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一个网格集成的AES框架,用于在资源有限的边缘设备上提供超安全的生物识别保护

Aanjankumar Sureshkumar¹, M Maragatharajan², Kaushik Jangiti³

¹School of Computing Science and Engineering, VIT Bhopal University, Bhopal-Indore Highway, Kothrikalan, Sehore, Madhya Pradesh, 466114, India.

Scientific reports

|February 4, 2026

概括

本研究介绍了消费电子产品的轻量级指纹保护框架. 它使用AES-256 GCM和基于格子的随机性来增强生物识别数据的安全性,实现98.69%的假指纹检测准确度.

科学领域:

网络安全和加密技术
消费电子安全消费电子安全
生物识别数据的保护

背景情况:

消费电子产品 (手机,边缘设备) 的快速扩张增加了脆弱性.
持续存在的安全问题威胁到用户数据的机密性和完整性.
生物识别信息 (指纹,语音,面部映射) 的损害导致消费者遭受重大损失.

研究的目的:

为消费电子设备引入新的指纹模板保护框架.
保护用户的生物识别信息免受改和未经授权的访问.
确保资源有限的设备上的数据安全.

主要方法:

开发一个轻量化框架,对指纹数据进行有效的特征提取和规范化.
使用高级加密标准 (AES) 256 Galois/计数模式 (GCM) 与面向PIN的密钥.
集成一个轻量级的基于格子的随机生成器,以提高安全性.

主要成果:

实现了98.69%的假指纹检测准确度.
与RC5 (59.6%),ElGamal (91.1%) 和RSA (92.35%) 等最先进的方法相比,表现出更高的性能.
展示了加密和解密过程的最小周转时间.

结论:

拟议的框架为消费电子产品提供了更高的安全性和数据可访问性.
集成基于轻量级格子的随机生成器可以提高设备的安全性.
为用户提供更可靠,更安全的设备应用程序.

关键词:

在AES-256中使用AES.生物识别信息生物识别信息边缘设备边缘设备指纹数据数据的指纹数据.基于格子的安全系统.标签: 皮克皮克皮克

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