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Quality, Reliability, Security and Robustness in Heterogeneous Systems. 17th EAI International Conference, QShine 2021, Virtual Event, November 29–30, 2021, Proceedings

Research Article

Anti-eavesdropping Proportional Fairness Access Control for 5G Networks

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  • @INPROCEEDINGS{10.1007/978-3-030-91424-0_9,
        author={Shankar K. Ghosh and Avirup Das and Sasthi C. Ghosh and Nabanita Das},
        title={Anti-eavesdropping Proportional Fairness Access Control for 5G Networks},
        proceedings={Quality, Reliability, Security and Robustness in Heterogeneous Systems. 17th EAI International Conference, QShine 2021, Virtual Event, November 29--30, 2021, Proceedings},
        proceedings_a={QSHINE},
        year={2021},
        month={11},
        keywords={Eavesdropping Secrecy throughput Proportional fairness scheduling Hidden Markov model Physical layer security},
        doi={10.1007/978-3-030-91424-0_9}
    }
    
  • Shankar K. Ghosh
    Avirup Das
    Sasthi C. Ghosh
    Nabanita Das
    Year: 2021
    Anti-eavesdropping Proportional Fairness Access Control for 5G Networks
    QSHINE
    Springer
    DOI: 10.1007/978-3-030-91424-0_9
Shankar K. Ghosh1, Avirup Das2, Sasthi C. Ghosh2, Nabanita Das2
  • 1: Presidency University
  • 2: Indian Statistical Institute

Abstract

Due to the open access nature, communication over unlicensed band, suffers from security threats like eavesdropping. Eavesdroppers are unwanted nodes, attempting to overhear the signal transmitted between two legitimate mobile terminals (MTs), often for malicious purposes. Apart from security issues, it results in significant degradation of secrecy throughput, i.e., the throughput achieved by a legitimate user without being overheard by eavesdroppers. Since with the present technology, it is quite difficult to identify the eavesdroppers even in5G, the average throughput of the legitimateMTs decreases when the serving base station schedules the eavesdroppers as well, based on the channel condition only. So far, the issue of eavesdropping has rarely been considered in the context of scheduling. In this paper, we propose an anti-eavesdropping proportional fairness (APF) mechanism considering the possibility of eavesdroppers. Our proposedAPFtechnique first estimates a set of suspected eavesdroppers based on sleep mode information, and then reduces the possibility of scheduling these eavesdroppers by imposing penalties. Penalty assignments are based on past average throughput, current channel conditions and modulation/coding schemes. Both Hidden Markov model based analysis and simulations confirm that the proposedAPFtechnique outperforms the traditional proportional fairness protocol in terms of anti-eavesdropping efficiency and secrecy throughput.

Keywords
Eavesdropping Secrecy throughput Proportional fairness scheduling Hidden Markov model Physical layer security
Published
2021-11-17
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-91424-0_9
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