BANA: Body Area Network Authentication Exploiting Channel Characteristics
BANA: Body Area Network Authentication Exploiting Channel Characteristics
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DOI：
10.1145/2185448.2185454
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发表时间：
2012-04
影响因子：
16.4
通讯作者：
Lu Shi;Ming Li;Shucheng Yu;Jiawei Yuan
中科院分区：
文献类型：
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作者：
Lu Shi;Ming Li;Shucheng Yu;Jiawei Yuan
在无线体域网络（BAN）中，节点认证是可靠可靠地收集患者关键健康信息的关键。传统的身份验证解决方案依赖于节点之间的先验信任，其建立要么需要密钥预分发，要么需要经验不足的用户非直觉地参与。大多数现有的非加密认证方案需要先进的硬件或对系统软件进行重大修改，这对于ban来说是不切实际的。本文首次提出了一种轻量级体域网络认证方案BANA。与以往的工作不同，BANA不依赖于节点之间的先验信任，可以在商用现成的低端传感器上高效实现。我们通过利用围绕BAN的多径环境自然产生的独特物理层特性来实现这一目标，即在体内信道之间以及体内和体外通信信道之间不同的接收信号强度（RSS）变化行为。基于不同的RSS变化，BANA采用聚类分析来区分来自攻击者和合法节点的信号。我们还利用多跳体上信道特性来增强认证机制的鲁棒性。BANA的有效性通过各种场景下的大量现实世界实验得到验证。结果表明，BANA能够以最小的开销准确识别多个攻击者。
In wireless body area network (BAN), node authentication is essential for trustworthy and reliable gathering of patient's critical health information. Traditional authentication solutions depend on prior trust among nodes whose establishment would require either key pre-distribution or non-intuitive participation by inexperienced users. Most existing non-cryptographic authentication schemes require advanced hardware or significant modifications to the system software, which are impractical for BANs. In this paper, for the first time, we propose a lightweight body area network authentication scheme BANA. Different from previous work, BANA does not depend on prior-trust among nodes and can be efficiently realized on commercial off-the-shelf low-end sensors. We achieve this by exploiting a unique physical layer characteristic naturally arising from the multi-path environment surrounding a BAN, i.e., the distinct received signal strength (RSS) variation behaviors among on-body channels and between on-body and off-body communication channels. Based on distinct RSS variations, BANA adopts clustering analysis to differentiate the signals from an attacker and a legitimate node. We also make use of multi-hop on-body channel characteristics to enhance the robustness of our authentication mechanism. The effectiveness of BANA is validated through extensive real-world experiments under various scenarios. It is shown that BANA can accurately identify multiple attackers with minimal amount of overhead.