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This paper explores the cryptanalysis of the ASCON algorithm, a lightweight cryptographic method designed for applications like the Internet of Things (IoT). We utilize deep learning techniques to identify potential vulnerabilities within ASCON's structure. First, we provide an overview of how ASCON operates, including key generation and encryption processes.
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34 Views
This paper explores the cryptanalysis of the ASCON algorithm, a lightweight cryptographic method designed for applications like the Internet of Things (IoT). We utilize deep learning techniques to identify potential vulnerabilities within ASCON's structure. First, we provide an overview of how ASCON operates, including key generation and encryption processes.
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7 Views
This dataset accompanies the study “Universal Metrics to Characterize the Performance of Imaging 3D Measurement Systems with a Focus on Static Indoor Scenes” and provides all measurement data, processing scripts, and evaluation code necessary to reproduce the results. It includes raw and processed point cloud data from six state-of-the-art 3D measurement systems, captured under standardized conditions. Additionally, the dataset contains high-speed sensor measurements of the cameras’ active illumination, offering insights into their optical emission characteristics.
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120 Views
Twelve (12) realistic datasets encapsulating residents’ preferences, with each dataset representing the appliance-usage preferences expressed for a variant set of households by their respective residents for a specific season and day. The preferences were extracted from the REFIT dataset, a public 500MB dataset which contains real kW readings of the power output for the most energy-intensive shiftable/real-time appliances in 20 households in the UK, between September 2013 and July 2015.
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174 Views
This dataset contains human motion data collected using inertial measurement units (IMUs), including accelerometer and gyroscope readings, from participants performing specific activities. The data was gathered under controlled conditions with verbal informed consent and includes diverse motion patterns that can be used for research in human activity recognition, wearable sensor applications, and machine learning algorithm development. Each sample is labeled and processed to ensure consistency, with raw and augmented data available for use.
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59 Views
This paper describes a dataset of droplet images captured using the sessile drop technique, intended for applications in wettability analysis, surface characterization, and machine learning model training. The dataset comprises both original and synthetically augmented images to enhance its diversity and robustness for training machine learning models. The original, non-augmented portion of the dataset consists of 420 images of sessile droplets. To increase the dataset size and variability, an augmentation process was applied, generating 1008 additional images.
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127 Views
We introduce a wireless potato root tuber sensing (WPS) dataset comprising multi-channel received signal strength(RSS) data from a wireless network and ground truth annotations for potato root tubers. We design a testbed called spin, which is based on a multi-channel wireless network, the wireless network is consist of 16 TI CC25231 nodes deploy on a white rack, using this testbed, we conduct extensive measurement expriments. We first perform expriments in a static environment.
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159 Views
This dataset is utilized for adversarial camouflage generation. We collect vehicle datasets in the CARLA simulation environment under 16 weather conditions. These weather conditions are generated by combining four sun altitude angles (-90°, 10°, 45°, 90°) with four fog densities (0, 25, 50, 90). Within each weather scenario, we randomly choose 16 locations for texture generation. Camera transformation values are randomly selected within specified intervals at each car location.
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429 Views
Smart focal-plane and in-chip image processing has emerged as a crucial technology for vision-enabled embedded systems with energy efficiency and privacy. However, the lack of special datasets providing examples of the data that these neuromorphic sensors compute to convey visual information has hindered the adoption of these promising technologies.
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152 Views
This dataset contains Wi-Fi sensing data using Channel State Information (CSI) for various sleep disturbance parameters, from respiratory disturbances, to motion-based disturbances from posture shifts, leg restlessness and confusional arousals.The Wi-Fi CSI data was collected using the Wi-Fi module on the ESP32 Microcontroller units using the esp32-csi-tool.The Wi-Fi CSI respiratory disturbance data is accompanied by respiration belt data taken with the Wi-Fi measurements simultaneously using the Neulog NUL-236 respiration belt logger as ground truth.
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1024 Views