Related Experiment Video
Updated: Jun 30, 2026
11:18
Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
Published on: March 2, 2015
10.2K
Metaheuristic optimized complex-valued dilated recurrent neural network for attack detection in internet of vehicular
Prasanalakshmi Balaji1, Korhan Cengiz2,3, Sangita Babu4
1Department of Computer Science, King Khalid University, Alqaraa, Saudi Arabia.
Peerj. Computer Science
|December 9, 2024
Summary
This study introduces a novel deep learning model for detecting attacks in the Internet of Vehicles (IoV). The advanced Complex-Valued Dilated Recurrent Neural Network (CV-DRNN) enhances security in vehicular networks.
Area of Science:
- Cybersecurity
- Artificial Intelligence
- Transportation Systems
Background:
- The Internet of Vehicles (IoV) enhances transportation through real-time data exchange but faces significant security challenges.
- Existing attack detection methods can be costly and complex, limiting their deployment in resource-constrained environments.
Purpose of the Study:
- To develop an innovative and efficient attack detection model for IoV networks.
- To enhance the security and reliability of vehicular communication systems.
Main Methods:
- Utilized deep learning techniques, specifically a Complex-Valued Dilated Recurrent Neural Network (CV-DRNN).
- Employed an Enhanced Exploitation in Hybrid Leader-based Optimization (EEHLO) method for optimal feature extraction from collected data.
- Collected data from online databases for model training and evaluation.
Main Results:
- The proposed CV-DRNN model demonstrated accurate attack detection capabilities in vehicular networks.
- The novel model's performance was rigorously evaluated and compared against traditional attack detection methods.
Conclusions:
- The developed deep learning model offers an effective solution for enhancing IoV security.
- This approach addresses the limitations of current methods, paving the way for more secure vehicular networks.
Related Concept Videos
01:11IP3/DAG Signaling Pathway
Membrane lipids such as phosphatidylinositol (PI) are precursors for several membrane-bound and soluble second messengers. Specific kinases phosphorylate PI and produce phosphorylated inositol phospholipids. One such inositol phospholipids are the phosphatidylinositol-4,5 bisphosphate [PI(4,5)P2], present in the inner half of the lipid bilayer. Upon ligand binding, GPCR stimulates Gq proteins to turn on phospholipase Cꞵ. Activated phospholipase Cꞵ cleaves PI(4,5)P2 and produces two-second...
01:21Distributed Loads: Problem Solving
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
01:23Propagation of Action Potentials
The propagation of an action potential refers to the process by which a nerve impulse, or "action potential," travels along a neuron.
Neurons (nerve cells) have a resting membrane potential, with a slightly negative charge inside compared to outside. This is maintained by ion channels, such as sodium (Na+) and potassium (K+) channels, which control the flow of ions. When a stimulus, like a touch or a signal from another neuron, triggers the neuron, sodium channels open, allowing sodium ions to...
Neurons (nerve cells) have a resting membrane potential, with a slightly negative charge inside compared to outside. This is maintained by ion channels, such as sodium (Na+) and potassium (K+) channels, which control the flow of ions. When a stimulus, like a touch or a signal from another neuron, triggers the neuron, sodium channels open, allowing sodium ions to...
01:25Neural Circuits
Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
01:25Network Function of a Circuit
Frequency response analysis in electrical circuits provides vital insights into a circuit's behavior as the frequency of the input signal changes. The transfer function, a mathematical tool, is instrumental in understanding this behavior. It defines the relationship between phasor output and input and comes in four types: voltage gain, current gain, transfer impedance, and transfer admittance. The critical components of the transfer function are the poles and zeros.
01:28Methods of Medium Optimization
Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...