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Enhancing Two-Step Random Access in LEO Satellite Internet an Attack-Aware Adaptive Backoff Indicator (AA-BI)

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  • Jiajie Dong

    (Anhui Province Key Laboratory of Electronic Restriction, Hefei 230037, China
    College of Electronic Engineering, National University of Defense Technology, Hefei 230037, China)

  • Yong Wang

    (Anhui Province Key Laboratory of Electronic Restriction, Hefei 230037, China
    College of Electronic Engineering, National University of Defense Technology, Hefei 230037, China)

  • Qingsong Zhao

    (Anhui Province Key Laboratory of Electronic Restriction, Hefei 230037, China
    College of Electronic Engineering, National University of Defense Technology, Hefei 230037, China)

  • Ruiqian Ma

    (Anhui Province Key Laboratory of Electronic Restriction, Hefei 230037, China
    College of Electronic Engineering, National University of Defense Technology, Hefei 230037, China)

  • Jiaxiong Yang

    (Anhui Province Key Laboratory of Electronic Restriction, Hefei 230037, China
    College of Electronic Engineering, National University of Defense Technology, Hefei 230037, China)

Abstract

Low-Earth-Orbit Satellite Internet (LEO SI), with its capability for seamless global coverage, is a key solution for connecting IoT devices in areas beyond terrestrial network reach, playing a vital role in building a future ubiquitous IoT system. Inspired by the IEEE 802.15.4 Improved Adaptive Backoff Algorithm (I-ABA), this paper proposes an Attack-Aware Adaptive Backoff Indicator (AA-BI) mechanism to enhance the security and robustness of the two-step random access process in LEO SI. The mechanism constructs a composite threat intensity indicator that incorporates collision probability, Denial-of-Service (DoS) attack strength, and replay attack intensity. This quantified threat level is smoothly mapped to a dynamic backoff window to achieve adaptive backoff adjustment. Simulation results demonstrate that, with 200 pieces of user equipment (UE), the AA-BI mechanism significantly improves the access success rate ( ASR ) and jamming resistance rate (JRR) under various attack scenarios compared to the I-ABA and Binary Exponential Backoff (BEB) algorithms. Notably, under high-attack conditions, AA-BI improves ASR by up to 25.1% and 56.6% over I-ABA and BEB, respectively. Moreover, under high-load conditions with 800 users, AA-BI still maintains superior performance, achieving an ASR of 0.42 and a JRR of 0.68, thereby effectively ensuring the access performance and reliability of satellite Internet in malicious environments.

Suggested Citation

  • Jiajie Dong & Yong Wang & Qingsong Zhao & Ruiqian Ma & Jiaxiong Yang, 2025. "Enhancing Two-Step Random Access in LEO Satellite Internet an Attack-Aware Adaptive Backoff Indicator (AA-BI)," Future Internet, MDPI, vol. 17(10), pages 1-15, October.
  • Handle: RePEc:gam:jftint:v:17:y:2025:i:10:p:454-:d:1762880
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