• 한국인터넷방송통신학회논문지
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• 제20권3호
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• pp.195-200
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• 2020

무선랜은 사용의 편리함으로 인해 점차 많은 분야에 걸쳐 활용되고 있다. 무선랜의 가장 큰 장점은 무엇보다도 이동성에 있다고 할 수 있다. 국내 유선 인터넷 서비스는 '06년을 기점으로 포화상태에 있지만, 무선 인터넷 사용자는 꾸준한 증가세를 보이고 있다. 하지만 무선랜은 많은 장점과 동시에 무선 서비스의 특성 상 존재하게 되는 다수의 보안 취약점을 가지고 있으며, 이런 문제점을 해결하기 위해 다양한 보안관련 기술이 개발 및 적용되고 있다. 하지만 그에 반해 무선랜 사용자의 보안인식은 여전히 부족한 상태로, 매년 개인정보유출 등의 보안사고가 반복적으로 발생하고 있는 상황이다. 무선랜에서 발생할 수 있는 주요 취약점을 연구하고, 그에 대한 관리차원에서의 보안대책을 제시하고자 한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권12호
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• pp.5654-5668
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• 2018

Driven by security and real-time demands of Internet of Things (IoT), the timing of fog computing and edge computing have gradually come into place. Gateways bear more nearby computing, storage, analysis and as an intelligent broker of the whole computing lifecycle in between local devices and the remote cloud. In fog computing, the edge broker requires X-aware capabilities that combines software programmability, stream processing, hardware optimization and various connectivity to deal with such as security, data abstraction, network latency, service classification and workload allocation strategy. The prosperous of Field Programmable Gate Array (FPGA) pushes the possibility of gateway capabilities further landed. In this paper, we propose a software-defined gateway (SDG) scheme for fog computing paradigm termed as Fog Computing Zero-Knowledge Gateway that strengthens data protection and resilience merits designed for industrial internet of things or highly privacy concerned hybrid cloud scenarios. It is a proxy for fog nodes and able to integrate with existing commodity gateways. The contribution is that it converts Privacy-Enhancing Technologies rules into provable statements without knowing original sensitive data and guarantees privacy rules applied to the sensitive data before being propagated while preventing potential leakage threats. Some logical functions can be offloaded to any programmable micro-controller embedded to achieve higher computing efficiency.

• 인터넷정보학회논문지
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• 제22권5호
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• pp.27-33
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• 2021

With the broad adoption of the Internet of Things (IoT) in a variety of scenarios and application services, management and orchestration entities require upgrading the traditional architecture and develop intelligent models with ultra-reliable methods. In a heterogeneous network environment, mission-critical IoT applications are significant to consider. With erroneous priorities and high failure rates, catastrophic losses in terms of human lives, great business assets, and privacy leakage will occur in emergent scenarios. In this paper, an efficient resource slicing scheme for optimizing federated learning in software-defined IoT (SDIoT) is proposed. The decentralized support vector regression (SVR) based controllers predict the IoT slices via packet inspection data during peak hour central congestion to achieve a time-sensitive condition. In off-peak hour intervals, a centralized deep neural networks (DNN) model is used within computation-intensive aspects on fine-grained slicing and remodified decentralized controller outputs. With known slice and prioritization, federated learning communications iteratively process through the adjusted resources by virtual network functions forwarding graph (VNFFG) descriptor set up in software-defined networking (SDN) and network functions virtualization (NFV) enabled architecture. To demonstrate the theoretical approach, Mininet emulator was conducted to evaluate between reference and proposed schemes by capturing the key Quality of Service (QoS) performance metrics.

• 한국컴퓨터정보학회논문지
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• 제20권6호
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• pp.43-50
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• 2015

In order to protect important information of smart phone from these security threats, this paper has studied a mechanism for protecting information from the leakage of various information and personal information stored in the smart phone. This paper has configured the basic protection scope for the information protection and applied real time encodement when new contents were created. Also, this paper has applied a security function so that the content of the protected scope can be managed and erased remotely in preparation for loss and burglary.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권2호
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• pp.495-513
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• 2020

The correlation identification of the subsurface is a novel electrical prospecting method which could suppress stochastic noise. This method is increasingly being utilized by geophysicists. It achieves the frequency response of the underground media through division of the cross spectrum of the input & output signal and the auto spectrum of the input signal. This is subject to the spectral leakage when the cross spectrum and the auto spectrum are computed from cross correlation and autocorrelation function by Discrete Fourier Transformation (DFT, "To obtain an accurate frequency response of the earth system, we propose an improved correlation identification method which uses all phase Fast Fourier Transform (APFFT) to acquire the cross spectrum and the auto spectrum. Simulation and engineering application results show that compared to existing correlation identification algorithm the new approach demonstrates more precise frequency response, especially the phase response of the system under identification.

• International Journal of Internet, Broadcasting and Communication
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• 제12권1호
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• pp.90-94
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• 2020

Artificial intelligence (AI) is software that learns large amounts of data and provides the desired results for certain patterns. In other words, learning a large amount of data is very important, and the role of memory in terms of computing systems is important. Massive data means wider bandwidth, and the design of the memory system that can provide it becomes even more important. Providing wide bandwidth in AI systems is also related to power consumption. AlphaGo, for example, consumes 170 kW of power using 1202 CPUs and 176 GPUs. Since more than 50% of the consumption of memory is usually used by system chips, a lot of investment is being made in memory technology for AI chips. MRAM, PRAM, ReRAM and Hybrid RAM are mainly studied. This study presents various memory technologies that are being studied in artificial intelligence chip design. Especially, MRAM and PRAM are commerciallized for the next generation memory. They have two significant advantages that are ultra low power consumption and nearly zero leakage power. This paper describes a comparative analysis of the four representative new memory technologies.

• International Journal of Internet, Broadcasting and Communication
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• 제10권4호
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• pp.25-30
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• 2018

When producing a business card, there is always a risk for exposing personal information as the information from the business card application is saved in the computer of the printing agency. The information that goes into the business card application file, such as name, mobile phone number, and e-mail address is not encrypted, which makes it easy to access. This study was conducted in order to find a way to automatize the business card application process by encrypting the information entered into the business card application file, simplifying the business card application process, minimizing the workload and by directly linking to the print shop to remove the print file after completing the printing of the business card.

• 한국IT서비스학회지
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• 제7권3호
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• pp.175-198
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• 2008

The wide spread of the Internet has become a momentum to promote informatization, and thus individuals, organizations, and government bodies are competitively participating in this kind of new wave. Informatization enables us not only to circulate and utilize information without any limitation but also to maximize users' benefits and convenience. On the other hand, it brings about negative effects-security incidents such as cyber terror, Internet fraud and technology leakage, etc. Evaluation on security level should precede over all the others in order to minimize damage by security incidents since it diagnoses current status on security as it is and can be used as a guideline for appropriate security management. In this study, evaluation domains, items and indicators of information security to evaluate information security are theoretically developed on the basis of critically reviewing the major existing research. And then the coincidence level(content validity, ease and reliability of evaluation) of each evaluation indicators are empirically analyzed through performing the field study of 83 information security experts.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권4호
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• pp.2198-2222
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• 2019

The cloud storage service becomes a rising trend based on the cloud computing, which promotes the remote data integrity auditing a hot topic. Some research can audit the integrity and correctness of user data and solve the problem of user privacy leakage. However, these schemes cannot use fewer data blocks to achieve better auditing results. In this paper, we figure out that the random sampling used in most auditing schemes is not well apply to the problem of cloud service provider (CSP) deleting the data that users rarely use, and we adopt the probability proportionate to size sampling (PPS) to handle such situation. A new scheme named improving audit efficiency of remote data for cloud storage is designed. The proposed scheme supports the public auditing with fewer data blocks and constrains the server's malicious behavior to extend the auditing cycle. Compared with the relevant schemes, the experimental results show that the proposed scheme is more effective.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권5호
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• pp.2718-2731
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• 2019

Conjunctive keyword search encryption is an important technique for protecting sensitive data that is outsourced to cloud servers. However, the process of searching outsourced data may facilitate the leakage of sensitive data. Thus, an efficient data search approach with high security is critical. To solve this problem, an efficient conjunctive keyword search scheme based on ciphertext-policy attribute-based encryption is proposed for cloud storage environment. This paper proposes an efficient mechanism for removing the secure channel and resisting off-line keyword-guessing attacks. The storage overhead and the computational complexity are regardless of the number of keywords. This scheme is proved adaptively secure based on the decisional bilinear Diffie-Hellman assumption in the standard model. Finally, the results of theoretical analysis and experimental simulation show that the proposed scheme has advantages in security, storage overhead and efficiency, and it is more suitable for practical applications.