• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2021년도 추계학술발표대회
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• pp.280-283
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• 2021

SME(small and medium sized enterprise) 환경의 스마트공장 환경에서는 실제 제조라인에서 동작하는 센서(Sensor) 및 액추에이터(Actuator)와 이를 관리하는 PLC(Programmable Logic Controller), 더불어 그러한 PLC를 제어 및 관리하는 HMI(Human-Machine Interface), 그리고 다시 PLC와 HMI를 관리하는 OT(Operational Technology)서버로 구성되어 있으며, 제어자동화를 담당하는 PLC 및 HMI는 공장운영을 위한 응용시스템인 OT서버 및 현장 자동화를 위한 로봇, 생산설비와의 직접적인 연결을 수행하고 있어서 스마트공장 환경에서 보안 기술의 개발이 중점적으로 필요한 영역이다. 이러한 SME 환경의 스마트공장 보안 내재화를 이루기 위해서는, 스마트공장 SW 및 HW 개발 단계에서 IEC 62443-4-1 Secure Product Development Lifecycle에 따른 프로세스 정립 및 IEC 62443-4-2 Component 보안 요구사항과 IEC 62443-3-3 System 보안 요구사항에 적합한 개발 방법론의 도입이 필요하다.

• 정보보호학회논문지
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• 제18권5호
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• pp.149-160
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• 2008

개인 사용자들은 정보통신 서비스 이용을 위해 필요 이상의 개인정보를 공개하므로 프라이버시를 심각하게 침해당한다. 이러한 불완전한 개인정보관리 인프라를 보완하기 위해 P3P나 EPAL, XACML 같은 개인정보보호 플랫폼 기술이 개발되고 있지만, 이들은 개별주체들을 대상으로 보호자원에 대한 접근통제정책을 적용하므로 역할기반 접근통제를 원하는 기업이나 기관에는 적합하지 않다. 본 논문에서는 프라이버시를 강화한 역할기반 접근통제 정책을 표현하는 언어를 제안한다. 제안된 프라이버시 강화형 역할기반 접근통제 정책은 XACML을 변형한 것으로, XACML의 장점인 매칭과 조건 표현을 사용하며 프라이버시를 강화하기 위해 목적, 의무사항을 별도의 엘리먼트로 표현한다. 본 논문에서는 퍼미션 배정 정책에 관한 정책언어 모델을 제안하고, 개인정보보호 법률에 기초한 정책 시나리오와 도큐먼트 인스턴스를 제공한다. 또한 사용자의 요청컨텍스트와 그에 대한 응답컨텍스트도 제공한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제4권3호
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• pp.411-427
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• 2010

Data sharing is an essential process for collaborative works particularly in the banking, finance and healthcare industries. These industries require many collaborative works with their internal and external parties such as branches, clients, and service providers. When data are shared among collaborators, security and privacy concerns becoming crucial issues and cannot be avoided. Privacy is an important issue that is frequently discussed during the development of collaborative systems. It is closely related with the security issues because each of them can affect the other. The tradeoff between privacy and security is an interesting topic that we are going to address in this paper. In view of the practical problems in the existing approaches, we propose a collaborative framework which can be used to facilitate concurrent operations, single point failure problem, and overcome constraints for two-party computation. Two secure computation protocols will be discussed to demonstrate our collaborative framework.

• ETRI Journal
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• 제34권1호
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• pp.66-75
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• 2012

This paper proposes a privacy-preserving database encryption scheme that provides access pattern hiding against a service provider. The proposed scheme uses a session key to permute indices of database records each time they are accessed. The proposed scheme can achieve access pattern hiding in situations in which an adversary cannot access the inside of the database directly, by separating the entity with an index table and data table and permuting both the index and position where the data are stored. Moreover, it is very efficient since only O(1) server computation and communication cost are required in terms of the number of the data stored. It can be applied to cloud computing, where the intermediate entities such as cloud computing service provider can violate the privacy of users or patients.

• International Journal of Contents
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• 제12권2호
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• pp.6-11
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• 2016

We developed a pilot-job based large-scale distributed computing system to support HTC and MTC, called HTCaaS (High-Throughput Computing as a Service), which helps scientists solve large-scale scientific problems in areas such as pharmaceutical domains, high-energy physics, nuclear physics and bio science. Since most of these problems involve critical data that affect the national economy and activate basic industries, data privacy is a very important issue. In this paper, we implement a privacy enhanced data security mechanism to support HTC and MTC in a large-scale distributed computing system and show how this technique affects performance in our system. With this mechanism, users can securely store data in our system.

• International Journal of Computer Science & Network Security
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• 제22권4호
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• pp.340-350
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• 2022

The big data term refers to the great volume of data and complicated data structure with difficulties in collecting, storing, processing, and analyzing these data. Big data analytics refers to the operation of disclosing hidden patterns through big data. This information and data set cloud to be useful and provide advanced services. However, analyzing and processing this information could cause revealing and disclosing some sensitive and personal information when the information is contained in applications that are correlated to users such as location-based services, but concerns are diminished if the applications are correlated to general information such as scientific results. In this work, a survey has been done over security and privacy challenges and approaches in big data. The challenges included here are in each of the following areas: privacy, access control, encryption, and authentication in big data. Likewise, the approaches presented here are privacy-preserving approaches in big data, access control approaches in big data, encryption approaches in big data, and authentication approaches in big data.

• International Journal of Computer Science & Network Security
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• 제22권12호
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• pp.1-12
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• 2022

Besides unexpected growth perceived by IoT's, the variety and volume of threats have increased tremendously, making it a necessity to introduce intrusion detections systems for prevention and detection of such threats. But Intrusion Detection and Prevention System (IDPS) inside the IoT network yet introduces some unique challenges due to their unique characteristics, such as privacy inference, performance, and detection rate and their frequency in the dynamic networks. Our research is focused on the privacy inferences of existing intrusion prevention and detection system approaches. We also tackle the problem of providing unified a solution to implement the open-source IDPS in the IoT architecture for assessing the performance of IDS by calculating; usage consumption and detection rate. The proposed scheme is considered to help implement the human health monitoring system in IoT networks

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2022년도 춘계학술발표대회
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• pp.264-267
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• 2022

Recently, federated learning (FL) has increased prominence as a viable approach for enhancing user privacy and data security by allowing collaborative multi-party model learning without exchanging sensitive data. Despite this, most present FL systems still depend on a centralized aggregator to generate a global model by gathering all submitted models from users, which could expose user privacy and the risk of various threats from malicious users. To solve these issues, we suggested a safe FL framework that employs differential privacy to counter membership inference attacks during the collaborative FL model training process and empowers blockchain to replace the centralized aggregator server.

• International Journal of Computer Science & Network Security
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• 제22권3호
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• pp.364-374
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• 2022

Health information systems (HIS) are facing security challenges on data privacy and confidentiality. These challenges are based on centralized system architecture creating a target for malicious attacks. Blockchain technology has emerged as a trending technology with the potential to improve data security. Despite the effectiveness of this technology, still HIS are suffering from a lack of data privacy and confidentiality. This paper presents a blockchain-based data storage security architecture integrated with an e-Health care system to improve its security. The study employed a qualitative research method where data were collected using interviews and document analysis. Execute-order-validate Fabric's storage security architecture was implemented through private data collection, which is the combination of the actual private data stored in a private state, and a hash of that private data to guarantee data privacy. The key findings of this research show that data privacy and confidentiality are attained through a private data policy. Network peers are decentralized with blockchain only for hash storage to avoid storage challenges. Cost-effectiveness is achieved through data storage within a database of a Hyperledger Fabric. The overall performance of Fabric is higher than Ethereum. Ethereum's low performance is due to its execute-validate architecture which has high computation power with transaction inconsistencies. E-Health care system administrators should be trained and engaged with blockchain architectural designs for health data storage security. Health policymakers should be aware of blockchain technology and make use of the findings. The scientific contribution of this study is based on; cost-effectiveness of secured data storage, the use of hashes of network data stored in each node, and low energy consumption of Fabric leading to high performance.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2011년도 추계학술대회
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• pp.817-819
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• 2011

Most of the sources of security and privacy issues in RFID technology arise from the violation of the air interface between a tag and its read. Most of the sources of security and privacy issues in RFID technology arise from the violation of the air interface between a tag and its reader. This paper will approach consideration of security analysis with cryptographic primitive based on hardware basis.