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Design Example01:23

Design Example

325
The innovation of touch-tone telephony revolutionized the telecommunications industry by replacing the traditional rotary dial with a dual-tone multi-frequency (DTMF) signaling system. This system uses a matrix-style keypad with buttons arranged in four rows and three columns, creating 12 distinct signals each assigned to a pair of frequencies. Each button press results in a simultaneous generation of two sinusoidal tones – one from a low-frequency group (697 to 941 Hz) and one from a...
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Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

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Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
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Passive Filters01:27

Passive Filters

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Passive filters are utilized to shape the frequency spectrum of signals across a diverse array of applications. These filters, using only passive elements like resistors (R), inductors (L), and capacitors (C), are capable of selectively allowing or blocking certain frequency ranges without the need for external power sources.
Low-Pass Filters
Low-pass filters are designed to transmit signals with frequencies lower than the cutoff frequency, ωc, and attenuate those above it. The cutoff...
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Active Filters01:25

Active Filters

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Active filters are electronic circuits that use operational amplifiers (op-amps), resistors, and capacitors to filter out unwanted frequency components from a signal. A first-order low-pass active filter is designed to pass signals with a frequency lower than a certain cutoff frequency and attenuate frequencies higher than that cutoff frequency. The transfer function for a first-order low-pass active filter is:
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Feedback control systems01:26

Feedback control systems

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Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
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A Novel Architecture for an Intrusion Detection System Utilizing Cross-Check Filters for In-Vehicle Networks.

Hyungchul Im1, Donghyeon Lee1, Seongsoo Lee1

  • 1Department of Intelligent Semiconductors, Soongsil University, Seoul 06978, Republic of Korea.

Sensors (Basel, Switzerland)
|May 11, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a new intrusion detection system (IDS) for Controller Area Network (CAN) bus security. The enhanced system significantly improves the detection of vehicle cyberattacks like DoS, spoofing, and fuzzy attacks.

Keywords:
controller area networkcross-check systemcybersecurityin-vehicle networkintrusion detection systemmachine learning

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Area of Science:

  • Cybersecurity
  • Automotive Engineering
  • Network Security

Background:

  • Controller Area Network (CAN) bus systems are essential for vehicular communication but are susceptible to cyber-threats.
  • Existing machine learning (ML)-based intrusion detection systems (IDS) for CAN bus have limitations in detection performance.
  • Effective detection of malicious messages is crucial for ensuring vehicle cybersecurity.

Purpose of the Study:

  • To propose a novel IDS architecture for enhancing the cybersecurity of CAN bus systems.
  • To improve the detection performance of ML-based IDS by incorporating rule-based filters.
  • To effectively distinguish between legitimate and malicious CAN messages, specifically targeting DoS, spoofing, and fuzzy attacks.

Main Methods:

  • Developed a hybrid IDS architecture combining traditional ML models with specially designed rule-based filters.
  • Filters scrutinize CAN message ID and payload data to identify specific attack characteristics.
  • Evaluated the architecture's effectiveness against Denial of Service (DoS), spoofing, and fuzzy attacks.

Main Results:

  • The proposed architecture significantly improved detection performance across all tested ML models.
  • All ML-based IDS integrated with the new architecture achieved over 99% accuracy in detecting all attack types.
  • The rule-based filters effectively captured unique features of DoS, spoofing, and fuzzy attacks.

Conclusions:

  • The novel IDS architecture offers a robust and effective solution for enhancing CAN bus cybersecurity.
  • The hybrid approach overcomes the suboptimal detection performance of purely ML-based IDS.
  • The system demonstrates high accuracy and effectiveness in identifying various cyber threats in vehicles.