Search Results - (( iot applications security algorithm ) OR ( _ application learning algorithm ))*

A Review on Attack Graph Analysis for IoT Vulnerability Assessment: Challenges, Open Issues, and Future Directions by Almazrouei O.S.M.B.H., Magalingam P., Hasan M.K., Shanmugam M.

“…In this review, core modeling techniques for IoT vulnerability assessment are highlighted, such as Markov Decision Processes (MDP), Feature Pyramid Networks (FPN), K-means clustering, and logistic regression models, along with other techniques involving genetic algorithms like fast-forward (FF), contingent fast-forwards (CFF), advanced reinforcement-learning algorithms, and HARMs models. …”

Intrusion detection system for the internet of things based on blockchain and multi-agent systems by Liang, Chao, Shanmugam, Bharanidharan, Azam, Sami, Karim, Asif, Islam, Ashraful, Zamani, Mazdak, Kavianpour, Sanaz, Idris, Norbik Bashah

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Botnet Detection in IoT Devices Using Random Forest Classifier with Independent Component Analysis by Akash, Nazmus Sakib, Rouf, Shakir, Jahan, Sigma, Chowdhury, Amlan, Uddin, Jia

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Detection of DDoS attacks in IoT networks using machine learning algorithms by Abdulrahman Alwan, Alwan Ahmed, Shah, Asadullah, Abdulrahman Alwan, Alwan Abdullah, Laghari, Shams Ul Arfeen

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Applications of deep learning algorithms for supervisory control and data acquisition intrusion detection system by Balla, Asaad, Habaebi, Mohamed Hadi, Islam, Md Rafiqul, Mubarak, Sinil

“…In this paper, we have examined and presented the most recent research on developing robust IDSs using Deep Learning (DL) algorithms, including Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Stacked Autoencoders (SAE), and Deep Belief Networks (DBN). …”
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Trust-aware authentication and authorization for IoT: a federated machine learning approach by Ahmed, Kazi Istiaque, Tahir, Mohammad, Lau, Sian Lun, Habaebi, Mohamed Hadi, Ahad, Abdul, Mughees, Amna

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Home intruder detection system using machine learning and IoT by Sahlan, Fadhluddin, Feizal, Faeez Zimam, Mansor, Hafizah

“…The main objectives of HIDES are to create a reliable home security system with the implementation of IoT, to implement the object detection algorithm to determine the presence of humans, and to develop a smart mobile application for users to monitor their houses from anywhere in the world and be alerted if any threats are detected. …”
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Internet of Things (IoT) intrusion detection by Machine Learning (ML): a review by Dehkordi, Iman Farhadian, Manochehri, Kooroush, Aghazarian, Vahe

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Adaptive security architecture for protecting RESTful web services in enterprise computing environment by Beer, M.I., Hassan, M.F.

“…A novel security component named â��intelligent security engineâ�� is introduced which learns the possible occurrences of security threats on SOA using artificial neural networks learning algorithms, then it predicts the potential attacks on SOA based on obtained results by the developed theoretical security model, and the written algorithms as part of security solution prevent the SOA attacks. …”
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Adaptive security architecture for protecting RESTful web services in enterprise computing environment by Beer, M.I., Hassan, M.F.

“…A novel security component named â��intelligent security engineâ�� is introduced which learns the possible occurrences of security threats on SOA using artificial neural networks learning algorithms, then it predicts the potential attacks on SOA based on obtained results by the developed theoretical security model, and the written algorithms as part of security solution prevent the SOA attacks. …”
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Securing IoT networks using machine learning-resistant physical unclonable functions (PUFs) on edge devices by Sheikh, Abdul Manan, Islam, Md. Rafiqul, Habaebi, Mohamed Hadi, Zabidi, Suriza Ahmad, Najeeb, Athaur Rahman, Baloch, Mazhar

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Hyperparameter tuned deep learning enabled intrusion detection on internet of everything environment by Ahmed Hamza, Manar, Hassan Abdalla Hashim, Aisha, G. Mohamed, Heba, S. Alotaibi, Saud, Mahgoub, Hany, S. Mehanna, Amal, Motwakel, Abdelwahed

“…Here, the novelty of the work is the application of MVO algorithm in fine-turning the hyperparameters involved in BiGRU model. …”
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'Chapter 7: Smartphone penetration test: Securing Industry 5.0 mobile applications' in "1st Edition, The Future of Human-Computer Integration Industry 5.0 Technology, Tools, and Al... by Eka Wahyu, Aditya, Nur Haryani, Zakaria, Fazli, Azzali, Mohamad Nazim, Jambli

“…The Future of Human-Computer Integration: Industry 5.0 Technology, Tools, and Algorithms provides a valuable insight into how Industry 5.0 technologies, tools, and algorithms can revolutionise industries and drive innovation. …”
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Development of IoT-based automated dynamic emergency response system against fire incidents in academic building by Al-Hady, Syed Mohammed Zakaria, Islam, Md Rafiqul, Rashid, Muhammad Mahbubur

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Fog-cloud scheduling simulator for reinforcement learning algorithms by Al-Hashimi, Mustafa Ahmed Adnan, Rahiman, Amir Rizaan, Muhammed, Abdullah, Hamid, Nor Asilah Wati

“…Fog computing is a popular choice for Internet of Things (IoT) applications, such as electricity, health, transportation, smart cities, security, and more. …”
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Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks by Mohammed Aswad, Firas, Saleh Ahmed,, Ali Mohammed, Ali Majeed Alhammadi, Nafea, Ahmad Khalaf, Bashar, A. Mostafa, Salama

“…IoT applications are now more popular than they used to be due to the availability of many gadgets that work as IoT enablers, including smartwatches, smartphones, security cameras, and smart sensors. …”
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Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks by Mohammed Aswad, Firas, Ahmed, Ali Mohammed Saleh, Majeed Alhammadi, Nafea Ali, Ahmad Khalaf, Bashar, A. Mostafa, Salama

“…IoT applications are now more popular than they used to be due to the availability of many gadgets that work as IoT enablers, including smartwatches, smartphones, security cameras, and smart sensors. …”
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Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks by Mohammed Aswad, Firas, Saleh Ahmed, Ali Mohammed, Ali Majeed Alhammadi, Nafea, Ahmad Khalaf, Bashar, A. Mostafa, Salama

“…IoT applications are now more popular than they used to be due to the availability of many gadgets that work as IoT enablers, including smartwatches, smartphones, security cameras, and smart sensors. …”
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Implementing server-side federated learning in an edge-cloud framework for precision aquaculture by Ng, Bryan Jing Hong

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Internet of Things (IoT) applications for estrus detection and management in precision livestock farming: a review by Ashraf, Arselan, Nisa, Syed Qamrun, Ashraf, Afreen, Gunawan, Teddy Surya, Sophian, Ali

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