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A Secure Authentication Method of Intelligent Terminals Based on Jensen-Shannon Divergence

机译:基于詹森-香农散度的智能终端安全认证方法

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To prevent information leakage and enhance the authentication security for intelligent terminals, this paper proposes an authentication method based on Jensen-Shannon divergence, which uses behavior characteristic distribution probability vector(BCDPV) obtained by normalizing and reconstructing the behavioral characteristics as an aided authentication beyond passwords. The security of the proposed method was evaluated and the results are presented using False Rejection Rate (FRR), False Acceptance Rate (FAR) and Equal Error Rate(ERR), which shows that the proposed method do the best job of identity authentication compared with other measurement method including the cosine, correlation euclidean and chebyshev, and has high security with the ERR under 3.179%. So the proposed authentication method is a feasible and secure method which balances convenience with efficiency and reduces performance overhead.
机译:为了防止信息泄露并提高智能终端的认证安全性,提出了一种基于詹森-香农散度的认证方法,该方法利用行为特征分布概率矢量(BCDPV)对行为特征进行归一化和重构得到的行为特征分布概率向量(BCDPV)作为密码以外的辅助认证方法。 。通过假拒绝率(FRR),假接受率(FAR)和均等错误率(ERR)对所提出方法的安全性进行了评估,结果表明该方法与身份认证相比表现最好。其他测量方法包括余弦,相关欧几里得和chebyshev,并且具有较高的安全性,且ERR在3.179%以下。因此,所提出的认证方法是一种既可行又安全,兼顾便利性与效率并降低性能开销的安全可行的方法。

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