Context-Aware Phishing-Resistant Authentication for Federated Identity in Internet of Things Platforms

The Internet of Things (IoT) has seen widespread adoption across various industries, enabling cross-domain collaboration among devices. As IoT platforms that allows users to manage and control these IoT devices become more prevalent, the security of IoT platforms has come under increasing scrutiny. Cryptographic authentication (CA) has long been central to authentication but poses significant security risks, such as account takeovers due to credential disclosure. Unfortunately, CA remains the most popular authentication scheme for IoT platforms, making them vulnerable to phishing attacks. Current enhancement methods, including challenge-response protocols and multifactor authentication, are still susceptible to phishing and face usability issues, particularly in cross-domain collaboration systems where seamless access is crucial. This article introduces Context-Auth, a context-aware authentication scheme designed to defend against phishing attacks without requiring tamper-resistant hardware. By incorporating contextual features of authentication and access behaviors into access credentials, Context-Auth detects inconsistencies and strengthens security. Our scheme addresses cross-domain verification challenges in federated identity scenarios, ensuring high usability across various devices without additional requirement from users. We conducted comprehensive evaluations and security analyses to ensure that Context-Auth remains secure against potential threats. The experimental results demonstrate that Context-Auth effectively defends against phishing attacks launched by real-world phishing kits.

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Institutions

Publication Details

Journal
IEEE Internet of Things Journal
Published
2024-12-11
DOI
https://doi.org/10.1109/jiot.2024.3515079
Citations
5
Primary Topic
Spam and Phishing Detection
Type
article
Field-Weighted Citation Impact
3.90

Funders

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article

Context-Aware Phishing-Resistant Authentication for Federated Identity in Internet of Things Platforms

Zhihong Tian, Hui Lu, Jian-ping Yang, Binxing Fang
5 citations
IEEE Internet of Things Journal
Spam and Phishing Detection
3.90
article

Context-Aware Phishing-Resistant Authentication for Federated Identity in Internet of Things Platforms

Zhihong Tian, Hui Lu, Jian-ping Yang, Binxing Fang
article en
5 citations

Abstract

The Internet of Things (IoT) has seen widespread adoption across various industries, enabling cross-domain collaboration among devices. As IoT platforms that allows users to manage and control these IoT devices become more prevalent, the security of IoT platforms has come under increasing scrutiny. Cryptographic authentication (CA) has long been central to authentication but poses significant security risks, such as account takeovers due to credential disclosure. Unfortunately, CA remains the most popular authentication scheme for IoT platforms, making them vulnerable to phishing attacks. Current enhancement methods, including challenge-response protocols and multifactor authentication, are still susceptible to phishing and face usability issues, particularly in cross-domain collaboration systems where seamless access is crucial. This article introduces Context-Auth, a context-aware authentication scheme designed to defend against phishing attacks without requiring tamper-resistant hardware. By incorporating contextual features of authentication and access behaviors into access credentials, Context-Auth detects inconsistencies and strengthens security. Our scheme addresses cross-domain verification challenges in federated identity scenarios, ensuring high usability across various devices without additional requirement from users. We conducted comprehensive evaluations and security analyses to ensure that Context-Auth remains secure against potential threats. The experimental results demonstrate that Context-Auth effectively defends against phishing attacks launched by real-world phishing kits.

IEEE Internet of Things JournalVol. 12(8)
Shenzhen Institute of Information Technology (CN), Harbin Institute of Technology (CN), Guangzhou University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Reduced inequalities
Openalex Percentile: Top 5%
Spam and Phishing Detection
3.90
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