• Title/Summary/Keyword: artificial immune network

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DIntrusion Detection in WSN with an Improved NSA Based on the DE-CMOP

  • Guo, Weipeng;Chen, Yonghong;Cai, Yiqiao;Wang, Tian;Tian, Hui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.11
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    • pp.5574-5591
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    • 2017
  • Inspired by the idea of Artificial Immune System, many researches of wireless sensor network (WSN) intrusion detection is based on the artificial intelligent system (AIS). However, a large number of generated detectors, black hole, overlap problem of NSA have impeded further used in WSN. In order to improve the anomaly detection performance for WSN, detector generation mechanism need to be improved. Therefore, in this paper, a Differential Evolution Constraint Multi-objective Optimization Problem based Negative Selection Algorithm (DE-CMOP based NSA) is proposed to optimize the distribution and effectiveness of the detector. By combining the constraint handling and multi-objective optimization technique, the algorithm is able to generate the detector set with maximized coverage of non-self space and minimized overlap among detectors. By employing differential evolution, the algorithm can reduce the black hole effectively. The experiment results show that our proposed scheme provides improved NSA algorithm in-terms, the detectors generated by the DE-CMOP based NSA more uniform with less overlap and minimum black hole, thus effectively improves the intrusion detection performance. At the same time, the new algorithm reduces the number of detectors which reduces the complexity of detection phase. Thus, this makes it suitable for intrusion detection in WSN.

Effect of Human or Mouse IL-7 on the Homeostasis of Porcine T Lymphocytes

  • Ji Hwa Hong;Sang Hoon Kim;Hyun Gyung Kim;Jun Ho Jang;Ryeo Gang Son;Seung Pil Pack;Young-Ho Park;Philyong Kang;Kang-Jin Jeong;Ji-Su Kim;Hanbyeul Choi;Sun-Uk Kim;Yong Woo Jung
    • IMMUNE NETWORK
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    • v.21 no.3
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    • pp.24.1-24.13
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    • 2021
  • Due to the inconsistent fluctuation of blood supply for transfusion, much attention has been paid to the development of artificial blood using other animals. Although mini-pigs are candidate animals, contamination of mini-pig T cells in artificial blood may cause a major safety concern. Therefore, it is important to analyze the cross-reactivity of IL-7, the major survival factor for T lymphocytes, between human, mouse, and mini-pig. Thus, we compared the protein sequences of IL-7 and found that porcine IL-7 was evolutionarily different from human IL-7. We also observed that when porcine T cells were cultured with either human or mouse IL-7, these cells did not increase the survival or proliferation compared to negative controls. These results suggest that porcine T cells do not recognize human or mouse IL-7 as their survival factor.

Towards an Artificial Immune System for Network Intrusion Detection: An Investigation of Dynamic Clonal Selection (네트워크 침입탐지를 위한 인공면역 시스템의 동적 클론선택 연구)

  • 김정원;최종욱;김상진
    • Proceedings of the Korean Information Science Society Conference
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    • 2002.04a
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    • pp.847-849
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    • 2002
  • 인공면역시스템에서 중요한 특징중의 하나는 지속적으로 변화하는 환경에서 자기(self)의 유동적인 패턴을 동적으로 학습하고 비자기(non-self)에 대한 새로운 패턴을 예측하는데 있다. 본 논문은 자기적 용(self-adaptation)의 인공면역체계 특성을 기반으로하여 설계된 dynamics(동적 클론선택 알고리즘, dynamic clonal selection algorithm)의 역할을 논한다. 시스템의 세가지 중요한 변수인 자기내성 기간(Tolerisation Period). 연역 반응 임계값(activation threshold). 수명(life span)에 따라 변화하는 dynamics의 성능을 네트워크 침입에서 흔히 발견되는 시나리오를 모의실험하여 평가한다

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Distributed Autonomous Robotics System based on Classifier System and Artificial Immune Network (분류자 시스템과 인공 면역 네트워크에 기반한 자율 분산 로봇 시스템 개발)

  • 황철민;박창현;심귀보
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2004.04a
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    • pp.85-88
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    • 2004
  • 본 논문에서는 인공 면역 네트워크와 분류자 시스템을 이용한 자율 분산 로봇 시스템을 제안한다. 시스템에서 각 로봇의 행동은 전역행동과 지역행동으로 구성된다. 전역행동은 작업을 찾고 수행하기 위해 필요한 환경을 조성하는데 필요한 전반적인 행동들을 결정하고, 지역 행동은 작업을 수행할 때 각 로봇들이 어떤 방식으로 동작하는가를 결정한다. 이때 전역 행동은 인공 면역 네트워크를 이용하여 결정되며 작업을 빠른 속도로 탐색하며 탐색한 작업 주위로 적절한 수의 로봇이 집합하도록 한다. 또한 지역 행동은 분류자 시스템을 이용하여 결정되며 작업을 수행하는데 적절한 로봇의 역할을 결정한다.

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Analysis of Computer Virus Immune System (바이러스 면역시스템 분석)

  • 전완근;이중식;이종일;김홍윤
    • Convergence Security Journal
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    • v.2 no.2
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    • pp.39-47
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    • 2002
  • To recently with the love-letter and Back Orifice the same Worm-virus, with the Trojan and the Linux-virus back against the new species virus which inside and outside of the country to increase tendency the malignant new species virus which is the possibility of decreasing the damage which is enormous in the object appears and to follow a same network coat large scale PC is being quicker, it disposes spontaneously to respect, applied an artificial intelligence technique the research against the next generation malignant computer virus of new form is demanded. Will reach and to respect it analyzes the digital immunity system of the automatic detection which is quick against the next generation malignant virus which had become unconfirmed and the foreign countries which has an removal function.

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Online Identification for Normal and Abnormal Status of Water Quality on Ocean USN (해양 USN 환경에서 수질환경의 온라인 정상·비정상 상태 구분)

  • Jeoung, Sin-Chul;Ceong, Hee-Taek
    • The Journal of the Korea institute of electronic communication sciences
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    • v.7 no.4
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    • pp.905-915
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    • 2012
  • This paper suggests the online method to identify normal and abnormal state of water quality on the ocean USN. To define normal of the ocean water quality, we utilize the negative selection algorithm of artificial immunity system which has self and nonself identification characteristics. To distinguish abnormal status, normal state set of the ocean water quality needs to be defined. For this purpose, we generate normal state set base on mutations of each data and mutation of the data as logical product. This mutated normal (or self) sets used to identify abnormal status of the water quality. We represent the experimental result about mutated self set with the Gaussian function. Through setting the method on the ocean sensor logger, we can monitor whether the ocean water quality is normal or abnormal state by online.

Seeing is Believing: Illuminating the Source of In Vivo Interleukin-7

  • Kim, Grace Yoon-Hee;Hong, Chang-Wan;Park, Jung-Hyun
    • IMMUNE NETWORK
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    • v.11 no.1
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    • pp.1-10
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    • 2011
  • Interleukin-7 (IL-7) is an essential cytokine for T cells. However, IL-7 is not produced by T cells themselves such that T cells are dependent on extrinsic IL-7. In fact, in the absence of IL-7, T cell development in the thymus as well as survival of naive T cells in the periphery is severely impaired. Furthermore, modulating IL-7 availability in vivo either by genetic means or other experimental approaches determines the size, composition and function of the T cell pool. Consequently, understanding IL-7 expression is critical for understanding T cell immunity. Until most recently, however, the spatiotemporal expression of in vivo IL-7 has remained obscured. Shortage of such information was partly due to scarce expression of IL-7 itself but mainly due to the lack of adequate reagents to monitor IL-7 expression in vivo. This situation dramatically changed with a recent rush of four independent studies that describe the generation and characterization of IL-7 reporter mice, all utilizing bacterial artificial chromosome transgene technology. The emerging consensus of these studies confirmed thymic stromal cells as the major producers of IL-7 but also identified IL-7 reporter activities in various peripheral tissues including skin, intestine and lymph nodes. Strikingly, developmental and environmental cues actively modulated IL-7 reporter activities in vivo suggesting that IL-7 regulation might be a new mechanism of shaping T cell development and homeostasis. Collectively, the availability of these new tools opens up new venues to assess unanswered questions in IL-7 biology in T cells and beyond.

Intrusion Detection Learning Algorithm using Adaptive Anomaly Detector (적응형 변형 인식부를 이용한 침입 탐지 학습알고리즘)

  • Sim, Kwee-Bo;Yang, Jae-Won;Kim, Young-Soo;Lee, Se-Yul
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.4
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    • pp.451-456
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    • 2004
  • Signature based intrusion detection system (IDS), having stored rules for detecting intrusions at the library, judges whether new inputs are intrusion or not by matching them with the new inputs. However their policy has two restrictions generally. First, when they couldn't make rules against new intrusions, false negative (FN) errors may are taken place. Second, when they made a lot of rules for maintaining diversification, the amount of resources grows larger proportional to their amount. In this paper, we propose the learning algorithm which can evolve the competent of anomaly detectors having the ability to detect anomalous attacks by genetic algorithm. The anomaly detectors are the population be composed of by following the negative selection procedure of the biological immune system. To show the effectiveness of proposed system, we apply the learning algorithm to the artificial network environment, which is a computer security system.

Adaptive Intrusion Detection Algorithm based on Learning Algorithm (학습 알고리즘 기반의 적응형 침입 탐지 알고리즘)

  • Sim, Kwee-Bo;Yang, Jae-Won;Lee, Dong-Wook;Seo, Dong-Il;Choi, Yang-Seo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.1
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    • pp.75-81
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    • 2004
  • Signature based intrusion detection system (IDS), having stored rules for detecting intrusions at the library, judges whether new inputs are intrusion or not by matching them with the new inputs. However their policy has two restrictions generally. First, when they couldn`t make rules against new intrusions, false negative (FN) errors may are taken place. Second, when they made a lot of rules for maintaining diversification, the amount of resources grows larger proportional to their amount. In this paper, we propose the learning algorithm which can evolve the competent of anomaly detectors having the ability to detect anomalous attacks by genetic algorithm. The anomaly detectors are the population be composed of by following the negative selection procedure of the biological immune system. To show the effectiveness of proposed system, we apply the learning algorithm to the artificial network environment, which is a computer security system.

Comprehensive Analysis of Epstein-Barr Virus LMP2A-Specific CD8+ and CD4+ T Cell Responses Restricted to Each HLA Class I and II Allotype Within an Individual

  • Hyeong-A Jo;Seung-Joo Hyun;You-Seok Hyun;Yong-Hun Lee;Sun-Mi Kim;In-Cheol Baek ;Hyun-Jung Sohn;Tai-Gyu Kim
    • IMMUNE NETWORK
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    • v.23 no.2
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    • pp.17.1-17.16
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    • 2023
  • Latent membrane protein 2A (LMP2A), a latent Ag commonly expressed in Epstein-Barr virus (EBV)-infected host cells, is a target for adoptive T cell therapy in EBV-associated malignancies. To define whether individual human leukocyte antigen (HLA) allotypes are used preferentially in EBV-specific T lymphocyte responses, LMP2A-specific CD8+ and CD4+ T cell responses in 50 healthy donors were analyzed by ELISPOT assay using artificial Ag-presenting cells expressing a single allotype. CD8+ T cell responses were significantly higher than CD4+ T cell responses. CD8+ T cell responses were ranked from highest to lowest in the order HLA-A, HLA-B, and HLA-C loci, and CD4+ T cell responses were ranked in the order HLA-DR, HLA-DP, and HLA-DQ loci. Among the 32 HLA class I and 56 HLA class II allotypes, 6 HLA-A, 7 HLA-B, 5 HLA-C, 10 HLA-DR, 2 HLA-DQ, and 2 HLA-DP allotypes showed T cell responses higher than 50 spot-forming cells (SFCs)/5×105 CD8+ or CD4+ T cells. Twenty-nine donors (58%) showed a high T cell response to at least one allotype of HLA class I or class II, and 4 donors (8%) had a high response to both HLA class I and class II allotypes. Interestingly, we observed an inverse correlation between the proportion of LMP2A-specific T cell responses and the frequency of HLA class I and II allotypes. These data demonstrate the allele dominance of LMP2A-specific T cell responses among HLA allotypes and their intra-individual dominance in response to only a few allotypes in an individual, which may provide useful information for genetic, pathogenic, and immunotherapeutic approaches to EBV-associated diseases.