Analysis of machine learning classifiers for early detection of DDoS attacks on IoT devices

V Gaur, R Kumar - Arabian Journal for Science and Engineering, 2022 - Springer
Distributed denial-of-service attacks are still difficult to handle as per current scenarios. The
attack aim is a menace to network security and exhausting the target networks with …

Blockchain and artificial intelligence enabled privacy‐preserving medical data transmission in Internet of Things

OA Alzubi, JA Alzubi, K Shankar… - Transactions on …, 2021 - Wiley Online Library
Advancements in information technology have benefited the healthcare industry by
providing it with distinct methods of managing medical data which improve the quality of …

Dependent task offloading with deadline-aware scheduling in mobile edge networks

M Maray, E Mustafa, J Shuja, M Bilal - Internet of Things, 2023 - Elsevier
In the field of the Internet of Things (IoT), Edge computing has emerged as a revolutionary
paradigm that offers unprecedented benefits by serving the IoT at the network edge. One of …

Hasse sensitivity level: A sensitivity-aware trajectory privacy-enhanced framework with Reinforcement Learning

J Zhang, Y Huang, Q Huang, Y Li, X Ye - Future Generation Computer …, 2023 - Elsevier
LBS services generate massive amounts of trajectory data over time, which will be shared
with others for further intelligent services. Due to the ubiquity and openness of LBS, the …

FedDCS: A distributed client selection framework for cross device federated learning

M Panigrahi, S Bharti, A Sharma - Future Generation Computer Systems, 2023 - Elsevier
Abstract In cross-device Federated Learning (FL) the existing client selection approaches
are centralized, making the assumption that the participatory clients are resource-full and …

[HTML][HTML] CR-IOT based selfish attack detection via RSSI-LSTM

S Sindhuja, DM Chakkaravarthy, J Selvam - Measurement: Sensors, 2023 - Elsevier
Internet of Things-based technologies rely on cooperating between nodes to increase
network capacity. A selfish or malicious node is a node that does not cooperate with other …

[HTML][HTML] False Data Injection Attack Detection, Isolation, and Identification in Industrial Control Systems Based on Machine Learning: Application in Load Frequency …

S Mokhtari, KK Yen - Electronics, 2024 - mdpi.com
The integration of advanced information and communication technology in smart grids has
exposed them to increased cyber attacks. Traditional model-based fault detection systems …

Design of an adaptive framework with compressive sensing for spatial data in wireless sensor networks

C Sureshkumar, S Sabena - Wireless Networks, 2023 - Springer
Abstract Wireless Sensor Networks (WSNs) gather active sensor data within a specified
period to the sink node. The data transmission in restricted resource utilization in wireless …

SWIM: Sliding-Window Model contrast for federated learning

HR Zhang, R Chen, SH Wen, XQ Bian - Future Generation Computer …, 2025 - Elsevier
In federated learning, data heterogeneity leads to significant differences in the local models
learned by the clients, thereby affecting the performance of the global model. To address this …

Optimal emplacement of sensors by orbit-electron theory in wireless sensor networks

M Sathyamoorthy, S Kuppusamy, A Nayyar… - Wireless …, 2022 - Springer
Wireless sensor networks (WSNs) play a significant role in various applications, ranging
from cellphones to highly secure military operations in unmanned areas where continuous …