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基于 Sierpinski 三角形的分形在智能设备中的认证技术。

A Fractal-Based Authentication Technique Using Sierpinski Triangles in Smart Devices.

机构信息

Faculty of Computing and Information Technology, University of Sialkot, Sialkot 51040, Pakistan.

College of Computer Science and Engineering, University of Jeddah, Jeddah 21577, Saudi Arabia.

出版信息

Sensors (Basel). 2019 Feb 7;19(3):678. doi: 10.3390/s19030678.

Abstract

The prevalence of smart devices in our day-to-day activities increases the potential threat to our secret information. To counter these threats like unauthorized access and misuse of phones, only authorized users should be able to access the device. Authentication mechanism provide a secure way to safeguard the physical resources as well the information that is processed. Text-based passwords are the most common technique used for the authentication of devices, however, they are vulnerable to a certain type of attacks such as brute force, smudge and shoulder surfing attacks. Graphical Passwords (GPs) were introduced as an alternative for the conventional text-based authentication to overcome the potential threats. GPs use pictures and have been implemented in smart devices and workstations. Psychological studies reveal that humans can recognize images much easier and quicker than numeric and alphanumeric passwords, which become the basis for creating GPs. In this paper a novel Fractal-Based Authentication Technique (FBAT) has been proposed by implementing a Sierpinski triangle. In the FBAT scheme, the probability of password guessing is low making system resilient against abovementioned threats. Increasing fractal level makes the system stronger and provides security against attacks like shoulder surfing.

摘要

在我们的日常活动中,智能设备的普及增加了我们的秘密信息面临潜在威胁的可能性。为了应对这些威胁,如未经授权的访问和滥用手机,只有授权用户才能访问设备。身份验证机制提供了一种安全的方式来保护物理资源以及处理的信息。基于文本的密码是用于设备身份验证的最常见技术,但是,它们容易受到某些类型的攻击,例如暴力破解、指纹和肩窥攻击。图形密码 (Graphical Passwords, GPs) 作为传统基于文本的身份验证的替代方法被引入,以克服潜在的威胁。GPs 使用图片,并已在智能设备和工作站中实现。心理学研究表明,人类比数字和字母数字密码更容易和更快地识别图像,这成为创建 GPs 的基础。在本文中,通过实现 Sierpinski 三角形,提出了一种新的分形基认证技术 (Fractal-Based Authentication Technique, FBAT)。在 FBAT 方案中,密码猜测的概率较低,使系统能够抵御上述威胁。增加分形级别可以使系统更强大,并提供针对肩窥等攻击的安全性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4da2/6387263/02c0fbeec843/sensors-19-00678-g004.jpg

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