• 정보보호학회논문지
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• 제33권6호
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• pp.939-946
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• 2023

IT 기술이 급속히 발전하는 현대 초연결 환경은 네트워크 장비들이 다양해지고 네트워크 구성이 복잡해짐에 따라 사이버 공격자가 침투경로로 활용될 수 있는 공격표면(attack surface) 또한 증가하게 되었다. 이러한 환경에서 사이버 공격을 원천적으로 방어하기 위해 공격표면을 변이하는 MTD(Moving Target Defense) 기술이 연구되고 있다. 그중에 네트워크를 통해 공격이 시작됨에 따라 주요 속성 네트워크 주소를 변이하는 기술이 있으나, 대부분 운용환경이 기존 고정 IP 기반으로 운용되기 때문에 주소변이 기술이 기존 네트워크 보호체계 내에 적용되었을 때 어떠한 영향이 있는지 연구가 필요하다. 본 논문에서는 기존 네트워크 보호체계에서 네트워크 주소변이 기술이 적용되었을 때의 영향성을 연구하였고 연구 결과로서 네트워크 보호체계의 주요 시스템인 방화벽, NAC, IPS와 네트워크 주소변이 기술이 동시 적용되었을 때 운용 측면에서 고려해야 할 요소를 도출하였다. 또한 사이버 대응체계 내에서 네트워크 분석시스템과의 연동성을 위해 네트워크 주소변이 기술에서 관리해야하는 요소를 제안하였다.

• 한국컴퓨터정보학회논문지
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• 제24권9호
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• pp.35-42
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• 2019

In this paper, we propose an approach to apply network-based moving target defense into Internet of Things (IoT) networks. The IoT is a technology that provides the high interconnectivity of things like electronic devices. However, cyber security risks are expected to increase as the interconnectivity of such devices increases. One recent study demonstrated a man-in-the-middle attack in the statically configured IoT network. In recent years, a new approach to cyber security, called the moving target defense, has emerged as a potential solution to the challenge of static systems. The approach continuously changes system's attack surface to prevent attacks. After analyzing IPv4 / IPv6-based moving target defense schemes and IoT network-related technologies, we present our approach in terms of addressing systems, address mutation techniques, communication models, network configuration, and node mobility. In addition, we summarize the direction of future research in relation to the proposed approach.

• Journal of Information Processing Systems
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• 제19권4호
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• pp.450-464
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• 2023

To address the problems of large system overhead and low timeliness when dealing with task scheduling in mobile edge cloud computing, a task scheduling and resource management strategy for edge cloud computing based on an improved genetic algorithm was proposed. First, a user task scheduling system model based on edge cloud computing was constructed using the Shannon theorem, including calculation, communication, and network models. In addition, a multi-objective optimization model, including delay and energy consumption, was constructed to minimize the sum of two weights. Finally, the selection, crossover, and mutation operations of the genetic algorithm were improved using the best reservation selection algorithm and normal distribution crossover operator. Furthermore, an improved legacy algorithm was selected to deal with the multi-objective problem and acquire the optimal solution, that is, the best computing task scheduling scheme. The experimental analysis of the proposed strategy based on the MATLAB simulation platform shows that its energy loss does not exceed 50 J, and the time delay is 23.2 ms, which are better than those of other comparison strategies.

• Molecules and Cells
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• 제41권10호
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• pp.881-888
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• 2018

During the cortical development, cells in the brain acquire somatic mutations that can be implicated in various neurodevelopmental disorders. There is increasing evidence that brain somatic mutations lead to sporadic form of epileptic disorders with previously unknown etiology. In particular, malformation of cortical developments (MCD), ganglioglioma (GG) associated with intractable epilepsy and non-lesional focal epilepsy (NLFE) are known to be attributable to brain somatic mutations in mTOR pathway genes and others. In order to identify such somatic mutations presenting as low-level in epileptic brain tissues, the mutated cells should be enriched and sequenced with high-depth coverage. Nevertheless, there are a lot of technical limitations to accurately detect low-level of somatic mutations. Also, it is important to validate whether identified somatic mutations are truly causative for epileptic seizures or not. Furthermore, it will be necessary to understand the molecular mechanism of how brain somatic mutations disturb neuronal circuitry since epilepsy is a typical example of neural network disorder. In this review, we overview current genetic techniques and experimental tools in neuroscience that can address the existence and significance of brain somatic mutations in epileptic disorders as well as their effect on neuronal circuitry.