• 제목/요약/키워드: Computer Networks

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SEC Approach for Detecting Node Replication Attacks in Static Wireless Sensor Networks

  • Sujihelen, L.;Jayakumar, C.;Senthilsingh, C.
    • Journal of Electrical Engineering and Technology
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    • 제13권6호
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    • pp.2447-2455
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    • 2018
  • Security is more important in many sensor applications. The node replication attack is a major issue on sensor networks. The replicated node can capture all node details. Node Replication attacks use its secret cryptographic key to successfully produce the networks with clone nodes and also it creates duplicate nodes to build up various attacks. The replication attacks will affect in routing, more energy consumption, packet loss, misbehavior detection, etc. In this paper, a Secure-Efficient Centralized approach is proposed for detecting a Node Replication Attacks in Wireless Sensor Networks for Static Networks. The proposed system easily detects the replication attacks in an effective manner. In this approach Secure Cluster Election is used to prevent from node replication attack and Secure Efficient Centralized Approach is used to detect if any replicated node present in the network. When comparing with the existing approach the detection ratio, energy consumption performs better.

신경망을 이용한 건물 공조시스템의 최적제어 관한 연구 ((A Simulation of Neural Networks Control for Building HVAC))

  • 육상조;유승선;이극
    • 한국컴퓨터산업학회논문지
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    • 제3권9호
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    • pp.1199-1206
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    • 2002
  • 본 연구에서는 일반적인 건물의 공조시스템의 제어에 이용되고 있는 비례-적분(PI)제어의 적용특성을 알아보고 새로운 지능형 제어방식중의 하나인 신경망(neural networks) 제어의 적용가능성을 검토하여 보았다. PI제어에 의한 건물공조와 신경망 제어에 의한 건물공조에 대한 성능을 비교한다. 기존의 PI제어에 의하여 운영되던 건물을 신경망 제어로서 운용하는 경우 기후적, 시스템적 변화에 자체적 대응이 가능한 제어로 적용 가능하다.

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Multi-Agent System for Fault Tolerance in Wireless Sensor Networks

  • Lee, HwaMin;Min, Se Dong;Choi, Min-Hyung;Lee, DaeWon
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권3호
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    • pp.1321-1332
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    • 2016
  • Wireless sensor networks (WSN) are self-organized networks that typically consist of thousands of low-cost, low-powered sensor nodes. The reliability and availability of WSNs can be affected by faults, including those from radio interference, battery exhaustion, hardware and software failures, communication link errors, malicious attacks, and so on. Thus, we propose a novel multi-agent fault tolerant system for wireless sensor networks. Since a major requirement of WSNs is to reduce energy consumption, we use multi-agent and mobile agent configurations to manage WSNs that provide energy-efficient services. Mobile agent architecture have inherent advantages in that they provide energy awareness, scalability, reliability, and extensibility. Our multi-agent system consists of a resource manager, a fault tolerance manager and a load balancing manager, and we also propose fault-tolerant protocols that use multi-agent and mobile agent setups.

Cross-layer Optimized Vertical Handover Schemes between Mobile WiMAX and 3G Networks

  • Jo, Jae-Ho;Cho, Jin-Sung
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제2권4호
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    • pp.171-183
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    • 2008
  • Nowadays, wireless packet data services are provided over Wireless MAN (WMAN) at a high data service rate, while 3G cellular networks provide wide-area coverage at a low data service rate. The integration of mobile WiMAX and 3G networks is essential, to serve users requiring both high-speed wireless access as well as wide-area connectivity. In this paper, we propose a cross-layer optimization scheme for a vertical handover between mobile WiMAX and 3G cellular networks. More specifically, L2 (layer 2) and L3 (layer 3) signaling messages for a vertical handover are analyzed and reordered/combined, to optimize the handover procedure. Extensive simulations using ns-2 demonstrate that the proposed scheme enhances the performance of a vertical handover between mobile WiMAX and 3G networks: low handover latency, high TCP throughput, and low UDP packet loss ratio.

신경회로망을 이용한 컴퓨터 네트워크의 최적 라우팅에 관한 연구 (A Study on Optimal Routing of Computer Networks using Neural Networks)

  • 김정욱;이석필;박상희
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1995년도 추계학술대회 논문집 학회본부
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    • pp.566-568
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    • 1995
  • An optimal routing method using hysteresis binary neurons with link failure probability is proposed in this paper. The link failures in computer networks can degrade the performance of the entire networks. We assume the time between successive link failures is exponentially distributed with parameter ${\lambda}$ and the failures are independent. The link failure probability is used for neural networks to find the shortest paths of given source-destination pairs. By using the probability of link failures and hysteresis binary neurons we implement an optimal routing method that can takes routes by coping with link failures.

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Power Allocation Framework for OFDMA-based Decode-and-Forward Cellular Relay Networks

  • Farazmand, Yalda;Alfa, Attahiru S.
    • Journal of Communications and Networks
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    • 제16권5호
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    • pp.559-567
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    • 2014
  • In this paper, a framework for power allocation of downlink transmissions in orthogonal frequency division multiple access-based decode-and-forward cellular relay networks is investigated. We consider a system with a single base station communicating with multiple users assisted by multiple relays. The relays have limited power which must be divided among the users they support in order to maximize the data rate of the whole network. Advanced power allocation schemes are crucial for such networks. The optimal relay power allocation which maximizes the data rate is proposed as an upper bound, by finding the optimal power requirement for each user based on knapsack problem formulation. Then by considering the fairness, a new relay power allocation scheme, called weighted-based scheme, is proposed. Finally, an efficient power reallocation scheme is proposed to efficiently utilize the power and improve the data rate of the network. Simulation results demonstrate that the proposed power allocation schemes can significantly improve the data rate of the network compared to the traditional scheme.

Dynamic Routing and Spectrum Allocation with Traffic Differentiation to Reduce Fragmentation in Multifiber Elastic Optical Networks

  • ZOUNEME, Boris Stephane;ADEPO, Joel;DIEDIE, Herve Gokou;OUMTANAGA, Souleymane
    • International Journal of Computer Science & Network Security
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    • 제21권3호
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    • pp.1-10
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    • 2021
  • In recent decades, the heterogeneous and dynamic behavior of Internet traffic has placed new demands on the adaptive resource allocation of the optical network infrastructure. However, the advent of multifiber elastic optical networks has led to a higher degree of spectrum fragmentation than conventional flexible grid networks due to the dynamic and random establishment and removal of optical connections. In this paper, we propose heuristic routing and dynamic slot allocation algorithms to minimize spectrum fragmentation and reduce the probability of blocking future connection requests by considering the power consumption in elastic multifiber elastic optical networks.

Exploring the Feasibility of Neural Networks for Criminal Propensity Detection through Facial Features Analysis

  • Amal Alshahrani;Sumayyah Albarakati;Reyouf Wasil;Hanan Farouquee;Maryam Alobthani;Someah Al-Qarni
    • International Journal of Computer Science & Network Security
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    • 제24권5호
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    • pp.11-20
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    • 2024
  • While artificial neural networks are adept at identifying patterns, they can struggle to distinguish between actual correlations and false associations between extracted facial features and criminal behavior within the training data. These associations may not indicate causal connections. Socioeconomic factors, ethnicity, or even chance occurrences in the data can influence both facial features and criminal activity. Consequently, the artificial neural network might identify linked features without understanding the underlying cause. This raises concerns about incorrect linkages and potential misclassification of individuals based on features unrelated to criminal tendencies. To address this challenge, we propose a novel region-based training approach for artificial neural networks focused on criminal propensity detection. Instead of solely relying on overall facial recognition, the network would systematically analyze each facial feature in isolation. This fine-grained approach would enable the network to identify which specific features hold the strongest correlations with criminal activity within the training data. By focusing on these key features, the network can be optimized for more accurate and reliable criminal propensity prediction. This study examines the effectiveness of various algorithms for criminal propensity classification. We evaluate YOLO versions YOLOv5 and YOLOv8 alongside VGG-16. Our findings indicate that YOLO achieved the highest accuracy 0.93 in classifying criminal and non-criminal facial features. While these results are promising, we acknowledge the need for further research on bias and misclassification in criminal justice applications

An Identity-based Ring Signcryption Scheme: Evaluation for Wireless Sensor Networks

  • Sharma, Gaurav;Bala, Suman;Verma, Anil K.
    • IEIE Transactions on Smart Processing and Computing
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    • 제2권2호
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    • pp.57-66
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    • 2013
  • Wireless Sensor Networks consist of small, inexpensive, low-powered sensor nodes that communicate with each other. To achieve a low communication cost in a resource constrained network, a novel concept of signcryption has been applied for secure communication. Signcryption enables a user to perform a digital signature for providing authenticity and public key encryption for providing message confidentiality simultaneously in a single logical step with a lower cost than that of the sign-then-encrypt approach. Ring signcryption maintains the signer's privacy, which is lacking in normal signcryption schemes. Signcryption can provide confidentiality and authenticity without revealing the user's identity of the ring. This paper presents the security notions and an evaluation of an ID-based ring signcryption scheme for wireless sensor networks. The scheme has been proven to be better than the existing schemes. The proposed scheme was found to be secure against adaptive chosen ciphertext ring attacks (IND-IDRSC-CCA2) and secure against an existential forgery for adaptive chosen message attacks (EF-IDRSC-ACMA). The proposed scheme was found to be more efficient than scheme for Wireless Sensor Networks reported by Qi. et al. based on the running time and energy consumption.

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SELFCON: An Architecture for Self-Configuration of Networks

  • Boutaba, Raouf;Omari, Salima;Singh Virk, Ajay Pal
    • Journal of Communications and Networks
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    • 제3권4호
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    • pp.317-323
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    • 2001
  • Traditional configuration management involves complex labor-intensive processes performed by experts. The configuration tasks such as installing or reconfiguring a system, provisioning network services and allocating resources typically involve a large number of activities involving multiple network elements. The network elements may be associated with proprietary configuration management instrumentation and may also be spread across heterogeneous network domains thereby increasing the complexity of configuration management. This paper introduces an architecture for the self-configuration of networks (SELFCON). The proposed architecture involves a directory server, which is uses to maintain configuration information. The configuration information stared in the directory server is modeled using the standard DEN specification thereby allowing effective exchange of network, system and configuration management data among heterogeneous management domains. SELFCON associates configuration intelligence with the components of the network, rather than limit it to a centralized management station. The network elements are notified about related changes in configuration policies, based upon which, they perform self-configuration. SELFCON is able to provide automation of configuration management and also an effective unifying framework for enterprise management.

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