Deep learning for cyber threat detection in IoT networks: A review

Aldhaheri, Alyazia; Alwahedi, Fatima; Ferrag, Mohamed Amine; Battah, Ammar

doi:10.1016/j.iotcps.2023.09.003

Cited by 16 publications

(7 citation statements)

References 56 publications

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“…[27] Surveys collaborative data-access enablers in IIoT, vital for secure and efficient data handling. [28] A forward-looking survey that discusses the role of machine learning and GenAI in IoT security. [29] Evaluates cyber threats in Industrial IoT and discusses the relevant standards.…”

Section: Ref Contribution and Significance [5]mentioning

confidence: 99%

“…These emerging advancements leverage AI techniques to address the unique challenges of IoT security, enabling distributed security intelligence, on-device security processing, and adaptive and self-defending IoT systems. Some notable advancements in AI for IoT security include: Tools like ChatGPT, which fall under the umbrella of GenAI, have emerged over the past few years and are reshaping several industries, including cybersecurity [28]. GenAI has revolutionized threat detection and system protection, which is essential for the security of the IoT.…”

Section: A Advancements In Ai For Iot Securitymentioning

confidence: 99%

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Securing the Internet of Things in Artificial Intelligence Era: A Comprehensive Survey

Humayun,

Tariq,

Alfayad

et al. 2024

IEEE Access

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The Internet of Things (IoT) has revolutionized various domains, enabling interconnected devices to communicate and exchange data. The integration of Artificial Intelligence (AI) in IoT systems further enhances their capabilities and potential benefits. Unfortunately, in the era of AI, ensuring the privacy and security of the IoT faces novel and specific challenges. IoT security is imperative, necessitating comprehensive strategies, including comprehension of IoT security challenges, implementation of AI methodologies, adoption of resilient security frameworks, and handling of privacy and ethical concerns to construct dependable and secure IoT systems. It is vital to note that the term 'security' encompasses a more comprehensive view than cyberattacks alone. Therefore, with an emphasis on securing against cyberattacks, this comprehensive survey also includes physical security threats on the IoT. It investigates the complexities and solutions for IoT systems, placing particular emphasis on AI-based security techniques. The paper undertakes a categorization of the challenges associated with ensuring IoT security, investigates the utilization of AI in IoT security, presents security frameworks and strategies, underscores privacy and ethical considerations, and provides insights derived from practical case studies. Furthermore, the survey sheds light on emerging trends concerning IoT security in the AI era. This survey provides significant contributions to the understanding of establishing dependable and secure IoT systems through an exhaustive examination of the present condition of IoT security and the ramifications of AI on it.

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Section: Ref Contribution and Significance [5]mentioning

confidence: 99%

Section: A Advancements In Ai For Iot Securitymentioning

confidence: 99%

Securing the Internet of Things in Artificial Intelligence Era: A Comprehensive Survey

Humayun,

Tariq,

Alfayad

et al. 2024

IEEE Access

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“…Canva, yang user-friendly dan populer, digunakan untuk menciptakan variasi dan fleksibilitas dalam pembuatan slide presentasi. Melalui integrasi output dari ChatGPT dengan Canva, para guru dapat menghasilkan presentasi yang lebih kreatif sesuai dengan gaya masing-masing (Aldhaheri et al, 2024).…”

Section: Pendahuluanunclassified

Pemanfaatan Artificial intelligence dalam Pembuatan Presentasi bagi Guru-Guru Brainfor Islamic School Kisaran

Maharani,

Anggraeni,

Nofitri

2024

JISS

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Pengabdian Masyarakat berjudul "Pemanfaatan Artificial Intelligence dalam Pembuatan SlidePresentasi bagi Guru-Guru” ini merupakan upaya mendukung inovasi dalam dunia pendidikankhususnya di tingkat Sekolah Dasar (SD) dan Pendidikan Anak Usia Dini (PAUD) di SekolahBrainfor Islamic School Kisaran. Permasalahan yang dihadapi guru-guru pada tingkat ini adalahkendala dalam menyusun materi presentasi yang cepat, serta menarik perhatian orangtua siswamaupun siswanya dan mampu efektif dalam menyampaikan informasi. Dalam menyikapipermasalahan ini, kami mengusulkan solusi melalui pemanfaatan kecerdasan buatan (AI) denganfokus pada penggunaan ChatGPT yang dapat memberikan panduan desain, layout, dan kontenpresentasi secara otomatis, sesuai dengan tujuan yang ingin di sampaikan Narasumber atau Guru.Penggunaan ChatGPT ini bertujuan membantu guru-guru Brainfor dalam menyusun slidepresentasi yang sesuai alur ataupun prosedur serta relevan dengan kurikulum yang berlaku.ChatGPT ini akan dapat diakses melalui platform online atau aplikasi, memudahkan akses danpenggunaan oleh para guru. Dalam upaya mendukung pemahaman dan penerapan teknologi ini,proposal ini juga mencakup pelatihan intensif bagi guru-guru mengenai penggunaan alat AIdalam menyusun materi presentasi yang berkualitas.Selain itu, sebagai langkah inovatif tambahan, narasumber melibatkan penggunaan platformdesain grafis Canva dalam pembuatan slide presentasi. Canva adalah alat yang user-friendly danpopuler dalam pembuatan desain grafis, termasuk pembuatan slide presentasi. Para guru akandiajarkan cara mengintegrasikan output dari Chat GPT yang dikembangkan dengan Canva,sehingga para guru-guru dapat menghasilkan presentasi yang lebih kreatif dan sesuai dengangaya masing-masing. Langkah ini diambil untuk memberikan variasi dan fleksibilitas lebihkepada guru dalam menciptakan materi yang menarik perhatian siswa atau objek lainnya.Rencana kegiatan diawali dengan identifikasi kebutuhan guru-guru melalui survei dan dialoguntuk memastikan bahwa AI yang digunakan dapat menjawab kebutuhan yang sebenarnya.Setelah itu, dilanjutkan dengan penggunaan Canva dalam desain grafis. Pelatihan ini tidak hanyamencakup aspek teknis, tetapi juga penerapan praktis dalam kegiatan pengetahuan danpembelajaran sehari-hari.Setelah fase pelatihan, guru-guru akan diberikan kesempatan untuk mengimplementasikanpengetahuan yang diperoleh mereka dalam pembelajaran di kelas. Selama periode ini, merekajuga akan mendapatkan dukungan dan pemantauan penggunaan ChatGPT AI dan Canva untukmemberikan dampak positif atau hasil pembelajaran.Dengan menyatukan kecerdasan buatan, platform desain grafis, dan pelatihan guru, proyek inibertujuan menciptakan solusi holistik untuk meningkatkan kualitas pembelajaran di tingkat SDdan PAUD. Melalui pendekatan ini, diharapkan para guru dapat dengan lebih kreatif dan efektifmenyampaikan materi kepada siswa, maupun objek lainnya serta menghasilkan dampak positifpada proses pembelajaran dan pemahaman mereka.

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“…Compared to traditional machine learning, it can automatically extract image features, achieving higher recognition accuracy, and more accurately and objectively identify and grade stresses. At the same time, deep learning models have been proven to be superior to previous image recognition techniques [ 17 ], with numerous studies showing their high recognition accuracy and broad application range advantages [ 18 , 19 ].…”

Section: Introductionmentioning

confidence: 99%

Multimodal deep learning-based drought monitoring research for winter wheat during critical growth stages

Yao,

Wu,

Liu

et al. 2024

PLoS ONE

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Wheat is a major grain crop in China, accounting for one-fifth of the national grain production. Drought stress severely affects the normal growth and development of wheat, leading to total crop failure, reduced yields, and quality. To address the lag and limitations inherent in traditional drought monitoring methods, this paper proposes a multimodal deep learning-based drought stress monitoring S-DNet model for winter wheat during its critical growth periods. Drought stress images of winter wheat during the Rise-Jointing, Heading-Flowering and Flowering-Maturity stages were acquired to establish a dataset corresponding to soil moisture monitoring data. The DenseNet-121 model was selected as the base network to extract drought features. Combining the drought phenotypic characteristics of wheat in the field with meteorological factors and IoT technology, the study integrated the meteorological drought index SPEI, based on WSN sensors, and deep image learning data to build a multimodal deep learning-based S-DNet model for monitoring drought stress in winter wheat. The results show that, compared to the single-modal DenseNet-121 model, the multimodal S-DNet model has higher robustness and generalization capability, with an average drought recognition accuracy reaching 96.4%. This effectively achieves non-destructive, accurate, and rapid monitoring of drought stress in winter wheat.

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Deep learning for cyber threat detection in IoT networks: A review

Cited by 16 publications

References 56 publications

Securing the Internet of Things in Artificial Intelligence Era: A Comprehensive Survey

Securing the Internet of Things in Artificial Intelligence Era: A Comprehensive Survey

Pemanfaatan Artificial intelligence dalam Pembuatan Presentasi bagi Guru-Guru Brainfor Islamic School Kisaran

Multimodal deep learning-based drought monitoring research for winter wheat during critical growth stages

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