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Blockchain-based cryptographic framework for secure data transmission in IoT edge environments using ECaps-Net.

Islabudeen Mohamed Meerasha1, Jafar Ali Ibrahim Syed Masood2, Thanapal P3

  • 1School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India. islabudeen.m@vit.ac.in.

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Summary
This summary is machine-generated.

This study introduces an enhanced Intrusion Detection System (IDS) for Internet of Things (IoT) edge computing. The system uses deep learning and blockchain to secure data transmission, achieving high accuracy in detecting threats.

Keywords:
BlockchainEdge computingEnhanced capsule networkInternet of thingsIntrusion detectionMerkle-damgard cryptographic algorithmSecure data transmissionSqueeze and excitation

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Area of Science:

  • Cybersecurity
  • Computer Networks
  • Artificial Intelligence

Background:

  • Internet of Things (IoT) and edge computing present unique security challenges due to distributed data processing.
  • Traditional cloud-based security is insufficient for dynamic IoT environments, necessitating edge-level solutions.
  • Intrusion Detection Systems (IDS) are crucial for real-time monitoring and mitigation of attacks in IoT ecosystems.

Purpose of the Study:

  • To propose an Enhanced Deep Learning (DL)-based IDS integrated with a Blockchain-Based Cryptographic-Algorithm for secure IoT edge computing.
  • To enhance data privacy, integrity, and security in distributed IoT environments.
  • To develop a robust defense against malicious access targeting cloud servers and edge devices.

Main Methods:

  • Data preprocessing and normalization of intrusion datasets.
  • Classification using an Enhanced Capsule Network (ECaps-Net) with a Squeeze and Excitation (SE) block.
  • Secure data transmission using Blockchain technology and Merkle-Damgard cryptographic hashing.

Main Results:

  • The proposed IDS achieved high accuracy, with maximums of 98.90% on KDD Cup-99 and 98.78% on UNSW-NB 15 datasets.
  • Demonstrated superior performance compared to existing intrusion detection methods.
  • Successfully protected cloud servers and edge devices from unauthorized access.

Conclusions:

  • The integrated DL and blockchain framework offers a reliable and efficient solution for secure data transmission in IoT edge environments.
  • The ECaps-Net effectively identifies and classifies network intrusions.
  • Blockchain integration ensures data integrity and confidentiality, enhancing overall IoT security.