A Secure ECG based Smart Authentication Scheme for IoT Devices

Preeti Chandrakar, Aashish Kumar, Rifaqat Ali, R. D. Patidar
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引用次数: 1

Abstract

In this super-evolving world, there exist numerous hidden vulnerabilities and any kind of security breach in recent times would have implications in ways which are even difficult to imagine. To counter such probable scenarios the demand evolved to design security protocols which are sound enough to counter most of such situations in near future. In this scheme, an ECG based user authentication protocol for smart IoT devices is proposed. ECG is one of the unique characteristic traits of any individual which is experimented to remain similar throughout, provided any biological changes have not occured. The scheme uses the captured ECG signal from a smart IoT device taken as raw input by the computation model. The signal is then used to extract the user characteristics such as the QRS complex, P peak, T peak, etc. A feature vector is derived after pre-processing of the signal, which is then used by the computation model to check for the authenticity of the individual. The final authentication of the user depends upon the similarity index of the feature vector generated by the existing user’s record captured during registration. The data used here is from the ECG ID database and the obtained accuracy is measured close to 94.2%. A comprehensive study of the performance of the protocol is presented taking communication cost, computation cost, storage cost, and even the security features as the parameters for comparison.
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一种基于安全心电的物联网设备智能认证方案
在这个超级进化的世界里,存在着许多隐藏的漏洞,最近任何一种安全漏洞都会以难以想象的方式产生影响。为了应对这种可能出现的情况,人们要求设计足够可靠的安全协议,以便在不久的将来应对大多数此类情况。在该方案中,提出了一种基于心电的智能物联网设备用户认证协议。心电图是任何个体的独特特征之一,在没有发生任何生物学变化的情况下,它在实验中始终保持相似。该方案使用从智能物联网设备捕获的心电信号作为计算模型的原始输入。然后利用该信号提取用户特征,如QRS复合体、P峰、T峰等。对信号进行预处理后,得到一个特征向量,然后计算模型使用该特征向量来检查个体的真实性。用户的最终认证依赖于注册过程中捕获的现有用户记录生成的特征向量的相似度索引。这里使用的数据来自ECG ID数据库,得到的精度接近94.2%。从通信成本、计算成本、存储成本甚至安全特性等方面对协议的性能进行了全面的研究。
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