In the paper, we use the Microsoft Visual Studio Development Kit and C# programming language to implement a chaos-based electroencephalogram (EEG) encryption system involving three encryption levels. A chaos logic map, initial value, and bifurcation parameter for the map were used to generate Level I chaos-based EEG encryption bit streams. Two encryption-level parameters were added to these elements to generate Level II chaos-based EEG encryption bit streams. An additional chaotic map and chaotic address index assignment process was used to implement the Level III chaos-based EEG encryption system. Eight 16-channel EEG Vue signals were tested using the encryption system. The encryption was the most rapid and robust in the Level III system. The test yielded superior encryption results, and when the correct deciphering parameter was applied, the EEG signals were completely recovered. However, an input parameter error (e.g., a 0.00001 % initial point error) causes chaotic encryption bit streams, preventing the recovery of 16-channel EEG Vue signals.
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January 2025
Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China.
The complete manipulation of Jones matrix phase-channels using metasurfaces brings forth unparalleled possibilities across diverse wavefront modulation applications. Traditionally, achieving independent control over all four phase-channels usually involves the introduction of chirality with multilayer or three-dimensional metasurfaces. Here, we present a general chirality-free method that relies on polarization base transformation with a planar minimalist metasurface, effectively decoupling the four Jones matrix phase-channels, thereby unleashing the fundamental boundaries imposed by conventional linear or circular polarization bases.
View Article and Find Full Text PDFSci Rep
December 2024
Faculty of Engineering and Technology, Multimedia University, Melaka, Malaysia.
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View Article and Find Full Text PDFData Brief
December 2024
Department of Computer Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran.
With the development of smart buildings, the risks of cyber-attacks against them have also increased. One of the popular and evolving protocols used for communication between devices in smart buildings, especially HVAC systems, is the BACnet protocol. Machine learning algorithms and neural networks require datasets of normal traffic and real attacks to develop intrusion detection (IDS) and prevention (IPS) systems that can detect anomalies and prevent attacks.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Computer Science, College of Education for Pure Sciences, University of Basrah, Basrah, Iraq.
Vehicular Ad-hoc Networks (VANETs) are growing into more desirable targets for malicious individuals due to the quick rise in the number of automated vehicles around the roadside. Secure data transfer is necessary for VANETs to preserve the integrity of the entire network. Federated learning (FL) is often suggested as a safe technique for exchanging data among VANETs, however, its capacity to protect private information is constrained.
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