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Related Concept Videos

Probability Histograms01:17

Probability Histograms

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A probability histogram is a visual representation of a probability distribution. Similar a typical histogram, the probability histogram consists of contiguous (adjoining) boxes. It has both a horizontal axis and a vertical axis. The horizontal axis is labeled with what the data represents. The vertical axis is labeled with probability. Each rectangular bar in the histogram is 1 unit wide, which suggests that the area under each bar equals the probability, P(x), where x is 1, 2, 3, and so on.
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Histogram01:05

Histogram

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The histogram is a graphical representation in the x-y form of data distribution in a data set. The horizontal x-axis is labeled with what the data represents (for instance, distance from your home to school). The vertical y-axis is labeled either frequency or relative frequency (or percent frequency or probability).
A histogram graph consists of contiguous (adjoining) boxes. The heights of the bars correspond to frequency values. The graph will have the same shape with respective labels. The...
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Weighted Mean00:57

Weighted Mean

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While taking the arithmetic, geometric, or harmonic mean of a sample data set, equal importance is assigned to all the data points. However, all the values may not always be equally important in some data sets. An intrinsic bias might make it more important to give more weightage to specific values over others.
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Related Experiment Videos

Research on Network Intrusion Detection Based on Weighted Histogram Algorithm for In-Vehicle Ethernet.

Yutong Wang1, Yujing Wu1, Yihu Xu1

  • 1College of Engineering, Yanbian University, Yanji 133002, China.

Sensors (Basel, Switzerland)
|September 19, 2025
PubMed
Summary

This study introduces a weighted histogram algorithm to detect network intrusions in In-Vehicle Ethernet, enhancing security for intelligent transportation systems. The new method significantly improves anomaly detection rates compared to traditional algorithms.

Keywords:
Audio Video Transport ProtocolIn-Vehicle Ethernetintrusion detectionnetwork securityweighted histogram algorithm

Related Experiment Videos

Area of Science:

  • Computer Science
  • Network Security
  • Intelligent Transportation Systems

Background:

  • In-Vehicle Ethernet is critical for next-generation intelligent transportation systems.
  • Existing In-Vehicle Ethernet networks are vulnerable to data theft, tampering, and malicious attacks.
  • Audio Video Transport Protocol data characteristics and attack vectors are analyzed.

Purpose of the Study:

  • To propose an innovative network intrusion detection method for In-Vehicle Ethernet.
  • To enhance the overall security and stability of in-vehicle communication networks.
  • To address specific network security threats within the In-Vehicle Ethernet framework.

Main Methods:

  • Analysis of Audio Video Transport Protocol data characteristics.
  • Development of a novel network intrusion detection method utilizing a weighted histogram algorithm.
  • Comparative performance evaluation against traditional Bayesian and decision tree algorithms.

Main Results:

  • The proposed weighted histogram algorithm achieved a 99.7% anomaly detection rate.
  • Demonstrated a 15.8% improvement over the traditional Bayesian algorithm.
  • Showed a 6.9% increase in detection rate compared to the decision tree algorithm.

Conclusions:

  • The weighted histogram algorithm significantly enhances In-Vehicle Ethernet security.
  • The proposed method improves the stability and anti-attack capabilities of in-vehicle networks.
  • Provides a robust network security foundation for the Internet of Vehicles.