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المؤلفTabassum, Aliya
المؤلفErbad, Aiman
المؤلفGuizani, Mohsen
تاريخ الإتاحة2020-05-14T09:55:45Z
تاريخ النشر2019
اسم المنشور2019 15th International Wireless Communications and Mobile Computing Conference, IWCMC 2019
المصدرScopus
معرّف المصادر الموحدhttp://dx.doi.org/10.1109/IWCMC.2019.8766455
معرّف المصادر الموحدhttp://hdl.handle.net/10576/14861
الملخصInternet of Things (IoTs) are Internet-connected devices that integrate physical objects and internet in diverse areas of life like industries, home automation, hospitals and environment monitoring. Although IoTs ease daily activities benefiting human operations, they bring serious security challenges worth concerning. IoTs have become potentially vulnerable targets for cybercriminals, so companies are investing billions of dollars to find an appropriate mechanism to detect these kinds of malicious activities in IoT networks. Nowadays intelligent techniques using Machine Learning (ML) and Artificial Intelligence (AI) are being adopted to prevent or detect novel attacks with best accuracy. This survey classifies and categorizes the recent Intrusion Detection approaches for IoT networks, with more focus on hybrid and intelligent techniques. Moreover, it provides a comprehensive review on IoT layers, communication protocols and their security issues which confirm that IDS is required in both layered and protocol approaches. Finally, this survey discusses the limitations and advantages of each approach to identify future directions of potential IDS implementation. - 2019 IEEE.
اللغةen
الناشرInstitute of Electrical and Electronics Engineers Inc.
الموضوعDeep Learning
Intelligent Techniques
Internet of Things (IoTs)
Intrusion Detection System (IDS)
Machine Learning
العنوانA survey on recent approaches in intrusion detection system in IoTs
النوعConference Paper
الصفحات1190-1197


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