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Lightweight Payload Encryption-Based Authentication Scheme for Advanced Metering Infrastructure Sensor Networks.

Nasr Abosata1, Saba Al-Rubaye1, Gokhan Inalhan1

  • 1School of Aerospace, Transport and Manufacturing, Cranfield University, Cranfield MK43 0AL, UK.

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Summary
This summary is machine-generated.

This study introduces a lightweight authentication scheme, PEOS, for secure data in the Internet of Things (IoT) and Advanced Metering Infrastructure (AMI) systems. PEOS enhances security and efficiency for resource-constrained distributed sensors.

Keywords:
AESCoAPDTLSIoTlightweightpayload encryptionsecuritysensors

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Area of Science:

  • Computer Science
  • Cybersecurity
  • Network Engineering

Background:

  • The Internet of Things (IoT) enables widespread data collection via sensors, with Advanced Metering Infrastructure (AMI) being a key application.
  • Security and privacy are critical concerns in IoT, especially for distributed sensors with two-way communication.
  • Existing authentication and encryption protocols may not be efficient enough for resource-constrained smart sensors in IoT environments.

Purpose of the Study:

  • To propose an efficient and lightweight security authentication scheme for distributed sensors in IoT applications.
  • To address the need for enhanced data confidentiality, privacy, and message authentication in resource-constrained environments.
  • To optimize the integration of security protocols within existing IoT communication architectures.

Main Methods:

  • Development of a Payload Encryption-based Optimisation Scheme (PEOS) for lightweight authentication.
  • Integration and optimization of Datagram Transport Layer Security (DTLS) features within the Constrained Application Protocol (CoAP) architecture.
  • Design of a payload encryption scheme and an Optimized Advanced Encryption Standard (OP-AES) with modifications to DTLS handshaking, retransmission, and duplicate feature removal.

Main Results:

  • The PEOS scheme demonstrates improved efficiency and lightweight authentication for distributed sensors.
  • Optimized AES operations, including parallel S-box execution and delayed Mixcolumns, enhance CoAP performance.
  • Evaluations on Contiki OS using the Cooja simulator show PEOS achieves better throughput and reduces message size overhead by 9% and 23% compared to PbMA and basic DTLS/CoAP.

Conclusions:

  • The proposed PEOS scheme offers an effective solution for lightweight security and authentication in IoT and AMI systems.
  • PEOS successfully balances security requirements with the constraints of distributed sensor networks.
  • The optimized approach provides a viable pathway for enhancing the security of energy consumption data in smart grids.