Network intrusion detection is an effective method to identify normal and abnormal data packets to ensure the security of network. Denoising diffusion probabilistic models (DDPM) are a class of generative models, and have recently been proved to produce excellent samples. With the advantages of DDPM...
The dataset consists of high quality, Full HD video sequences (both RGB and IR), spanning multiple occurrences of multi-scale UAVs, densely annotated with bounding boxes, attributes, and flags indicating whether the target exists or not in each frame. Environment Setup Refer to: 3rd_Anti-UAV_...
Also, the frameworks support the complete encryption of a model training, inferencing process, and the dataset. All federated edge nodes perform additive encryption, whereas the blockchain exploits multiplicative encryptions for aggregating the upgraded model's parameter. Pokhrel [18] developed a new ...
Controlled blur (up to 0.5%) and exposure modifications (卤5%) were also implemented on the image dataset to improve accuracy. Three Convolutional Neural Network (CNN) architectures, single-stage detectors named YOLO v7, YOLO v8, and Roboflow...
To achieve real-time tracking of UAV targets, we employed the tracking-by-detection mode in machine learning, with the network-modified YOLOv3 (you only look once v3) as the target detector and Deep SORT as the target tracking correlation algorithm. We established a drone tracking dataset that...
The UAVSwarm dataset can be widely used in training and testing of various UAV detection tasks and UAV swarm MOT tasks. Keywords: unmanned aerial vehicles (UAV) swarm; multiple object tracking; unmanned aerial vehicles (UAV) detection; image dataset...
The simulation results also show that the proposed framework is robust against various types of attacks, demonstrating the effectiveness of the proposed intrusion detection system. In our proposed framework, we used the CICIDS2017 dataset to evaluate the performance of our UAV-assisted intrusion ...
4.1. Dataset First, we used a handheld infrared thermal-imaging device to collect some UAV data at night. The equipment parameters were as follows: The IR resolution was 640 × 512 px; the pixel size was 12 μμm; the focal length of the infrared objective lens was 50 mm; the field ...
anti-UAV; UAV detection; UAV tracking; UAV dataset; anti-UAV systems1. Introduction With the rapid advancement of technology, unmanned aerial vehicles (UAVs) have found numerous urban IoT (Internet of Things) applications in fields such as rescue operations [1], surveillance [2,3], edge ...
An IoT Environment Based Framework for Intelligent Intrusion Detection. CMC Comput. Mater. Contin. 2023, 75, 2365–2381. [Google Scholar] [CrossRef] Goyal, N.; Sharma, S.; Rana, A.K.; Tripathi, S.L. (Eds.) Internet of Things: Robotic and Drone Technology; CRC Press: Boca Raton, ...