Identifying and Mitigating Phishing Attack Threats in IoT Use Cases Using a Threat Modelling Approach

Syed Ghazanfar Abbas, Ivan Vaccari, Faisal Hussain, Shahzaib Zahid, Ubaid Ullah Fayyaz, Ghalib A. Shah, Taimur Bakhshi, Enrico Cambiaso

Allbwn ymchwil: Cyfraniad at gyfnodolynErthygladolygiad gan gymheiriaid

1 Wedi eu Llwytho i Lawr (Pure)

Crynodeb

Internet of things (IoT) is a technology that enables our daily life objects to connect on the Internet and to send and receive data for a meaningful purpose. In recent years, IoT has led to many revolutions in almost every sector of our society. Nevertheless, security threats to IoT devices and networks are relentlessly disruptive, because of the proliferation of Internet technologies. Phishing is one of the most prevalent threats to all Internet users, in which attackers aim to fraudulently extract sensitive information of a user or system, using fictitious emails, websites, etc. With the rapid increase in IoT devices, attackers are targeting IoT devices such as security cameras, smart cars, etc., and perpetrating phishing attacks to gain control over such vulnerable devices for malicious purposes. In recent decades, such scams have been spreading, and they have become increasingly advanced over time. By following this trend, in this paper, we propose a threat modelling approach to identify and mitigate the cyber-threats that can cause phishing attacks. We considered two significant IoT use cases, i.e., smart autonomous vehicular system and smart home. The proposed work is carried out by applying the STRIDE threat modelling approach to both use cases, to disclose all the potential threats that may cause a phishing attack. The proposed threat modelling approach can support the IoT researchers, engineers, and IoT cyber-security policymakers in securing and protecting the potential threats in IoT devices and systems in the early design stages, to ensure the secure deployment of IoT devices in critical infrastructures.
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Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - 14 Gorff 2021
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