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Game theoretic decision making in IoT-assisted activity monitoring of defence personnel

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Abstract

Innovative growth of IoT Technology has enhanced the service delivery aspects of defence sector in terms of high-tech surveillance, and reliable defence mechanisms. Along with the sensing capability for ubiquitous events, IoT Technology provides means to deliver services in time sensitive and information intensive manner. In this paper, a framework for IoT based activity monitoring of defence personnel is presented to detect the precursors of suspiciousness in terms of information outflow that can compromise the national security. Though maintaining intellectual defence personnel remained a major area of concern for every nation, still investigating reports of recent terrorist attacks in different countries have discovered the number of suspicion factors from their daily activities. The work presented in this study focuses on these factors in terms of efficient monitoring of social activities and analyzing it over suspicious scale. Moreover, Suspicious Index (SI) is defined for every personnel on the basis of their activities that can compromise national security directly or indirectly. Furthermore, automated game theoretic decision making model is presented to aid the monitoring officials in suppressing the probability of information outflow. In order to validate the system, two types of evaluations are performed. In one case, an imitative environment is considered to monitor 10 college students’ daily engagements for 7 days. The results are compared with the state-of-the-art techniques of data assessment. In the second case, a mathematical evaluation for the game theoretic decision making is performed. Results in both cases show that the proposed model achieves better performance in efficient monitoring of suspicious activities and effective decision making.

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Authors and Affiliations

  1. Guru Nanak Dev University, Regional Campus, Gurdaspur, India

    Munish Bhatia & Sandeep K. Sood

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  1. Munish Bhatia
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  2. Sandeep K. Sood
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Correspondence to Munish Bhatia.

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Bhatia, M., Sood, S.K. Game theoretic decision making in IoT-assisted activity monitoring of defence personnel. Multimed Tools Appl 76, 21911–21935 (2017). https://doi.org/10.1007/s11042-017-4611-3

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