Developing future human-centered smart cities: Critical analysis of smart city security, Data management, and Ethical challenges
As the globally increasing population drives rapid urbanization in various parts of the world,
there is a great need to deliberate on the future of the cities worth living. In particular, as …
there is a great need to deliberate on the future of the cities worth living. In particular, as …
Impact of word embedding models on text analytics in deep learning environment: a review
The selection of word embedding and deep learning models for better outcomes is vital.
Word embeddings are an n-dimensional distributed representation of a text that attempts to …
Word embeddings are an n-dimensional distributed representation of a text that attempts to …
Selection of effective machine learning algorithm and Bot-IoT attacks traffic identification for internet of things in smart city
Identifying cyber attacks traffic is very important for the Internet of things (IoT) security in
smart city. Recently, the research community in the field of IoT Security endeavor hard to …
smart city. Recently, the research community in the field of IoT Security endeavor hard to …
Privacy preserving Federated Learning framework for IoMT based big data analysis using edge computing
The current industrial scenario has witnessed the application of several artificial intelligence-
based technologies for mining and processing IoMT-based big data. An emerging …
based technologies for mining and processing IoMT-based big data. An emerging …
IoT malicious traffic identification using wrapper-based feature selection mechanisms
Abstract Machine Learning (ML) plays very significant role in the Internet of Things (IoT)
cybersecurity for malicious and intrusion traffic identification. In other words, ML algorithms …
cybersecurity for malicious and intrusion traffic identification. In other words, ML algorithms …
A novel web attack detection system for internet of things via ensemble classification
Internet of Things (IoT) has become one of the fastest-growing technologies and has been
broadly applied in various fields. IoT networks contain millions of devices with the capability …
broadly applied in various fields. IoT networks contain millions of devices with the capability …
A systematic review on Deep Learning approaches for IoT security
The constant spread of smart devices in many aspects of our daily life goes hand in hand
with the ever-increasing demand for appropriate mechanisms to ensure they are resistant …
with the ever-increasing demand for appropriate mechanisms to ensure they are resistant …
Reinforcement learning for feedback-enabled cyber resilience
The rapid growth in the number of devices and their connectivity has enlarged the attack
surface and made cyber systems more vulnerable. As attackers become increasingly …
surface and made cyber systems more vulnerable. As attackers become increasingly …
[HTML][HTML] Towards asynchronous federated learning for heterogeneous edge-powered internet of things
The advancement of the Internet of Things (IoT) brings new opportunities for collecting real-
time data and deploying machine learning models. Nonetheless, an individual IoT device …
time data and deploying machine learning models. Nonetheless, an individual IoT device …
An edge computing based anomaly detection method in IoT industrial sustainability
X Yu, X Yang, Q Tan, C Shan, Z Lv - Applied Soft Computing, 2022 - Elsevier
In recent years, the evolving Internet of Things (IoT) technology has been widely used in
various industrial scenarios, whereby massive sensor data involving both normal data and …
various industrial scenarios, whereby massive sensor data involving both normal data and …