• Title/Summary/Keyword: random network

Search Result 1,205, Processing Time 0.03 seconds

Dynamic Control of Random Constant Spreading Worm using Depth Distribution Characteristics

  • No, Byung-Gyu;Park, Doo-Soon;Hong, Min;Lee, Hwa-Min;Park, Yoon-Sok
    • Journal of Information Processing Systems
    • /
    • v.5 no.1
    • /
    • pp.33-40
    • /
    • 2009
  • Ever since the network-based malicious code commonly known as a 'worm' surfaced in the early part of the 1980's, its prevalence has grown more and more. The RCS (Random Constant Spreading) worm has become a dominant, malicious virus in recent computer networking circles. The worm retards the availability of an overall network by exhausting resources such as CPU capacity, network peripherals and transfer bandwidth, causing damage to an uninfected system as well as an infected system. The generation and spreading cycle of these worms progress rapidly. The existing studies to counter malicious code have studied the Microscopic Model for detecting worm generation based on some specific pattern or sign of attack, thus preventing its spread by countering the worm directly on detection. However, due to zero-day threat actualization, rapid spreading of the RCS worm and reduction of survival time, securing a security model to ensure the survivability of the network became an urgent problem that the existing solution-oriented security measures did not address. This paper analyzes the recently studied efficient dynamic network. Essentially, this paper suggests a model that dynamically controls the RCS worm using the characteristics of Power-Law and depth distribution of the delivery node, which is commonly seen in preferential growth networks. Moreover, we suggest a model that dynamically controls the spread of the worm using information about the depth distribution of delivery. We also verified via simulation that the load for each node was minimized at an optimal depth to effectively restrain the spread of the worm.

Design of Speed Up Switch Using Banyan-Network with Sorting Network (정렬 반얀망을 이용한 고속 스위치 설계)

  • 최상진;권승탁
    • Proceedings of the IEEK Conference
    • /
    • 2001.06a
    • /
    • pp.281-284
    • /
    • 2001
  • In this paper, we design the Sorting-Banyan network with an efficient buffer and sorting management schema that makes switch be capable of supporting delay sensitive as well as loss sensitive. The proposed switching network is remodeled that based on Batcher-banyan network that have eight input and output ports The structure of designed switching network is constructed of modified banyan network with 2-way routing paths and two plane sorting networks. we have analysed the maximum throughput of the switch, under the uniform random traffic load, the FIFO discipline has increased by about 11% when we compare the switching system with the input buffering system.

  • PDF

Comparison between nonlinear statistical time series forecasting and neural network forecasting

  • Inkyu;Cheolyoung;Sungduck
    • Communications for Statistical Applications and Methods
    • /
    • v.7 no.1
    • /
    • pp.87-96
    • /
    • 2000
  • Nonlinear time series prediction is derived and compared between statistic of modeling and neural network method. In particular mean squared errors of predication are obtained in generalized random coefficient model and generalized autoregressive conditional heteroscedastic model and compared with them by neural network forecasting.

  • PDF

Design of Stochastic Movement Model Considering Sensor Node Reliability and Energy Efficiency

  • Cho, Do-Hyeoun;Yeol, Yun Dai;Hwang, Chi-Gon
    • International Journal of Internet, Broadcasting and Communication
    • /
    • v.12 no.3
    • /
    • pp.156-162
    • /
    • 2020
  • Wireless Sensor Network (WSN) field is mainly studied to monitor and characterize large-scale physical environments to track various environmental or physical conditions, such as temperature, pressure, wind speed and humidity. WSN can be used in various applications such as wild surveillance, military target tracking and monitoring, dangerous environmental exploration and natural disaster relief. We design probabilistic mobile models that apply to mobile ad hoc network mobile environments. A probabilistic shift model proposed by dividing the number of moving nodes and the distance of travel into two categories to express node movement characteristics. The proposed model of movement through simulation was compared with the existing random movement model, ensuring that the width and variation rate of the first node node node node (FND) was stable regardless of the node movement rate. In addition, when the proposed mobile model is applied to the routing protocol, the superiority of network life can be verified from measured FND values. We overcame the limitations of the existing random movement model, showing excellent characteristics in terms of energy efficiency and stable in terms of changes in node movement.

Active Control of Offshore Structures for Wave Response Reduction Using Probabilistic Neural Network

  • Kim, Doo-Kie;Kim, Dong-Hyawn;Chang, Sang-Kil;Chang, Seong-Kyu
    • Journal of Ocean Engineering and Technology
    • /
    • v.20 no.5 s.72
    • /
    • pp.1-8
    • /
    • 2006
  • Offshore structures are subjected to wave, wind, and earthquake loads. The failure of offshore structures can cause sea pollution, as well as losses of property and lives. Therefore, safety of the structure is an important issue. The reduction of the dynamic response of offshore towers, subjected wind generated random ocean waves, is a critical problem with respect to serviceability, fatigue life and safety of the structure. In this paper, a structural control method is proposed to control the vibration of offshore structures by the probabilistic neural network (PNN). The state vectors of the structure and control forces are used for training patterns of the PNN, in which control forces are prepared by linear quadratic regulator (LQR) control algorithm. The proposed algorithm is applied to a fixed offshore structure under random ocean waves. Active control of the fixed offshore structure using the PNN control algorithm shows good results.

The Throughput Order of Multicast Traffics with Physical-Layer Network Coding in Random Wireless Ad Hoc Networks

  • Chen, Chen;Bai, Lin;He, Jianhua;Xiang, Haige;Choi, Jin-Ho
    • Journal of Communications and Networks
    • /
    • v.13 no.3
    • /
    • pp.214-220
    • /
    • 2011
  • This paper attempts to address the effectiveness of physical-layer network coding (PNC) on the throughput improvement for multi-hop multicast in random wireless ad hoc networks (WAHNs). We prove that the per session throughput order with PNC is tightly bounded as ${\Theta}((n\sqrt{m}R(n))^{-1})$ if $m=(R^{-2}(n))$, where n is the total number of nodes, R(n) is the communication range, and m is the number of destinations for each multicast session. We also show that per-session throughput order with PNC is tight bounded as ${\Theta}(n^{-1})$, when $m={\Omega}(R^{-2}(n))$. The results of this paper imply that PNC cannot improve the throughput order of multicast in random WAHNs, which is different from the intuition that PNC may improve the throughput order as it allows simultaneous signal access and combination.

Improve ARED Algorithm in TCP/IP Network (TCP/IP 네트워크에서 ARED 알고리즘의 성능 개선)

  • Nam, Jae-Hyun
    • Journal of the Korea Society of Computer and Information
    • /
    • v.12 no.3
    • /
    • pp.177-183
    • /
    • 2007
  • Active queue management (AQM) refers to a family of packet dropping mechanisms for router queues that has been proposed to support end-to-end congestion control mechanisms in the Internet. The proposed AQM algorithm by the IETF is Random Early Detection (RED). The RED algorithm allows network operators simultaneously to achieve high throughput and low average delay. However. the resulting average queue length is quite sensitive to the level of congestion. In this paper, we propose the Refined Adaptive RED(RARED), as a solution for reducing the sensitivity to parameters that affect RED performance. Based on simulations, we observe that the RARED scheme improves overall performance of the network. In particular, the RARED scheme reduces packet drop rate and improves goodput.

  • PDF

An Analysis of Random Routes in SybilGuard (SybilGuard 에서의 부하 분석 및 부하균등 방법 제시)

  • Kim, Hyeong Seog;Kim, Ki Young;Yeom, Heon Young
    • Proceedings of the Korea Information Processing Society Conference
    • /
    • 2007.11a
    • /
    • pp.1151-1153
    • /
    • 2007
  • P2P 및 Mobile Network, Reputations System 등의 분산 시스템은 sybil attack 에 노출되어 있다. sybil attack 은 한 명의 사용자가 다수의 식별자를 가진 것으로 위장하여 시스템 내에서 마치 실제 다수의 사용자인 양 시스템을 악용하는 공격방법이다. sybil attack 을 막기 위한 다양한 노력이 진행되었고, 최근에 SybilGuard 라는 social network 를 이용한 방어 방법이 제시되었다. SybilGuard 는 악의적인 사용자를 막기 위하여, Random Walk 의 변형이면서 결정적인 경로의 특징을 가지는 임의경로(Random Route)를 사용하여 악의적인 사용자의 sybil attack 을 방어한다. SybilGuard 는 sybil node 의 개수를 제한하고, 이들을 하나의 동일한 그룹으로 분류할 수 있도록 하여 시스템 내에서 가짜 식별자의 개수를 제한한다. 이를 위해 각 노드가 시스템에 돌어올 때 Verifier(V)노드가 이들 노드를 확인하게 되는데, 이를 위해 시스템 내의 선한 노드(Honest Node)를 사용하여 이들을 확인한다. 이 때, honest node 들은 verifier 의 요청에 따라 확인요청을 수행하게 되는데, social network 의 특성상 몇몇 노드들은 사회적인 명망으로 매우 큰 링크수를 가지게 될 것이며, 따라서 이들 노드들이 처리해야할 요청의 양이 매우 많아지게 될 것이다. 따라서 이들 honest node 들 간에 로드분포를 균등하게 하는 것이 요구되며, 이 논문에서는 부하 조절을 하기 위한 기법을 제시하고, 이들을 평가한다.

Learning of Neural Network Using Tabu Search Method with Random Moves (Random 탐색법과 조합된 Tabu 탐색법을 이용한 신경회로망의 학습)

  • 신광재;양보석;최원호
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
    • /
    • 1994.10a
    • /
    • pp.121-125
    • /
    • 1994
  • 본 논문에서는 Hu에 의해 고안된 random 탐색법과 조합된 tabu 탐색법(radnom tabu 탐색법)을 결합계수를 구하는 학습 알고리즘으로 직접 사용하여 국소적 최적해에 수렴하는 것을 방지하고, 수렴정도를 개선하는 새로운 방법을 제안한다. 이 방법을 배타적 논리합 문제에 적용하여 역전파법 및 tabu 탐색법을 이용한 오차역전파법과 비교한다. 그리고, 각 파라메터가 오차함수의 수렴에 미치는 영향을 조사한다.

  • PDF

Sensor Network Key Management Scheme for Detecting Malicious Node Based on Random Key Predistribution (악의적 노드 탐지를 위한 Random Key Predistribution 기반의 센서 네트워크 키 관리 기법)

  • Park, Han;Song, JooSeok
    • Proceedings of the Korea Information Processing Society Conference
    • /
    • 2009.04a
    • /
    • pp.1245-1246
    • /
    • 2009
  • 센서 네트워크는 유비쿼터스 컴퓨팅에서 핵심적인 역할을 담당하는 기반 네트워크이다. 그 때문에 센서 네트워크로부터 제공되는 정보는 신뢰할 수 있어야 한다. 하지만 센서 자체의 여러 가지 한계로 인해 보안의 핵심 요소인 키 관리에는 많은 어려움이 존재한다. 이 논문에서는 Random Key Predistribution 기법에 기반하여 악의적인 노드를 탐지하지 못하는 기존의 한계점을 분석하고, 이를 해결하기 위한 새로운 키 관리 기법을 제안한다.