Deep learning and big data technologies for IoT security
Technology has become inevitable in human life, especially the growth of Internet of Things (IoT), which enables communication and interaction with various devices. However, IoT has been proven to be vulnerable to security breaches. Therefore, it is necessary to develop fool proof solutions by creat...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
2020
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| Online Access: | https://eprints.ums.edu.my/id/eprint/25056/7/Deep%20learning%20and%20big%20data%20technologies%20for%20IoT%20security.pdf |
| _version_ | 1796910324806320128 |
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| author | Mohamed Ahzam Amanullah Riyaz Ahamed Ariyaluran Habeeb Fariza Hanum Nasaruddin Abdullah Gani Ejaz Ahmed Abdul Salam Mohamed Nainar Nazihah Md Akim Muhammad Imran |
| author_facet | Mohamed Ahzam Amanullah Riyaz Ahamed Ariyaluran Habeeb Fariza Hanum Nasaruddin Abdullah Gani Ejaz Ahmed Abdul Salam Mohamed Nainar Nazihah Md Akim Muhammad Imran |
| author_sort | Mohamed Ahzam Amanullah |
| collection | UMS |
| description | Technology has become inevitable in human life, especially the growth of Internet of Things (IoT), which enables communication and interaction with various devices. However, IoT has been proven to be vulnerable to security breaches. Therefore, it is necessary to develop fool proof solutions by creating new technologies or combining existing technologies to address the security issues. Deep learning, a branch of machine learning has shown promising results in previous studies for detection of security breaches. Additionally, IoT devices generate large volumes, variety, and veracity of data. Thus, when big data technologies are incorporated, higher performance and better data handling can be achieved. Hence, we have conducted a comprehensive survey on state-of-the-art deep learning, IoT security, and big data technologies. Further, a comparative analysis and the relationship among deep learning, IoT security, and big data technologies have also been discussed. Further, we have derived a thematic taxonomy from the comparative analysis of technical studies of the three aforementioned domains. Finally, we have identified and discussed the challenges in incorporating deep learning for IoT security using big data technologies and have provided directions to future researchers on the IoT security aspects. |
| first_indexed | 2024-03-06T03:02:47Z |
| format | Article |
| id | ums.eprints-25056 |
| institution | Universiti Malaysia Sabah |
| language | English |
| last_indexed | 2024-03-06T03:02:47Z |
| publishDate | 2020 |
| record_format | dspace |
| spelling | ums.eprints-250562020-04-17T15:37:15Z https://eprints.ums.edu.my/id/eprint/25056/ Deep learning and big data technologies for IoT security Mohamed Ahzam Amanullah Riyaz Ahamed Ariyaluran Habeeb Fariza Hanum Nasaruddin Abdullah Gani Ejaz Ahmed Abdul Salam Mohamed Nainar Nazihah Md Akim Muhammad Imran Technology has become inevitable in human life, especially the growth of Internet of Things (IoT), which enables communication and interaction with various devices. However, IoT has been proven to be vulnerable to security breaches. Therefore, it is necessary to develop fool proof solutions by creating new technologies or combining existing technologies to address the security issues. Deep learning, a branch of machine learning has shown promising results in previous studies for detection of security breaches. Additionally, IoT devices generate large volumes, variety, and veracity of data. Thus, when big data technologies are incorporated, higher performance and better data handling can be achieved. Hence, we have conducted a comprehensive survey on state-of-the-art deep learning, IoT security, and big data technologies. Further, a comparative analysis and the relationship among deep learning, IoT security, and big data technologies have also been discussed. Further, we have derived a thematic taxonomy from the comparative analysis of technical studies of the three aforementioned domains. Finally, we have identified and discussed the challenges in incorporating deep learning for IoT security using big data technologies and have provided directions to future researchers on the IoT security aspects. 2020-02-01 Article PeerReviewed text en https://eprints.ums.edu.my/id/eprint/25056/7/Deep%20learning%20and%20big%20data%20technologies%20for%20IoT%20security.pdf Mohamed Ahzam Amanullah and Riyaz Ahamed Ariyaluran Habeeb and Fariza Hanum Nasaruddin and Abdullah Gani and Ejaz Ahmed and Abdul Salam Mohamed Nainar and Nazihah Md Akim and Muhammad Imran (2020) Deep learning and big data technologies for IoT security. Computer Communications, 151. pp. 495-517. https://doi.org/10.1016/j.comcom.2020.01.016 |
| spellingShingle | Mohamed Ahzam Amanullah Riyaz Ahamed Ariyaluran Habeeb Fariza Hanum Nasaruddin Abdullah Gani Ejaz Ahmed Abdul Salam Mohamed Nainar Nazihah Md Akim Muhammad Imran Deep learning and big data technologies for IoT security |
| title | Deep learning and big data technologies for IoT security |
| title_full | Deep learning and big data technologies for IoT security |
| title_fullStr | Deep learning and big data technologies for IoT security |
| title_full_unstemmed | Deep learning and big data technologies for IoT security |
| title_short | Deep learning and big data technologies for IoT security |
| title_sort | deep learning and big data technologies for iot security |
| url | https://eprints.ums.edu.my/id/eprint/25056/7/Deep%20learning%20and%20big%20data%20technologies%20for%20IoT%20security.pdf |
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