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Node misbehavior detection and secure trust metadata management in mobile networks.

机译:移动网络中的节点行为异常检测和安全信任元数据管理。

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摘要

The topic of study of this dissertation is node misbehavior detection and secure trust metadata management in mobile networks. For concreteness, two classic mobile networks, delay-tolerant networks and mobile ad-hoc networks, are chosen as the context of this study.;In a Delay-Tolerant Network (DTN), data originating from a source node may be delivered to the destination node, despite the non-existence of end-to-end connectivity between them at all times. In an adversarial environment such as a battlefield, DTN nodes could be compromised to launch Denial-of-Service (DoS) attacks by generating excess data, to cause an overflow of the limited resources of the legitimate nodes, hence decreasing the network throughput. A node may also display selfish behavior by generating more data than allowed, to increase its throughput and to decrease the latency of its data packets. In this dissertation, such a DoS attack and selfish data generation behavior is termed a resource-misuse attack. Two types of resource-misuse attacks are studied, breadth attacks and depth attacks. Accordingly, different schemes to detect these attacks are proposed. Trace-driven simulations using both a synthetic and a real-world trace show that the detection schemes have low average detection latency and additionally, probabilistic detection of the depth attack has low false positive and false negative rates.;Nodes may also display selfish or malicious behavior in a mobile ad-hoc network (MANET). Since the nodes in a MANET are generally resource limited, some nodes could refuse service to other nodes to conserve their resources, thereby exhibiting selfish behavior. Also, since a MANET is often deployed in uncontrolled environments, some nodes could be compromised by an adversary and directed to act maliciously. A trust management framework in a MANET is useful to infer if nodes behave in a selfish or malicious manner, so that appropriate action could be taken, in order to maximize network performance. In this dissertation, a scalable semantics-aware trust metadata management scheme to partition and store an information network of trust metadata of nodes in a MANET is proposed. In this scheme, trust metadata created by individual nodes is propagated to and stored at certain geographic locations in the network itself, based on its semantics. A network entity, such as a trust authority (TA) (e.g., the network administrator), could then send queries of various types in the network to obtain the trust metadata of its interest, and thereby evaluate the behavior of nodes and make prompt decisions (e.g., revoking malicious nodes). The simplicity of this scheme for trust metadata propagation and retrieval, and its robustness to node failures, membership changes and mobility, make it a promising choice for trust metadata management in a MANET. Simulation results that evaluate this scheme based on some trust management metrics demonstrate its performance benefits.;A trust metadata management scheme for a MANET is also required to be secure. Misbehaving nodes could attempt to prevent trust metadata from eventually reaching the concerned network entity (e.g., a TA), to escape detection of their misbehavior. In this dissertation, a secure and scalable trust metadata management scheme for a MANET is designed. This scheme is robust to several security attacks that attempt to disrupt the availability of trust metadata in the network. Analysis of the proposed scheme shows that it provides desirable security and functionality properties with low query overhead.
机译:本文的研究主题是移动网络中的节点不良行为检测和安全信任元数据管理。为具体起见,本研究选择了两个经典的移动网络,即延迟容忍网络和移动自组织网络。在延迟容忍网络(DTN)中,源节点的数据可能会传递到目标节点,尽管它们之间始终不存在端到端连接。在战场等对抗性环境中,DTN节点可能会受到损害,以通过生成过多数据来发起拒绝服务(DoS)攻击,从而导致合法节点的有限资源溢出,从而降低网络吞吐量。节点还可以通过生成超出允许范围的数据来显示自私行为,以增加其吞吐量并减少其数据包的延迟。本文将这种DoS攻击和自私的数据生成行为称为资源滥用攻击。研究了两种类型的资源滥用攻击:广度攻击和深度攻击。因此,提出了用于检测这些攻击的不同方案。使用合成和真实轨迹的轨迹驱动模拟表明,检测方案的平均检测延迟较低,此外,深度攻击的概率检测的误报率和误报率也很低;节点也可能显示自私或恶意移动自组织网络(MANET)中的行为。由于MANET中的节点通常受资源限制,因此某些节点可能拒绝服务其他节点以节省其资源,从而表现出自私的行为。而且,由于MANET通常部署在不受控制的环境中,因此某些节点可能会受到对手的攻击并被定向为恶意行为。 MANET中的信任管理框架可用于推断节点是否以自私或恶意的方式运行,以便可以采取适当的措施以最大化网络性能。本文提出了一种可扩展的语义感知信任元数据管理方案,用于在MANET中划分和存储节点信任元信息网络。在此方案中,由单个节点创建的信任元数据将基于其语义传播并存储在网络本身中的某些地理位置。然后,诸如信任机构(TA)(例如,网络管理员)之类的网络实体可以在网络中发送各种类型的查询,以获得其感兴趣的信任元数据,从而评估节点的行为并做出迅速的决策。 (例如,撤销恶意节点)。此方案用于信任元数据的传播和检索的简单性,以及对节点故障,成员资格更改和移动性的鲁棒性,使其成为MANET中信任元数据管理的有希望的选择。基于某些信任管理度量标准评估该方案的仿真结果证明了其性能优势。; MANET的信任元数据管理方案也必须是安全的。行为不当的节点可能会尝试阻止信任元数据最终到达相关的网络实体(例如TA),以逃避对其行为不当的检测。本文设计了一种安全,可扩展的MANET信任元数据管理方案。此方案对于尝试破坏网络中信任元数据的可用性的几种安全攻击具有鲁棒性。对提出的方案的分析表明,它以较低的查询开销提供了理想的安全性和功能性。

著录项

  • 作者

    Natarajan, Vivek.;

  • 作者单位

    The Pennsylvania State University.;

  • 授予单位 The Pennsylvania State University.;
  • 学科 Computer Science.;Engineering Geological.
  • 学位 Ph.D.
  • 年度 2012
  • 页码 108 p.
  • 总页数 108
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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