Authors : Priya.M; Viji.K

Volume/Issue : Volume 10 - 2025, Issue 1 - January

Google Scholar : https://tinyurl.com/3epu287w

Scribd : https://tinyurl.com/4uj9j23k

DOI : https://doi.org/10.5281/zenodo.14621435

Abstract : Protecting sensitive data, personnel, and assets in the defence sector against unauthorised access and security breaches requires authentication. Strong authentication protocols are needed to preserve the security and integrity of military networks, systems, and facilities as defence operations become more digitalised. The development of safe and efficient monitoring systems is necessary due to the quick advancements in technology and the increasing complexity of defence operations. This article addresses the unique security issues faced by the military industry by combining blockchain technology, AI-powered facial recognition technology, and Internet of Things-based digital twin technology. The proposed system builds a robust platform for monitoring people, assets, and critical infrastructure by utilising blockchain's inherent advantages, including decentralisation, immutability, and enhanced security. By employing facial recognition technology to instantly identify and validate people, the system automates access control and grants only authorised individuals access to vital resources or restricted areas. To prevent manipulation and safeguard data privacy, licensed workers' biometric information is safely stored on the blockchain. The decentralised ledger records each access attempt, permitted or not, establishing an unchangeable audit trail for compliance and accountability. Blockchain-integrated smart contracts enable automated responses to security incidents, like alerting authorities, setting off alarms, or securing areas when unauthorised individuals are detected. The distributed form of the framework eliminates single points of failure, boosting defences against upcoming cyberattacks and guaranteeing business continuity.

Keywords : Authentication, Block Chain, Digital Twin Technology, Face Recognition, Monitoring Systems, Smart Contracts, Security Branches, Unauthorised Access.

References :

1. Pătraşcu, Petrișor. "Emerging technologies and National Security: The impact of IoT in critical infrastructures protection and defencesector." Land Forces Academy Review 26.4 (2021): 423-429.
2. Sirait, Jonathan, Hazen Alrasyid, and Nadia Aurora Soraya. "Strengthening The Defense Industry's Independence Through The Internet Of Things In The Manufacturing Sector: A Review." International Journal of Science, Technology & Management 4.2 (2023): 335-340.
3. Sharma, Pradip Kumar, et al. "Wearable computing for defence automation: Opportunities and challenges in 5G network." IEEE Access 8 (2020): 65993-66002.
4. Bhatia, Munish, and Ankush Manocha. "Cognitive framework of food quality assessment in IoT-inspired smart restaurants." IEEE Internet of Things Journal 9.9 (2020): 6350-6358.
5. Javed, Safdar Hussain, et al. "APT adversarial defence mechanism for industrial IoT enabled cyber-physical system." IEEE Access 11 (2023): 74000-74020.
6. Bhatia, Munish, et al. "Internet of things-inspired healthcare system for urine-based diabetes prediction." Artificial Intelligence in Medicine 107 (2020): 101913.
7. Bhatia, Munish, Sandeep K. Sood, and Simranpreet Kaur. "Quantumized approach of load scheduling in fog computing environment for IoT applications." Computing 102.5 (2020): 1097-1115.
8. Li, Luning, et al. "Digital twin in aerospace industry: A gentle introduction." IEEE Access 10 (2021): 9543-9562.
9. Zhou, Xiaokang, et al. "Deep-learning-enhanced multitarget detection for end–edge–cloud surveillance in smart IoT." IEEE Internet of Things Journal 8.16 (2021): 12588-12596.
10. Fukawa, Nobuyuki, and Aric Rindfleisch. "Enhancing innovation via the digital twin." Journal of Product Innovation Management 40.4 (2023): 391-406.