随机部署无线网络中的安全定位
Towards Secure Localization in Randomly Deployed Wireless Networks
摘要：
能够准确地定位无线设备，同时保证针对欺骗攻击的高级别安全性，使定位链中的所有参与者（例如，最终用户、网络运营商和位置服务提供商）。一方面，大多数现有的定位系统是为无害的环境而设计的，其中不存在恶意的对手。这使得它们非常容易受到来自入侵者、攻击甚至无意错误（故障）的安全威胁，因此在敌对环境中几乎是徒劳的。另一方面，现有的安全定位解决方案做出关于网络拓扑的某些（有利的）假设（例如，目标设备位于由参考点形成的凸包内），这限制了它们的适用性。因此，这项工作解决了随机部署的无线网络中存在的恶意攻击者，其目标是操纵（欺骗）的估计过程和禁用准确的定位目标定位的问题。我们提出了一个低复杂度的解决方案，基于聚类和加权中心质量来检测攻击者，只使用最少的参考点，之后，我们解决了定位问题的二分法。从定位精度和攻击者检测成功率两个角度研究了该方法，推导出了攻击者检测概率的上下界的封闭表达式。通过计算机仿真验证了该方法的有效性，其性能优于现有的方法。
英文摘要：
Being able to accurately locate wireless devices, while guaranteeing high-level of security against spoofing attacks, benefits all participants in the localization chain (e.g., end users, network operators, and location service providers). On the one hand, most of existing localization systems are designed for innocuous environments, where no malicious adversaries are present. This makes them highly susceptible to security threats coming from interferers, attacks or even unintentional errors (malfunctions) and thus, practically futile in hostile settings. On the other hand, existing secure localization solutions make certain (favorable) assumptions regarding the network topology (e.g., that the target device lies within a convex hull formed by reference points), which restrict their applicability. Therefore, this work addresses the problem of target localization in randomly deployed wireless networks in the presence of malicious attackers, whose goal is to manipulate (spoof) the estimation process and disable accurate localization. We propose a low-complex solution based on clustering and weighted central mass to detect attackers, using only the bare minimum of reference points, after which we solve the localization problem by a bisection procedure. The proposed method is studied from both localization accuracy and success in attacker detection point of views, where closed-form expressions for upper and lower bounds on the probability of attacker detection are derived. Its performance is validated through computer simulations, which corroborate the effectiveness of the proposed scheme, outperforming the state-of-the-art methods.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
