• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.4
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• pp.255-261
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• 2011

In this paper, we propose a security-enhanced storing method for the voice data obtained during the flight. When an emergency occurs during flight, the flight data in the storage device such as DTS or Blackbox can be exposed to antagonist or enemy. Currently, zeroize function is embedded in these devices in order to prevent this situation. However, this could not be operated if the system is malfunctioned or the pilot is wounded in the emergency. In order to solve this problem, the voice data compressed by the ADPCM is encrypted in the proposed method composed of the AES algorithm and a reordering method. The simulation results show that the security for the voice date is further enhanced due to the proposed method.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.42-49
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• 2021

As cyber attacks become more intelligent, there is difficulty in detecting advanced attacks in various fields such as industry, defense, and medical care. IPS (Intrusion Prevention System), etc., but the need for centralized integrated management of each security system is increasing. In this paper, we collect big data for intrusion detection and build an intrusion detection platform using deep learning and CNN (Convolutional Neural Networks). In this paper, we design an intelligent big data platform that collects data by observing and analyzing user visit logs and linking with big data. We want to collect big data for intrusion detection and build an intrusion detection platform based on CNN model. In this study, we evaluated the performance of the Intrusion Detection System (IDS) using the KDD99 dataset developed by DARPA in 1998, and the actual attack categories were tested with KDD99's DoS, U2R, and R2L using four probing methods.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.6
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• pp.1525-1540
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• 2015

Due to a rapid advancement in the electronic commerce technology, the payment method varies from cash to electronic settlement such as credit card, mobile payment and mobile application card. Therefore, financial fraud is increasing notably for a purpose of personal gain. In response, financial companies are building the FDS (Fraud Detection System) to protect consumers from fraudulent transactions. The one of the goals of FDS is identifying the fraudulent transaction with high accuracy by analyzing transaction data and personal information in real-time. Data mining techniques are providing great aid in financial accounting fraud detection, so it have been applied most extensively to provide primary solutions to the problems. In this paper, we try to provide an overview of the research on data mining based fraud detection. Also, we classify researches under few criteria such as data set, data mining algorithm and viewpoint of research.

• Journal of the Korea Society of Computer and Information
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• v.16 no.4
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• pp.93-99
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• 2011

Recently, the development of internet technology makes user's personal data used by being saved in USB. But there is a critical issue that personal data can be exposed with malicious purpose because that personal data doesn't need to be certificate to use. This paper proposes USB security framework to prevent a duplicate use of personal data for protecting the data which in USB. The proposed USB security framework performs certification process of user with additional 4bite of user's identification data and usage choice of USB security token before certification data when the framework uses USB security product in different network. It makes communication overhead and service delay increased. As a result of the experiment, packet certification delay time is more increased by average 7.6% in the proposed USB security framework than simple USB driver and USB Token, and procedure rate of certification server on the number of USB is also increased by average 9.8%.

• Convergence Security Journal
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• v.24 no.1
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• pp.35-42
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• 2024

Multi-tenancy architecture plays a crucial role in cloud-based services and applications, and data isolation within such environments has emerged as a significant security challenge. This paper investigates various data isolation methods including schema-based isolation, logical isolation, and physical isolation, and compares their respective advantages and disadvantages. It evaluates the practical application and effectiveness of these data isolation methods, proposing security considerations and selection criteria for data isolation in the development of multi-tenant websites. This paper offers important guidance for developers, architects, and system administrators aiming to enhance data security in multi-tenancy environments. It suggests a foundational framework for the design and implementation of efficient and secure multi-tenant websites. Additionally, it provides insights into how the choice of data isolation methods impacts system performance, scalability, maintenance ease, and overall security, exploring ways to improve the security and stability of multi-tenant systems.

• Convergence Security Journal
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• v.15 no.4
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• pp.27-33
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• 2015

In this paper, the development level of information security technology for internet of things(Iot), big data and clo ud services is analyzed, and the detail policy is proposed to be leader in area of patents and ICT standard. The conc ept of ICT convergence is defined frist, market and current state of technology for three convergence services is the n analyzed, and finally main function and security target for each technology are presented. The evaluation criteria a nd IPR are analyzed to diagnose the level of patent and standard for the technology. From the results, even though the domestic competence is inferior compared to other advanced country, the efficient policy should be presented by using our capability for the big data and cloud. Furthermore, the technology development for the IoT and cloud is ne eded in advance considering the market-technology influence effects. In addition to, M2M security framework in IoT, data security in big data and reliable networking in cloud should be developed in advance.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.6
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• pp.1441-1455
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• 2017

In order to build a secure electric vehicle charging infrastructure, security research is required because various data including charging and payment data are transmitted in the electric vehicle charging infrastructure. However, previous researches have focused on smart grid related security research such as power system infrastructure rather than charging infrastructure for electric vehicle charging. In addition, research on charging infrastructure is still lacking, and research using a systematic methodology such as threat modeling is not yet under way. Therefore, it is necessary to apply threat modeling to identify security threats and systematically analyze security requirements to build a secure electric vehicle charging infrastructure. In this paper, we analyze the electric vehicle charging infrastructure by accurately identifying possible threats and deriving objective security requirements using threat modeling including Data Flow Diagram, STRIDE, and Attack Tree.

• Journal of Information Technology Services
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• v.21 no.4
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• pp.63-74
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• 2022

Globally researchers at medical institutions are actively sharing COHORT data of patients to develop vaccines and treatments to overcome the COVID-19 crisis. OMOP-CDM, a common data model that efficiently shares medical data research independently operated by individual medical institutions has patient personal information (e.g. PII, PHI). Although PII and PHI are managed and shared indistinguishably through de-identification or anonymization in medical institutions they could not be guaranteed at 100% by complete de-identification and anonymization. For this reason the security of the OMOP-CDM database is important but there is no detailed and specific OMOP-CDM security inspection tool so risk mitigation measures are being taken with a general security inspection tool. This study intends to study and present a model for implementing a tool to check the security vulnerability of OMOP-CDM by analyzing the security guidelines for the US database and security controls of the personal information protection of the NIST. Additionally it intends to verify the implementation feasibility by real field demonstration in an actual 3 hospitals environment. As a result of checking the security status of the test server and the CDM database of the three hospitals in operation, most of the database audit and encryption functions were found to be insufficient. Based on these inspection results it was applied to the optimization study of the complex and time-consuming CDM CSF developed in the "Development of Security Framework Required for CDM-based Distributed Research" task of the Korea Health Industry Promotion Agency. According to several recent newspaper articles, Ramsomware attacks on financially large hospitals are intensifying. Organizations that are currently operating or will operate CDM databases need to install database audits(proofing) and encryption (data protection) that are not provided by the OMOP-CDM database template to prevent attackers from compromising.

• Proceedings of the IEEK Conference
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• 2000.11a
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• pp.469-472
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• 2000

Security-related issues in mobile communications are increasing. The security requirements of mobile communications for the mobile users include authentication of the mobile user, the data confidentiality, the data confidentiality and the location privacy of mobile user. These services require security features compatible with the wireline networks. However, wireless networks have many restrictions compare to wireline networks such as the limited computational capability of mobile equipment and limited resource(bandwidth) between a mobile user and a fixed network. So, security features for IMT-2000 are designed to meet the limited capacity. In this paper, we analyze the required security features and mechanism, and design network access security feature effective for IMT-2000 Systems. The design includes security functions allocation to each system. Finally, discuss the computational power of each system based on at]coated functions to it

• KEPCO Journal on Electric Power and Energy
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• v.6 no.4
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• pp.399-404
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• 2020

There are many attempts to apply AI technology to diagnose facilities or improve the work efficiency of the power industry. The emergence of new machine learning technologies, such as deep learning, is accelerating the digital transformation of the power sector. The problem is that traditional power systems face security risks when adopting state-of-the-art AI systems. This adoption has convergence characteristics and reveals new cybersecurity threats and vulnerabilities to the power system. This paper deals with the security measures and implementations of the power system using machine learning. Through building a commercial facility operations forecasting system using machine learning technology utilizing power big data, this paper identifies and addresses security vulnerabilities that must compensated to protect customer information and power system safety. Furthermore, it provides security guidelines by generalizing security measures to be considered when applying AI.