspects and governance mechanisms. By synthesizing these findings, we propose guidelines for assessing DeFi decentralization and their potential for integration within the regulatory framework, providing insights for industry experts, regulators, and policymakers to balance industry needs with societal benefits.

• Korean Security Journal
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• no.10
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• pp.189-213
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• 2005

Risk management should be controlled systematically by effectively evaluating and suggesting countermeasures against the various risks which are followed by the change of the society and environment. These days, enterprise risk management became a new trend in the field. The first step in risk analysis is to recognize the risk factors, that is to verify the vulnerabilities of loss in the security facilities. The second step is to consider the probability of loss in assessing the risk factors. And the third step is to evaluate the criticality of loss. The security manager will determine the assessment grades and then the risk levels of each risk factor, on the basis of the result of risk analysis which includes the assessment of vulnerability, the provability of loss and the criticality. It is of great importance to put the result of risk analysis in mathematical statement for a scientific approach to risk management. Using the risk levels gained from the risk analysis, the security manager can develop a comprehensive and supplementary security plan. In planning the risk management measures to prepare against and minimize the loss, insurance is one of the best loss-prevention programs. However, insurance in and of itself is no longer able to meet the security challenges faced by major corporations. The security manager have to consider the cost-effectiveness, to suggest the productive risk management alternatives by using the security files which contains every information about the security matters. Also he/she have to reinforce the company regulations on security and safety, and to execute education repeatedly on security and risk management. Risk management makes the most efficient before-the-loss arrangement for and after-the-loss continuation of a business. So it is very much important to suggest a best cost-effective and realistic alternatives for optimizing risk management above all, and this function should by maintained and developed continuously and repeatedly.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.136-141
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• 2006

The IEEE 802.1x can be using various user authentication mechanisms: One-Time Password, Certificate-Based TLS, Challenge/Response and Keberos through EAP(Extended Authentication Protocol). But, IEEE 802.1x also has vulnerabilities about the DoS, the session hijacking and the Man in the Middle attack due to the absence of AP authentication. In this paper, we propose a WLAN secure system which can offer a safety secure communication and a user authentications by intensified the vulnerability of spoofing and DoS attacks. The suppose system offers a safe secure communication because it offers sending message of integrity service and also it prevents DoS attack at authentication initial phase.