• Title/Summary/Keyword: adaptive security

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A Probe Detection based on Private Cloud using BlockChain (블록체인을 적용한 사설 클라우드 기반 침입시도탐지)

  • Lee, Seyul
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.14 no.2
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    • pp.11-17
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    • 2018
  • IDS/IPS and networked computer systems are playing an increasingly important role in our society. They have been the targets of a malicious attacks that actually turn into intrusions. That is why computer security has become an important concern for network administrators. Recently, various Detection/Prevention System schemes have been proposed based on various technologies. However, the techniques, which have been applied in many systems is useful for existing intrusion patterns on standard-only systems. Therefore, probe detection of private clouds using BlockChain has become a major security protection technology to detection potential attacks. In addition, BlockChain and Probe detection need to take into account the relationship between the various factors. We should develop a new probe detection technology that uses BlockChain to fine new pattern detection probes in cloud service security in the end. In this paper, we propose a probe detection using Fuzzy Cognitive Map(FCM) and Self Adaptive Module(SAM) based on service security using BlockChain technology.

Infrared Target Extraction Using Weighted Information Entropy and Adaptive Opening Filter

  • Bae, Tae Wuk;Kim, Hwi Gang;Kim, Young Choon;Ahn, Sang Ho
    • ETRI Journal
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    • v.37 no.5
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    • pp.1023-1031
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    • 2015
  • In infrared (IR) images, near targets have a transient distribution at the boundary region, as opposed to a steady one at the inner region. Based on this fact, this paper proposes a novel IR target extraction method that uses both a weighted information entropy (WIE) and an adaptive opening filter to extract near finely shaped targets in IR images. Firstly, the boundary region of a target is detected using a local variance WIE of an original image. Next, a coarse target region is estimated via a labeling process used on the boundary region of the target. From the estimated coarse target region, a fine target shape is extracted by means of an opening filter having an adaptive structure element. The size of the structure element is decided in accordance with the width information of the target boundary and mean WIE values of windows of varying size. Our experimental results show that the proposed method obtains a better extraction performance than existing algorithms.

A hybrid identification method on butterfly optimization and differential evolution algorithm

  • Zhou, Hongyuan;Zhang, Guangcai;Wang, Xiaojuan;Ni, Pinghe;Zhang, Jian
    • Smart Structures and Systems
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    • v.26 no.3
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    • pp.345-360
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    • 2020
  • Modern swarm intelligence heuristic search methods are widely applied in the field of structural health monitoring due to their advantages of excellent global search capacity, loose requirement of initial guess and ease of computational implementation etc. To this end, a hybrid strategy is proposed based on butterfly optimization algorithm (BOA) and differential evolution (DE) with purpose of effective combination of their merits. In the proposed identification strategy, two improvements including mutation and crossover operations of DE, and dynamic adaptive operators are introduced into original BOA to reduce the risk to be trapped in local optimum and increase global search capability. The performance of the proposed algorithm, hybrid butterfly optimization and differential evolution algorithm (HBODEA) is evaluated by two numerical examples of a simply supported beam and a 37-bar truss structure, as well as an experimental test of 8-story shear-type steel frame structure in the laboratory. Compared with BOA and DE, the numerical and experimental results show that the proposed HBODEA is more robust to detect the reduction of stiffness with limited sensors and contaminated measurements. In addition, the effect of search space, two dynamic operators, population size on identification accuracy and efficiency of the proposed identification strategy are further investigated.

A Study on Security Model Design of Adaptive Access Control based Context-Aware (상황인식 기반 적응적 접근제어 보안모델 설계에 관한 연구)

  • Kim, Nam-Il;Kim, Chang-Bok
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.8 no.5
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    • pp.211-219
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    • 2008
  • This paper is proposed context-aware based access control, model by extending original access control model. In this paper, we survey the recent researches about security model based context-aware such as xoRBAC and CAAC. For exactly policy evaluation, we make an addition Context Broker and Finder in existing CAAC security model. By this security model, Context information and context decision information is able to be collected easily for more correct policy decision. This paper controlled access of possible every resources that is able to access by user's event and constraint from primitive access resources. In this paper proposed security model can be offer dynamically various security level and access authority method alone with specified policy and constraint adjustment at user's role.

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A Study on the Security Processor Design based on Pseudo-Random Number in Web Streaming Environment

  • Lee, Seon-Keun
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.6
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    • pp.73-79
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    • 2020
  • Nowadays, with the rapid spread of streaming services in the internet world, security vulnerabilities are also increasing rapidly. For streaming security, this paper proposes a PN(pseudo-random noise) distributed structure-based security processor for web streaming contents(SP-WSC). The proposed SP-WSC is basically a PN distributed code algorithm designed for web streaming characteristics, so it can secure various multimedia contents. The proposed SP-WSC is independent of the security vulnerability of the web server. Therefore, SP-WSC can work regardless of the vulnerability of the web server. That is, the SP-WSC protects the multimedia contents by increasing the defense against external unauthorized signals. Incidentally it also suggests way to reduce buffering due to traffic overload.

Improvement of LMS Algorithm Convergence Speed with Updating Adaptive Weight in Data-Recycling Scheme (데이터-재순환 구조에서 적응 가중치 갱신을 통한 LMS 알고리즘 수렴 속 도 개선)

  • Kim, Gwang-Jun;Jang, Hyok;Suk, Kyung-Hyu;Na, Sang-Dong
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.9 no.4
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    • pp.11-22
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    • 1999
  • Least-mean-square(LMS) adaptive filters have proven to be extremely useful in a number of signal processing tasks. However LMS adaptive filter suffer from a slow rate of convergence for a given steady-state mean square error as compared to the behavior of recursive least squares adaptive filter. In this paper an efficient signal interference control technique is introduced to improve the convergence speed of LMS algorithm with tap weighted vectors updating which were controled by reusing data which was abandoned data in the Adaptive transversal filter in the scheme with data recycling buffers. The computer simulation show that the character of convergence and the value of MSE of proposed algorithm are faster and lower than the existing LMS according to increasing the step-size parameter $\mu$ in the experimentally computed. learning curve. Also we find that convergence speed of proposed algorithm is increased by (B+1) time proportional to B which B is the number of recycled data buffer without complexity of computation. Adaptive transversal filter with proposed data recycling buffer algorithm could efficiently reject ISI of channel and increase speed of convergence in avoidance burden of computational complexity in reality when it was experimented having the same condition of LMS algorithm.

Adaptive Absolute Delay Differentiation in Next-Generation Networks (차세대 네트워크에서의 적응형 절대적 지연 차별화 방식)

  • Paik, Jung-Hoon
    • Convergence Security Journal
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    • v.6 no.1
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    • pp.55-63
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    • 2006
  • In this paper, an algorithm that provisions absolute differentiation of packet delays is proposed with an objective for enhancing quality of service (QoS) in future packet networks. It features an adaptive scheme that compensates the deviation for prediction on the traffic to be arrived continuously. It predicts the traffic to be arrived at the beginning of a time slot and measures the actual arrived traffic at the end of the time slot, and derives the deviation between the two quantity. The deviation is utilized to the delay control operation for the next time slot to offset it. As it compensates the prediction error continuously, it shows superior adaptability to the bursty traffic as well as the constant rate traffic. It is demonstrated through simulation that the algorithm meets the quantitative delay bounds and shows superiority to the traffic fluctuation in comparison with the conventional mechanism.

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ATCS: An Adaptive TCP Coding Scheme for Satellite IP Networks

  • Dong, Wei;Wang, Junfeng;Huang, Minhuan;Tang, Jian;Zhou, Hongxia
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.5 no.5
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    • pp.1013-1027
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    • 2011
  • In this paper we propose ATCS, a practical TCP protocol coding scheme based on network coding for satellite IP networks. The proposal is specially designed to enhance TCP performance over satellite networks. In our scheme, the source introduces a degree of redundancy and transmits a random linear combination of TCP packets. Since the redundant packets are utilized to mask packet loss over satellite links, the degree of redundancy is determined by the link error rates. Through a simple and effective method, ATCS estimates link error rates in real time and then dynamically adjusts the redundant factor. Consequently, ATCS is adaptable to a wide range of link error rates by coding TCP segments with a flexible redundancy factor. Furthermore, the scheme is compatible with traditional TCP variants. Simulation results indicate that the proposal improves TCP performance considerably.

An Hybrid Probe Detection Model using FCM and Self-Adaptive Module (자가적응모듈과 퍼지인식도가 적용된 하이브리드 침입시도탐지모델)

  • Lee, Seyul
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.13 no.3
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    • pp.19-25
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    • 2017
  • Nowadays, networked computer systems play an increasingly important role in our society and its economy. They have become the targets of a wide array of malicious attacks that invariably turn into actual intrusions. This is the reason computer security has become an essential concern for network administrators. Recently, a number of Detection/Prevention System schemes have been proposed based on various technologies. However, the techniques, which have been applied in many systems, are useful only for the existing patterns of intrusion. Therefore, probe detection has become a major security protection technology to detection potential attacks. Probe detection needs to take into account a variety of factors ant the relationship between the various factors to reduce false negative & positive error. It is necessary to develop new technology of probe detection that can find new pattern of probe. In this paper, we propose an hybrid probe detection using Fuzzy Cognitive Map(FCM) and Self Adaptive Module(SAM) in dynamic environment such as Cloud and IoT. Also, in order to verify the proposed method, experiments about measuring detection rate in dynamic environments and possibility of countermeasure against intrusion were performed. From experimental results, decrease of false detection and the possibilities of countermeasures against intrusions were confirmed.