Edge-based IIoT malware detection for mobile devices with offloading
The advent of 5G brought new opportunities to leapfrog beyond current Industrial Internet of
Things (IoT). However, the ever-growing IoT has also attracted adversaries to develop new …
Things (IoT). However, the ever-growing IoT has also attracted adversaries to develop new …
TransMalDE: An Effective Transformer Based Hierarchical Framework for IoT Malware Detection
With the rapid development of the Internet of Things (IoT) and cloud applications, cloud
service providers have rented out access to servers to IoT devices for computing and …
service providers have rented out access to servers to IoT devices for computing and …
End-edge coordinated inference for real-time BYOD malware detection using deep learning
Bring-Your-Own-Device (BYOD) has been widely viewed as a definite trend among
enterprises in which employees bring and use their personal smartphones for work. Despite …
enterprises in which employees bring and use their personal smartphones for work. Despite …
Efficient and lightweight convolutional networks for iot malware detection: A federated learning approach
M Abdel-Basset, H Hawash, KM Sallam… - IEEE Internet of …, 2022 - ieeexplore.ieee.org
Over the past few years, billions of unsecured Internet of Things (IoT) devices have been
produced and released, and that number will only grow as wireless technology advances …
produced and released, and that number will only grow as wireless technology advances …
Resource-and workload-aware model parallelism-inspired novel malware detection for iot devices
S Kasarapu, S Shukla… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The wide adoption of Internet of Things (IoT) devices has led to better connectivity along with
seamless communication and smart computation capabilities across the network. Despite …
seamless communication and smart computation capabilities across the network. Despite …
An efficient cloud-integrated distributed deep neural network framework for IoT malware classification
MRB Mosleh, S Sharifian - Future Generation Computer Systems, 2024 - Elsevier
The proliferation of interconnected devices in the Internet of Things (IoT) landscape has
introduced significant security concerns. With the integration of android devices, the …
introduced significant security concerns. With the integration of android devices, the …
Resource-and workload-aware malware detection through distributed computing in iot networks
S Kasarapu, S Shukla… - 2024 29th Asia and …, 2024 - ieeexplore.ieee.org
Networked IoT systems have emerged in recent years to facilitate seamless connectivity,
portability, and smarter functionality. Despite lending a plethora of benefits, IoT devices are …
portability, and smarter functionality. Despite lending a plethora of benefits, IoT devices are …
A knowledge transfer-based semi-supervised federated learning for IoT malware detection
As the demand for Internet of Things (IoT) technologies continues to grow, IoT devices have
been viable targets for malware infections. Although deep learning-based malware …
been viable targets for malware infections. Although deep learning-based malware …
SIM-FED: Secure IoT malware detection model with federated learning
Many IoT devices are presently in use without sufficient security measures. The vulnerability
of these devices to malware highlights the necessity for effective methods to identify …
of these devices to malware highlights the necessity for effective methods to identify …
[PDF][PDF] Two-stage hybrid malware detection using deep learning
With the increasing number and variety of Internet of Things (IoT) devices supporting a wide
range of services such as smart homes, smart transportation, and smart factories in smart …
range of services such as smart homes, smart transportation, and smart factories in smart …