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A comprehensive survey on IoT attacks: taxonomy, detection mechanisms and challenges

Par Conseil national de recherches du Canada

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DOITrouver le DOI : https://doi.org/10.1016/j.jiixd.2023.12.001
AuteurRechercher : ; Rechercher : ; Rechercher : Identifiant ORCID : https://orcid.org/0000-0001-5720-0941; Rechercher : 1; Rechercher : 1
Affiliation
  1. Conseil national de recherches du Canada. Technologies numériques
FormatTexte, Article
SujetInternet of Things; IoT attacks; taxonomy; vulnerabilities; detection methods; and challenges
Résumé
The Internet of Things (IoT) has set the way for the continuing digitalization of society in various manners during the past decade. The IoT is a vast network of intelligent devices exchanging data online. The security component of IoT is crucial given its rapid expansion as a new technology paradigm since it may entail safety-critical procedures and the online storage of sensitive data. Unfortunately, security is the primary challenge when adopting Internet of Things (IoT) technologies. As a result, manufacturers’ and academics’ top priority now is improving the security of IoT devices. A substantial body of literature on the subject encompasses several issues and potential remedies. However, most existing research fails to offer a comprehensive perspective on attacks inside the IoT. Hence, this survey aims to establish a structure to guide researchers by categorizing attacks in the taxonomy according to various factors such as attack domains, attack threat type, attack executions, software surfaces, IoT protocols, attacks based on device property, attacks based on adversary location and attacks based on information damage level. This is followed by a comprehensive analysis of the countermeasures offered in academic literature. In this discourse, we investigate the countermeasures suggested for the most significant security attacks in the IoT. Following this, we develop a comprehensive classification system for the many domains of security research in the IoT and Industrial Internet of Things (IIoT), accompanied by their respective remedies. In conclusion, our study has revealed several open research areas pertinent to the subject matter.
Date de publication
Maison d’éditionElsevier
Xidian University
Licence
Dans
  • Journal of Information and Intelligence (22 décembre 2023).
Langueanglais
Sous presseOui
Publications évaluées par des pairsOui
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Identificateur de l’enregistrementcac39ec4-3edc-4871-856a-a22de42cf3a1
Enregistrement créé2024-01-03
Enregistrement modifié2024-03-01
Date de modification :