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Relay selection based on social relationship prediction and information leakage reduction for mobile social networks

  • * Corresponding author: Gaofei Sun

    * Corresponding author: Gaofei Sun 
The first author is supported by National Natural Science Foundation of China (61602062) and the Natural Science Foundation of Jiangsu Province (BK20160410).
Abstract / Introduction Full Text(HTML) Figure(3) / Table(2) Related Papers Cited by
  • Despite the extensive study on relay selection in mobile social networks (MSNs), few work has taken both transmission latency (i.e. efficiency) and information leakage probability (i.e. security) into consideration. Therefore we target on designing an efficient and secure relay selection algorithm to enable communication among legitimate users while reducing the information leakage probability to other users. In this paper, we propose a novel mobility model for MSN users considering both the randomness and the sociality of the movements, based on which the social relationship among users, i.e. the meeting probabilities among the users, are predicted. Taken both efficiency and security into consideration, we design a network formation game based relay selection algorithm by defining the payoff functions of the users, designing the game evolving rules, and proving the stability of the formed network structure. Extensive simulation is conducted to validate the performance of the relay selection algorithm by using both synthetic trace and real-world trace. The results show that our algorithm outperforms other algorithms by trading a balance between efficiency and security.

    Mathematics Subject Classification: Primary: 58F15, 58F17; Secondary: 53C35.

    Citation:

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  • Figure 1.  A toy example of user $i$'s movement

    Figure 2.  The power law distribution under different $k$

    Figure 3.  Performance comparison in the real trace. (a) Comparing the A-Latency performance. (b) Comparing the A-MLP performance

    Table 1.  Simulation Settings

    Parameter Meaning Setting
    $k_r$ The exponent of the power law distribution for $\zeta_{i\tau}$ 1.7
    $k_l$ The exponent of the power law distribution for $p_i$ 3
    $C_l$ The maximum value of $p_i$ 0.6
    $R_d$ The radius of the communication range 6m
    $\epsilon$ The length of the time interval within which users keep their moving direction and speed unchanged 30s
    $\mu$ The mean of the normal distribution for users' speed 1.4
    $\sigma$ The standard deviation of the normal distribution for users' speed $\frac{\mu}{3}$
     | Show Table
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    Table 2.  Simulation Results

    ESRS Relation Leakage Rand
    A-Latency 16.2 15.4 17.9 30.4
    A-MLP 0.38 0.63 0.35 0.72
     | Show Table
    DownLoad: CSV
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