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Robust wireless intrusion detections in vehicular and robotic networks

机译:车载和机器人网络中可靠的无线入侵检测

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摘要

Wireless intrusion detection systems have recently attracted considerable attention, specifically in the context of location-spoofing attacks. In the civilian domain, location spoofing is of growing concern due to extensive applications for future Intelligent Transport Systems (ITS), and emergency ad hoc networks. In the military domain, location spoofing attacks are of prime concern for networked multi-robot systems such as those deployed for e.g. mine sweeping, border surveillance and identification.In this thesis we will explore in detail the issue of location spoofing in emerging mobile networks. Specifically, we will investigate how to determine the time frames required for a user to be marked 'honest' or 'malicious' at required detection and false positive-rates. We also investigate the time frames needed to meet specific location verification accuracy. Having determined these time frames we will then investigate the additional time required for the mobile nodes to be moved to the required positions, necessary for the position verification, under distributed-control algorithms. Such distributed control algorithms, where each mobile node possesses no intrinsic accurate location information but only range estimates from its nearest neighbours, represent the likely emergency ad hoc deployment scenario. We now specify the contributions of the thesis in more detail.The first main contribution in this thesis is the development of a novel framework for a wireless intrusion detection algorithm that identifies malicious nodes which are not at their appropriate locations. We explicitly determine how the performance of the algorithm, as measured by detection and false positive rates, is influenced by the amount of tracking information collected. Based on the implementations of particle filters and detection thresholds set by Cramer-Rao Lower Bounds, we show how our tracking verification algorithm is capable of verifying any reported positions within a specific time frame at the required performance rates.The second main contribution in this thesis is the development of a new motion coordination scheme that can be employed in order to minimise the detection time for a specified location verification accuracy. We develop a greedy approach that achieves the optimum trajectory that minimises detection time in every sampling time. We also develop a sub-optimal approach to this problem that provides a good trade-off between performance and computational resources.The third main contribution of this thesis is the development of novel distributed control algorithms for controlling the positions of the mobile nodes that participate in the location verification. In these algorithms the nodes participating in the verification, use ranging information from nearest neighbours in order to align themselves in the best positions for the required location verification task. Such studies allow us to estimate the additional time required for our verification systems. This additional time arises because any realistic range-based distributed-motion control incurs latency costs in moving a node to a specific position. As an aside, our studies of distributed-motion control are also used to answer some key open questions regarding detection coverage in the context of military robotic detection systems.
机译:无线入侵检测系统最近引起了相当大的关注,特别是在位置欺骗攻击的背景下。在民用领域,由于未来智能运输系统(ITS)和应急自组织网络的广泛应用,位置欺骗日益受到关注。在军事领域,对于网络多机器人系统,例如部署在网络中的多机器人系统,位置欺骗攻击是首要考虑的问题。本文将详细探讨新兴移动网络中的位置欺骗问题。具体来说,我们将研究如何确定在要求的检测和误报率下将用户标记为“诚实”或“恶意”所需的时间范围。我们还将调查满足特定位置验证准确性所需的时间范围。确定了这些时间范围后,我们将在分布式控制算法下研究将移动节点移动到所需位置所需的额外时间,这对于位置验证是必需的。这样的分布式控制算法,其中每个移动节点不具有固有的准确位置信息,而仅具有来自其最近邻居的范围估计,代表了可能的紧急临时部署场景。现在,我们将更详细地说明本文的贡献。本论文的第一个主要贡献是,开发了一种新型的无线入侵检测算法框架,该算法可识别不在适当位置的恶意节点。我们显式确定通过检测和误报率衡量的算法性能如何受到收集的跟踪信息量的影响。基于Cramer-Rao Lower Bounds设置的粒子过滤器和检测阈值的实现,我们展示了我们的跟踪验证算法如何能够以所需的性能验证特定时间范围内的任何已报告位置。本文的第二个主要贡献是新运动协调方案的开发,可以采用该方案来最大程度地缩短指定位置验证准确性的检测时间。我们开发了一种贪婪的方法,该方法可实现最佳轨迹,从而在每个采样时间中将检测时间最小化。我们还针对该问题开发了一种次优方法,该方法在性能和计算资源之间提供了良好的折衷。本文的第三个主要贡献是开发了新颖的分布式控制算法,用于控制参与其中的移动节点的位置位置验证。在这些算法中,参与验证的节点使用来自最近邻居的测距信息,以便将其自身对准所需位置验证任务的最佳位置。这些研究使我们能够估计验证系统所需的额外时间。之所以会出现此额外时间,是因为任何现实的基于范围的分布式运动控制都会在将节点移动到特定位置时产生延迟成本。顺便说一句,我们对分布式运动控制的研究还用于回答一些有关军事机器人检测系统中检测范围的关键开放性问题。

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