Article: Intelligent early intrusion prediction and route migration framework for secure data transmission Journal: International Journal of Communication Networks and Distributed Systems (IJCNDS) 2026 Vol.32 No.4 pp.398 - 419 Abstract: A method of managing resources for networks that makes use of dynamic software-defined networking (SDN) that allows administrators to regulate resources in real-time. However, traditional models have met challenges, including high packet drop, energy consumption, and low performance. To overcome these challenges, a novel solution called hyena sequence intrusion detection (HSID) is proposed. This involves the creation of required nodes in the network, and the hyena function continually monitors node status. It effectively eliminates high-energy nodes, ensuring the sustainability of the routing process. The framework is implemented and rigorously tested in the Python platform, with a thorough evaluation of network efficiency parameters. In comparison, various metrics are considered, including energy consumption, throughput, packet drop, detection accuracy, and confidentiality rate. The results demonstrate higher performance satisfaction with the proposed model, emphasising its effectiveness in addressing the identified challenges and enhancing overall network security and efficiency. Inderscience Publishers - linking academia, business and industry through research

Title: Intelligent early intrusion prediction and route migration framework for secure data transmission

Authors: S. Kranthi; M. Kanchana; M. Suneetha

Addresses: Department of Computing Technologies, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu, 603203, India ' Department of Computing Technologies, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu, 603203, India ' Department of Information Technology, Velagapudi Ramakrishna Siddhartha Engineering College, Kanuru, Vijayawada, Andhra Pradesh, 520007, India

Abstract: A method of managing resources for networks that makes use of dynamic software-defined networking (SDN) that allows administrators to regulate resources in real-time. However, traditional models have met challenges, including high packet drop, energy consumption, and low performance. To overcome these challenges, a novel solution called hyena sequence intrusion detection (HSID) is proposed. This involves the creation of required nodes in the network, and the hyena function continually monitors node status. It effectively eliminates high-energy nodes, ensuring the sustainability of the routing process. The framework is implemented and rigorously tested in the Python platform, with a thorough evaluation of network efficiency parameters. In comparison, various metrics are considered, including energy consumption, throughput, packet drop, detection accuracy, and confidentiality rate. The results demonstrate higher performance satisfaction with the proposed model, emphasising its effectiveness in addressing the identified challenges and enhancing overall network security and efficiency.

Keywords: network efficiency; throughput; detection accuracy; confidentiality rate; network security.

DOI: 10.1504/IJCNDS.2026.154599

International Journal of Communication Networks and Distributed Systems, 2026 Vol.32 No.4, pp.398 - 419

Received: 06 Sep 2024
Accepted: 20 Mar 2025
Published online: 07 Jul 2026 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article

Title: Intelligent early intrusion prediction and route migration framework for secure data transmission

Keep up-to-date