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CICIoT2023: A Real-Time Dataset and Benchmark for Large-Scale Attacks in IoT Environment.

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Summary

This study introduces a comprehensive Internet of Things (IoT) attack dataset, featuring 33 diverse attacks across seven categories. This new resource aims to enhance the development of security analytics for real-world IoT environments.

Keywords:
DDoSDoSInternet of Things (IoT)Miraibrute forcedatasetdeep learningmachine learningreconnaissancesecurityspoofingweb attacks

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Area of Science:

  • Cybersecurity
  • Computer Networks
  • Data Science

Background:

  • The Internet of Things (IoT) is rapidly expanding, integrating into critical sectors like transportation and healthcare.
  • Increased IoT adoption presents significant challenges in ensuring efficient and secure operations, including interoperability, security vulnerabilities, and standardization issues.
  • Existing IoT attack datasets often lack comprehensiveness, failing to cover a wide range of attacks or utilize extensive network topologies with real devices.

Purpose of the Study:

  • To propose a novel and extensive dataset of Internet of Things (IoT) attacks.
  • To facilitate the development and improvement of security analytics applications for real-world IoT operations.
  • To address the limitations of existing datasets by including a broader spectrum of attacks and a realistic network environment.

Main Methods:

  • Execution of 33 distinct cyberattacks against a simulated IoT network.
  • The IoT topology comprised 105 devices, simulating a realistic operational environment.
  • Attacks were categorized into seven types: DDoS, DoS, Recon, Web-based, brute force, spoofing, and Mirai, with malicious IoT devices targeting other devices.

Main Results:

  • A novel and extensive IoT attack dataset has been generated, encompassing 33 attack types.
  • The dataset reflects attacks executed within a complex IoT network of 105 devices.
  • The dataset includes a wide array of attack vectors, crucial for training robust security systems.

Conclusions:

  • The developed IoT attack dataset provides a valuable resource for advancing cybersecurity research and development.
  • This dataset enables the creation of more effective security analytics tools capable of detecting and mitigating diverse IoT threats.
  • The availability of this dataset on the CIC Dataset website will foster innovation in IoT security.