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2013 IEEE International Conference on Body Sensor Networks最新文献

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Protect your BSN: No Handshakes, just Namaste! 保护你的BSN:不要握手,只要合掌!
Pub Date : 1900-01-01 DOI: 10.1109/BSN.2013.6575512
P. Bagade, Ayan Banerjee, J. Milazzo, S. Gupta
Privacy of physiological data collected by a network of embedded sensors on human body is an important issue to be considered. Physiological signal-based security is a light weight solution which eliminates the need for security key storage and complex exponentiation computation in sensors. An important concern is whether such security measures are vulnerable to attacks, where the attacker is in close proximity to the BSN and senses physiological signals through processes such as electromagnetic coupling. Recent studies show that when two individuals are in close proximity, the electrocardiogram of one person gets coupled to the electroencephalogram of the other, thus indicating a possibility of proximity-based security attacks. This paper proposes a model-driven approach to proximity-based attack on security using physiological signals and evaluates its feasibility. Results show that a proximity-based attack can be successful even without the exact reconstruction of the physiological data sensed by the attacked BSN.
嵌入式传感器网络采集的人体生理数据的隐私性是一个需要考虑的重要问题。基于生理信号的安全是一种轻量级的解决方案,它消除了传感器中安全密钥存储和复杂的幂运算的需要。一个重要的问题是,当攻击者靠近BSN并通过电磁耦合等过程感知生理信号时,这些安全措施是否容易受到攻击。最近的研究表明,当两个人靠得很近时,其中一个人的心电图会与另一个人的脑电图相关联,这表明存在基于接近度的安全攻击的可能性。提出了一种基于生理信号的模型驱动的基于邻近度的安全攻击方法,并对其可行性进行了评估。结果表明,即使没有精确重建被攻击的BSN感知到的生理数据,基于接近度的攻击也可以成功。
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引用次数: 15
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2013 IEEE International Conference on Body Sensor Networks
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