Adaptive User Authentication in Mobile Crowd Sensing via Nash Equilibrium Strategy Optimization

International Journal of Electronics and Communication Engineering

© 2025 by SSRG - IJECE Journal

Volume 12 Issue 7

Year of Publication : 2025

Authors : S. Domi Evangeline, G. Usha

10.14445/23488549/IJECE-V12I7P132

How to Cite?

S. Domi Evangeline, G. Usha, "Adaptive User Authentication in Mobile Crowd Sensing via Nash Equilibrium Strategy Optimization," SSRG International Journal of Electronics and Communication Engineering, vol. 12,  no. 7, pp. 407-414, 2025. Crossref, https://doi.org/10.14445/23488549/IJECE-V12I7P132

Abstract:

Depending on user-contributed data from mobile devices for large-scale sensing applications, Mobile Crowd Sensing (MCS) has severe risks from malicious activity, erroneous data, and inadequate authentication techniques. This work proposes a paradigm for adaptive user authentication, overcoming these obstacles by using the Nash equilibrium method optimization. The concept sees user-platform interactions as a game of strategy in which users try to increase value while reducing system-compromising risk. The system comprises a lightweight cryptographic protocol to safeguard communications without overloading devices, probabilistic validation to modify authentication intensity dynamically, and an adaptive trust score technique to assess user dependability based on previous behavior. Trust ratings support validation that uses resources effectively; uncertainty given by probabilistic checkpointing discourages manipulation. In terms of lowest overhead and low false positive rates, the suggested method outperforms traditional static and reputation-based models, thereby obtaining excellent detection accuracy. Regarding user identification in real-time MCS systems, the proposed model offers an innovative, scalable, safe alternative.

Keywords:

Mobile crowd sensing, Nash equilibrium, Adaptive authentication, Trust scoring, Game theory.

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