揭示多因素认证协议中的隐蔽漏洞:系统回顾与安全分析

IF 23.8 1区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS
Kok Wee Ang, Eyasu Getahun Chekole, Jianying Zhou
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引用次数: 0

摘要

如今,网络攻击正以惊人的速度增长,给数字社区造成了广泛的破坏。特别是,身份验证攻击已成为主要的攻击媒介,允许入侵者冒充合法用户并恶意访问资源。传统的单因素身份验证(SFA)协议依赖于单一身份验证因素,往往不足以应对日益复杂的现代网络攻击。为了解决SFA的缺点,近年来,多因素认证(MFA)协议被广泛采用,提高了对冒名顶替者的安全门槛,限制了未经授权的访问。MFA通过合并多个身份验证因素来增强安全性,例如基于知识的因素(例如密码)、基于所有权的因素(例如令牌)和基于固有的因素(例如生物识别技术)等等。然而,虽然MFA通常被认为比SFA更安全,但它并非万无一失。因为,由于MFA协议中的设计或实现缺陷,仍然可能出现严重漏洞。这些漏洞经常被设计人员或用户所忽视,直到被攻击者利用才被发现,从而可能导致灾难性的后果。不幸的是,现有的工作未能充分分析和识别MFA协议中的大多数此类关键安全漏洞。在这项工作中,我们系统地分析了MFA协议的复杂设计和构造,以发现潜在的设计级安全漏洞。为此,我们首先定义了八个安全评估标准,这些标准对于批判性地评估MFA协议的设计级安全缺陷至关重要。这些标准主要来源于现有的和新引入的MFA安全需求。然后我们回顾了一系列跨不同领域的MFA协议。使用我们建立的评估标准,我们对这些协议进行了系统的安全分析和评估,特别关注它们的设计和构建。最后,我们发现了大多数被评估的MFA协议中的几个安全缺陷。由于篇幅限制,我们选择其中的10个协议进行更深入的安全分析,并详细讨论所识别的各自缺陷。此外,我们还针对所发现的每个漏洞设计了相关的缓解策略。我们相信,我们的发现为网络安全研究人员和从业者提供了有价值的见解,帮助他们解决MFA协议中广泛的安全漏洞。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Unveiling the Covert Vulnerabilities in Multi-Factor Authentication Protocols: A Systematic Review and Security Analysis
Nowadays, cyberattacks are growing at an alarming rate, causing widespread havoc to the digital community. In particular, authentication attacks have become a dominant attack vector, allowing intruders to impersonate legitimate users and maliciously access resources. Traditional single-factor authentication (SFA) protocols, which rely on a single authentication factor are often insufficient to address the growing sophistication of modern cyberattacks. To address the shortcomings in SFA, multi-factor authentication (MFA) protocols have been widely adopted in recent years, raising the security bar against impostors and restricting unauthorized accesses. MFA enhances security by incorporating multiple authentication factors, such as knowledge-based (e.g., passwords), possession-based (e.g., tokens), and inherent-based factors (e.g., biometrics), among others. However, while MFA is generally considered more secure than SFA, it is not foolproof. Because, critical vulnerabilities may still arise due to design or implementation flaws in MFA protocols. These vulnerabilities are often overlooked by designers or users and remain undetected until exploited by attackers, potentially resulting in catastrophic consequences. Unfortunately, existing works failed to adequately analyze and identify most of such critical security flaws in MFA protocols. In this work, we systematically analyze the intricate design and construction of MFA protocols to uncover potential design-level security flaws. To this end, we first define eight security evaluation criteria that are essential to critically evaluate design-level security flaws of MFA protocols. These criteria are primarily derived from existing and newly introduced MFA security requirements. We then review a range of MFA protocols across various domains. Using our established evaluation criteria, we perform a systematic security analysis and evaluation of these protocols, particularly focusing on their design and construction. Ultimately, we uncover several security flaws in most of the MFA protocols evaluated. Due to space limitation, we select ten of those protocols for deeper security analysis and provide a detailed discussion of the respective flaws identified. Additionally, we devised relevant mitigation strategies for each of the flaws identified. We believe that our findings provide valuable insights to cybersecurity researchers and practitioners to help them addressing a wide range of security flaws in MFA protocols.
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来源期刊
ACM Computing Surveys
ACM Computing Surveys 工程技术-计算机:理论方法
CiteScore
33.20
自引率
0.60%
发文量
372
审稿时长
12 months
期刊介绍: ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods. ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.
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