ICTACT Journal on Communication Technology

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Securing It Networking Environment in Cran Using Dehaene–changeux Model Driven Moth-flame Optimization


Affiliations
1 Department of Computer Engineering, Amrutvahini College of Engineering, Sangamner, India
2 Electronics and Telecommunication Engineering Department, Government College of Engineering, Amravati, India
     

   Subscribe/Renew Journal


In the dynamic landscape of telecommunications, the evolution of Communication Radio Access Networks (CRAN) has introduced unprecedented challenges to the security of IT networking environments. As the demand for high-speed connectivity and seamless data transmission grows, safeguarding CRAN becomes paramount. With the proliferation of cyber-attacks and the complexity of CRAN architecture, conventional security measures prove insufficient, necessitating an innovative and adaptive approach. Existing methodologies lack the adaptability required to combat emerging threats effectively. This research bridges this gap by proposing the integration of the Dehaene–Changeux Model, renowned for its applicability in cognitive neuroscience, with Moth-Flame Optimization, a nature-inspired algorithm known for its efficiency in solving complex optimization problems. This research addresses the pressing need for a robust security framework using the Dehaene–Changeux Model Driven Moth-Flame Optimization approach. It elucidates the utilization of the Dehaene–Changeux Model to mimic cognitive responses, coupled with Moth-Flame Optimization for real-time adaptability. These models form a dynamic defense mechanism against evolving security threats in the CRAN environment. Results obtained from simulation and testing validate the efficacy of the proposed security model. The adaptive nature of the Dehaene–Changeux Model, combined with the optimization capabilities of Moth-Flame Optimization, showcases a significant enhancement in CRAN security. The research contributes a pioneering solution to fortify IT networking environments in CRAN, ensuring resilience against current and future cyber threats.

Keywords

CRAN, Dehaene–Changeux Model, Moth-Flame Optimization, IT networking security, Cognitive Security.
Subscription Login to verify subscription
User
Notifications
Font Size

  • M. Mofarreh-Bonab and S.A. Ghorashi, “A Low Complexity and High Speed Gradient Descent Based Secure Localization in Wireless Sensor Networks”, Proceedings of International Conference on Computer and Knowledge Engineering, pp. 300-303, 2013.

  • R. Garg, A.L. Varna and M. Wu, “An Efficient Gradient Descent Approach to Secure Localization in Resource Constrained Wireless Sensor Networks”, IEEE Transactions on Information Forensics and Security, Vol. 7, No. 2, pp. 717-730, 2012.

  • B. Gobinathan, P. Niranjan and V.P. Sundramurthy, “A Novel Method to Solve Real Time Security Issues in Software Industry using Advanced Cryptographic Techniques”, Scientific Programming, Vol. 2021, pp. 1-9, 2021.

  • A. Junpei, B. Leonard, X. Fatos and A. Durresi, “A Cluster Head Selection Method for Wireless Sensor Networks based on Fuzzy Logic”, Proceedings of IEEE International Conference on Region 10, pp. 1-4, 2007.

  • Zainab R. Zaidi, Brian L. Mark, “Mobility Tracking Based on Autoregressive Models”, IEEE Transactions on Mobile Computing, Vol. 10, No. 1, pp. 32-43, 2009.

  • A. Renuka and K.C. Shet, “Hierarchical Approach for Key Management in Mobile Ad hoc Networks”, International Journal of Computer Science and Information Security, Vol. 5, No. 1, pp. 87-95, 2009.

  • Shouling Ji, Raheem Beyah and Zhipeng Cai, “Snapshot and Continuous Data Collection in Probabilistic Wireless Sensor Networks”, IEEE Transactions on Mobile Computing, Vol. 13, No. 3, pp. 626-637, 2014.

  • D. Suganyadevi and G. Padmavathi, “Dynamic Clustering for QoS based Secure Multi Cast Key Distribution in Mobile Ad Hoc Networks”, International Journal of Computer Science, Vol. 7, No. 5, pp. 11-16, 2010.

  • M. Madiajagan, T.B. Rehman and B. Pattanaik, “IoT-based Blockchain Intrusion Detection using Optimized Recurrent Neural Network”, Multimedia Tools and Applications, Vol. 78, pp. 1-22, 2023.

  • P. Jayasree, “Non-Deterministic Paillier Endorsement Asymmetric Key Cryptosystem-Based Whirlpool Hashing Quotient Filter for Secured Data Access on Cloud Storage”, Proceedings of International Conference on Smart Intelligent Computing and Applications, pp. 127-140, 2020.

  • R. Sahay and C.D. Jensen, “The Application of Software Defined Networking on Securing Computer Networks: A Survey”, Journal of Network and Computer Applications, Vol. 131, pp. 89-108, 2019.


Abstract Views: 138

PDF Views: 1




  • Securing It Networking Environment in Cran Using Dehaene–changeux Model Driven Moth-flame Optimization

Abstract Views: 138  |  PDF Views: 1

Authors

Rahul Laxmanrao Paikrao
Department of Computer Engineering, Amrutvahini College of Engineering, Sangamner, India
Prashant Laxmanrao Paikrao
Electronics and Telecommunication Engineering Department, Government College of Engineering, Amravati, India

Abstract


In the dynamic landscape of telecommunications, the evolution of Communication Radio Access Networks (CRAN) has introduced unprecedented challenges to the security of IT networking environments. As the demand for high-speed connectivity and seamless data transmission grows, safeguarding CRAN becomes paramount. With the proliferation of cyber-attacks and the complexity of CRAN architecture, conventional security measures prove insufficient, necessitating an innovative and adaptive approach. Existing methodologies lack the adaptability required to combat emerging threats effectively. This research bridges this gap by proposing the integration of the Dehaene–Changeux Model, renowned for its applicability in cognitive neuroscience, with Moth-Flame Optimization, a nature-inspired algorithm known for its efficiency in solving complex optimization problems. This research addresses the pressing need for a robust security framework using the Dehaene–Changeux Model Driven Moth-Flame Optimization approach. It elucidates the utilization of the Dehaene–Changeux Model to mimic cognitive responses, coupled with Moth-Flame Optimization for real-time adaptability. These models form a dynamic defense mechanism against evolving security threats in the CRAN environment. Results obtained from simulation and testing validate the efficacy of the proposed security model. The adaptive nature of the Dehaene–Changeux Model, combined with the optimization capabilities of Moth-Flame Optimization, showcases a significant enhancement in CRAN security. The research contributes a pioneering solution to fortify IT networking environments in CRAN, ensuring resilience against current and future cyber threats.

Keywords


CRAN, Dehaene–Changeux Model, Moth-Flame Optimization, IT networking security, Cognitive Security.

References