Evaluation of Blockchain-based Data Sharing Acceptance among Intelligence Community

Intelligence data are among the critical elements used as a reference for risk-assessment and decision-making regarding national security. The intelligence data are shared among intelligence agencies in the intelligence community in improving the efficiency of their services. Centralised data with central authority is highly exposed to being an easy target of attackers. Leaked or unauthorised access of the intelligence data to a non-intelligence community will bring severe effect to a state. Blockchain as immutable and high-security technology is capable of providing cryptographic data in a decentralised environment and potentially can be applied for data sharing among the intelligence community. However, the acceptance and readiness of users on blockchain usage in the intelligence community are yet to be systematically studied. Considering the statement, this paper proposed an evaluation method to study the acceptance of blockchain technology by integrating a reliable acceptance model for blockchain technology implementation in the intelligence community. The acceptance model consisted of constructs from the Technology Acceptance Model 3 (TAM 3) and Technology Readiness Index 2 (TRI 2) and was analysed using partial least squares structural equation modelling (PLS-SEM). In this study, the result indicates that TAM 3 and TRI 2.0 integration model could contribute to determining the acceptance level in developing blockchain-based intelligence data sharing for the intelligence community.

@article{Muhamad2020,
  title     = {Evaluation of Blockchain-based Data Sharing Acceptance among Intelligence Community},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {11},
  number    = {12},
  year      = {2020},
  publisher = {The Science and Information Organization},
  author    = {Wan Nurhidayat Wan Muhamad and Noor Afiza Mat Razali and Muslihah Wook and Khairul Khalil Ishak and Norulzahrah Mohd Zainudin and Nor Asiakin Hasbullah and Suzaimah Ramli},
  doi       = {10.14569/IJACSA.2020.0111270},
  url       = {https://doi.org/10.14569/IJACSA.2020.0111270}
}