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Evaluating the impact of adversarial traffic patterns on vanet communication using veins simulation

Henry Agyapong

arXiv:2608.14583v1cs.NIcs.LG

TL;DR

VANETs remain vulnerable to adversarial traffic, but coordinated and mobility-aware attacks have limited empirical evaluation. This paper simulates flooding, false-information, and congestion attacks across traffic densities, finding that flooding can reduce PDR by 96.55% and throughput by 27.89% at low density.

  • Problem

    Empirical evidence is limited on how coordinated and mobility-aware adversarial traffic patterns affect VANET performance in realistic simulations.

  • Method

    The study simulates message flooding, false-information dissemination, and coordinated congestion attacks across low, medium, and high traffic densities, evaluating PDR, packet loss, and throughput.

  • Results

    96.55% PDR reduction and 27.89% throughput reduction occurred under message flooding at low traffic density, which also completely stopped network communication.

  • Takeaways & Limitations

    The results demonstrate that the evaluated malicious traffic types seriously disrupt VANET communication and expose substantial network vulnerability.

  • Takeaways & Limitations

    Hybrid attack strategies combining multiple simultaneous adversarial behaviors remain unevaluated and require further study.

Abstract

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Vehicular Ad Hoc Networks (VANETs) are a key component of intelligent transportation systems, enabling real-time communication between vehicles. However, their open and dynamic nature makes them highly vulnerable to adversarial behaviors that can disrupt communication reliability. This paper investigates the impact of adversarial traffic patterns on VANET performance using the Veins simulation framework integrated with OMNeT++ and SUMO. We design and evaluate multiple adversarial scenarios, including message flooding, false information dissemination, and coordinated congestion attacks, under varying traffic densities and mobility conditions. The study measures key performance metrics such as packet delivery ratio (PDR), end-to-end delay, and network throughput. Experimental results show that adversarial traffic can reduce PDR by up to 96.55%, with message flooding at low density producing a throughput reduction of 27.89%, and significantly degrade overall network efficiency. The findings highlight critical vulnerabilities in VANET communication and provide insights into designing more resilient and secure vehicular networks.

1 Introduction

VANETs support important vehicle and roadside-unit applications but remain vulnerable to adversarial traffic because of their decentralized, highly mobile, wireless environment. This paper addresses limited systematic evaluation by using Veins to model multiple attacks and quantify communication degradation under varying traffic densities.

  • Problem: Adversarial traffic behavior—including message flooding, false-data dissemination, and coordinated attacks—can inject disruptive communication patterns that degrade VANET performance.These behaviors are identified as critical and underexplored threats to network reliability.
  • Research gap: Prior research has examined VANET routing and normal-condition performance, but limited work systematically evaluates adversarial traffic under realistic mobility scenarios.The paper motivates its study by addressing this evaluation gap.
  • Study scope: The study uses a Veins-based simulation framework to model adversarial VANET behaviors and evaluate network degradation under varying traffic densities.Its stated goals include analyzing communication-performance effects and quantifying degradation in key network metrics.
  • Attack scenarios: The evaluated scenarios comprise message flooding, false information dissemination, and coordinated attacks.Flooding overloads communication channels, false information disrupts reliability, and coordinated congestion maximizes packet collisions and delay.
  • Contribution: The paper provides insights into VANET communication vulnerabilities, security, robustness, and resilience limitations.These objectives frame the contribution beyond measuring performance degradation.

2 RELATED WORK

Prior VANET research has emphasized routing, mobility, optimization, and performance evaluation under cooperative conditions, often using Veins with OMNeT++ and SUMO. Security research identifies important vulnerabilities, but empirical evaluation of coordinated, mobility-aware adversarial traffic in realistic VANET simulations remains limited; this paper addresses that gap with three attack scenarios across traffic densities.

  • Existing VANET Simulation Research: Prior VANET studies primarily examined routing protocols, mobility models, and performance optimization under benign conditions, commonly using Veins with OMNeT++ and SUMO.Veins integrates OMNeT++ and SUMO to study realistic vehicular communication scenarios.
  • Existing VANET Simulation Research: VANET performance research evaluated packet delivery ratio, delay, and throughput across traffic densities, but often assumed cooperative, non-malicious environments.These assumptions limit evaluation of adversarial effects on communication performance.
  • Security Vulnerabilities: Wireless ad hoc network security research highlights denial-of-service, message-tampering, and Sybil attacks, whose effects can be especially serious in real-time VANET communication.VANETs’ real-time communication makes adversarial behavior particularly impactful.
  • Research Gap: Empirical evaluation remains limited for coordinated and mobility-aware adversarial traffic patterns affecting VANET performance in realistic simulations.The identified gap concerns hostile traffic behavior under realistic mobility and communication conditions.
  • Research Gap and Contribution: This paper addresses the gap by simulating message flooding, false-information dissemination, and congestion attacks under different traffic-density settings using Veins.The study extends Veins-based analysis to hostile vehicular traffic conditions.

3 EXPERIMENT GOALS AND DESIGN

The experiment evaluates how three adversarial traffic patterns affect VANET communication across low, medium, and high vehicle densities. It uses an OMNeT++–SUMO–Veins simulation architecture and compares communication performance with PDR, throughput, and total packet loss.

  • Experiment goals: The study evaluates normal VANET communication, quantifies flooding, false-information, and congestion attacks, and identifies resistance weaknesses across three vehicle densities.The densities are low, medium, and high.
  • Simulation architecture: OMNeT++ performs discrete-event network simulation, SUMO models realistic vehicle mobility, and Veins 5.3.1 bridges the two through TraCI.TraCI exchanges mobility and network information in real time during simulation.
  • Traffic and network setup: The experiments use 10, 25, and 50 vehicles for low-, medium-, and high-density scenarios, respectively, with each scenario running for 200 seconds.Vehicles enter gradually at 3-second intervals on the Erlangen road network using IEEE 802.11p at 5.9 GHz, with one RSU supporting V2I and V2V communication.
  • Adversarial scenarios: The attacks model message flooding, false information dissemination, and coordinated congestion through excessive transmissions, incorrect road identifiers, and synchronized burst transmissions.Flooding uses 50 extra WSMs per vehicle, false-information attackers comprise one-third of vehicles, and coordinated congestion uses a 50% attacker ratio with three packets per burst for up to 30 transmissions.
  • Performance metrics: Performance is assessed using packet delivery ratio, network throughput, and total packet loss to capture successful delivery, effective data transfer, and undelivered packets.PDR is measured at the MAC layer because attacks affect the wireless channel, while total packet loss is calculated by Veins MAC-layer components.

4 EXPERIMENT ANALYSIS AND DISCUSSION

Baseline performance deteriorated sharply under message flooding, false information dissemination, and coordinated congestion attacks. Flooding produced PDR below 6% across densities, while false-information and coordinated-congestion attacks caused severe but comparatively higher delivery ratios and substantial packet losses.

  • Baseline Results: Baseline PDR declined from 100% at low density to 96.65% at medium and 93.45% at high density, while throughput increased with density.Low-density throughput was 1,048.80 bps, medium-density throughput was 3,030.48 bps, and high-density throughput was 4,018.56 bps.
  • Flooding Attack Results: 96.55 percentage points: message flooding reduced low-density PDR from 100% to 3.45%.Flooding also increased lost packets from zero to 3,832 in the low-density baseline comparison.
  • Flooding Attack Results: Less than 6%: flooding produced consistently low PDR across all three densities, with 15,045 medium-density and 44,605 high-density packets lost.Channel saturation degraded SNIR, while transmission and reception conflicts increased at the MAC layer.
  • False Information Attack Results: 16.02%: false-information dissemination achieved the highest PDR in the low-density case, while medium- and high-density PDR remained about 11%.Across densities, PDR ranged from 11.11% to 16.02%; correctly delivered packets could still contain fabricated road identifiers, emergency alerts, or congestion warnings.
  • Coordinated Congestion Attack Results: 166,848 packets lost: the combined coordinated congestion attack recorded the greatest packet losses and 125,844.96 bps throughput.The attack generated 3,142, 7,222, and 12,925 packets at low, medium, and high density, respectively; low-density PDR was 19.95%.

5 Comparative Analysis

The comparison shows that all three adversarial traffic patterns substantially undermine VANET communication, with message flooding producing the lowest PDR. Throughput can rise during attacks despite legitimate packet delivery collapsing, making it an unreliable standalone reliability measure.

  • Attack Comparison: Below 6% PDR occurred under message flooding at every traffic density, making it the most effective attack for reducing channel reliability.The passage identifies message flooding as producing the lowest PDR across all density variations.
  • Density Effects: PDR decreased from low to medium traffic density for all three attacks, then remained constant from medium to high density.High-density channels provide better communication conditions but experience greater hostile-attack impact.
  • Throughput Analysis: Raw throughput increased at medium and high densities during attacks because assault-generated traffic increased received traffic, while flooding reduced legitimate-packet PDR below 6%.The contrast shows why throughput alone cannot reliably measure network reliability under adversarial conditions.
  • Overall Vulnerability: From 100% to 19.95% PDR, coordinated congestion at low density caused an 80 percentage point loss, despite being the mildest attack.The results indicate vulnerability to all three malicious traffic patterns and the need for detection and mitigation systems.

6 Conclusion and Future Work

The study finds that message flooding, false information dissemination, and coordinated congestion attacks substantially undermine VANET communication across low, medium, and high traffic densities. Future work should evaluate hybrid strategies combining multiple adversarial behaviors.

  • Conclusion: The study evaluates message flooding, false information dissemination, and coordinated congestion attacks at low, medium, and high traffic densities using Packet Delivery Rate, packet loss, and network throughput.These metrics were used to estimate attack effects on VANET communication effectiveness.
  • Conclusion: 96.55%: message flooding decreases Packet Delivery Rate at low traffic density and completely stops network communication.At the same condition, throughput decreases by 27.89%.
  • Conclusion: 83.98%: false information dissemination decreases PDR and corrupts transmitted information.The supplied passage reports the PDR reduction and information corruption but is truncated before further details.
  • Conclusion: PDR is significantly lowered from 80% up to 96.55%, demonstrating that malicious traffic can seriously disrupt VANET communication processes.The findings emphasize the vulnerability of modern VANETs to malicious traffic types.
  • Future Work: Hybrid attack strategies combining multiple simultaneous adversarial behaviors should be studied to determine their compounded effect.The study’s simulation framework provides a baseline for evaluating hybrid-strategy efficiency in detail.
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