使用基于脑电图的脑印系统安全密码:使用脑机接口技术解锁智能手机密码

Zuwaina Alkhyeli, Ayesha Alshehhi, Mazna Alhemeiri, Salma Aldhanhani, Khalil AlBalushi, Fatima Ali AlNuaimi, Abdelkader Nasreddine Belkacem
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引用次数: 1

摘要

随着安全成为日常活动的重要因素,由于硬件限制和黑客攻击的高风险,找到安全解锁机器和智能手机的方法是一项挑战。考虑到数字世界的安全和隐私水平,攻击者往往会领先一步。因此,这篇技术论文介绍了一种脑机接口(BCI),利用独特的生物特征作为构建复杂密码的解决方案,提高了基于主体的安全性。脑机接口(BCI)通过无创脑电图(EEG)测试测量每个受试者的大脑变化并提取相关的生物特征。该系统允许用户使用脑电波(旁路)来访问他们的设备,而不是手动输入密码(正常路径),这节省了用户的时间,并且升级了隐私级别,因为在此过程中不需要任何物理动作。这个系统也非常适合行动不便的人。我们使用了基于p300的脑机接口控制范式,该范式依赖于读取用户在观察特定物体时的脑电活动。该系统的另一个特点是,它可以提取每个个体大脑的独特特征,以产生一个唯一识别他们的网络,这被用作安全层。用户需要进入他们唯一的网络才能访问他们的设备,如果尝试失败,需要进行脑电图测试来识别用户。系统对用户访问设备时的认证过程起到积极的促进作用。只要用户的大脑电流发出指令,系统就会建立紧急呼叫。在实时实施之前,通过模拟BCI来评估项目结果,以确定错误并解决项目范围的有效性。
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Secure Password Using EEG-based BrainPrint System: Unlock Smartphone Password Using Brain-Computer Interface Technology
As security becomes a strong factor in daily activities, finding secure ways to unlock machines and smartphones is a challenge due to hardware limitations and the high risk of hacking. Considering the level of security and privacy in the digital world, attackers tend to be one step ahead. Therefore, this technical paper introduces a brain-computer interface (BCI) for increasing subject-based security using unique biometric features as a solution to build complex passwords. The BCI measures brain changes and extracts relevant bio-features from each subject using non-invasive electroencephalogram (EEG) tests. The proposed system allows users to gain access to their devices using brain waves (bypass) instead of inserting their password manually (normal path), which saves the user time and upgrades the level of privacy as no physical actions are required during this process. This system is also well suited for individuals with mobility impairments. We used the P300-based BCI controlling paradigm which depends on reading the electrical brain activity of the user when observing a particular object. The other feature of the system is that it can extract unique features of each individual brain to produce a network that uniquely identifies them, which is used as a security layer. Users need to enter their unique network to access their device with failed attempts requiring an EEG test to identify the user. The system plays an active role in facilitating user processes for authentication while accessing devices. The system establishes an urgent call whenever the user’s brain currents command it to. The project outcomes were assessed by simulating the BCI before real-time implementation to determine errors and resolve the validity of the project scope.
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