A Synoptic Review on Feature Selection and Machine Learning models used for Detecting Cyber Attacks in IoT

B Bojarajulu, S Tanwar, A Rana - 2021 IEEE 8th Uttar Pradesh …, 2021 - ieeexplore.ieee.org
There is a colossal increase in the cyberattack on the Internet of Things due to the rapid
increase in its adoption rate worldwide. For ease of use, these devices are accessed by the …

Machine Learning based IoT-BotNet Attack Detection Using Real-time Heterogeneous Data

A Ahmed, C Tjortjis - 2022 International Conference on …, 2022 - ieeexplore.ieee.org
Security is a major concern for Internet of Things (IoT) devices. Due to their vulnerabilities,
these devices are an easy target for unauthorized access. Traditional security mechanisms …

Deep Learning and Metaheuristics based Cyber Threat Detection in Internet of Things Enabled Smart City Environment

S Das, Y Manchala, SK Rout, S kumar Panda - 2023 - researchsquare.com
Recently, the extensive use of Internet of Things (IoT) applications has a stronger impact and
greater contribution to the development of the smart city. A smart city (SC) uses IoT-based …

Models and Algorithms for Optimization of the Backup Equipment for the Intelligent Automated Control System Smart City

V Lakhno, A Mazaraki, D Kasatkin… - … : Proceedings of ICICCT …, 2022 - Springer
Algorithms for a neural network analyzer (NA) used in the decision support system (DSS)
during the selection of the composition of the backup equipment (CBE) for intelligent …

BoT-IoT: Detection of DDoS Attacks in Internet of Things for Smart Cities

A Sharma, H Babbar - 2023 10th International Conference on …, 2023 - ieeexplore.ieee.org
The recent research in technology brought a new era called the Internet of Things (IoT). This
modern technology created internet-connected things such as smartphones, smart …

Benchmarking the Bagging and Boosting (B & B) Algorithms for Modeling Optimized Autonomous Intrusion Detection Systems (AIDS)

S Upadhyaya, D Mehrotra - SN Computer Science, 2023 - Springer
The mapped mathematical models (MMMs) in machine learning are instrumental in
obtaining segregated yet effective solutions for security-specific scenarios in intrusion …

Performance enhancement of intrusion detection system using machine learning algorithms with feature selection

AS Raju, MM Rashid, F Sabrina - 2021 31st International …, 2021 - ieeexplore.ieee.org
Cybersecurity has emerged as a major concern for individuals and organisations due to
digitalisation. As a result, data is growing exponentially making it susceptible to various …

[PDF][PDF] Detecting Ransomware within Real Healthcare Medical Records Adopting Internet of Medical Things using Machine and Deep Learning Techniques

R ELGawish, M Abo-Rizka, R ELGohary… - International Journal of …, 2022 - academia.edu
The Internet of Medical Things was immensely implemented in healthcare systems during
the covid 19 pandemic to enhance the patient's circumstances remotely in critical care units …

Anomaly detection using deep learning approach for IoT smart city applications

S Shibu, S Kirubakaran, KP Remamany… - Multimedia Tools and …, 2024 - Springer
With the advancements of IoT devices, many smart applications start to rule this era. In
particular, smart cities has been adapted and realized by many countries around the world …

[PDF][PDF] Cyber Security Threats Detection And Protection Using Machine Learning Techniques In Iot

MP Rana, BP Patil - Journal of Theoretical and Applied …, 2023 - researchgate.net
Recently, technology has enhanced itself to the 4th Industrial Revolution, with the Internet of
Things (IoT), Edge computing, Computer safety, and along with Cyber-attacks are rapidly …