Institution profile

CMR University

Academic institutionasia · in
Official website
Research library1linked papers
Opportunities0open roles
Selected work

Representative Papers

SmartSecChain-SDN: A Blockchain-Integrated Intelligent Framework for Secure and Efficient Software-Defined Networks

Oct 31, 2025International Journal of Electronics and Communication Engineering

SDN networks suffer from weak security guarantees and coarse-grained traffic control. To address these challenges, this paper proposes an intelligent security framework integrating machine learning–based intrusion detection, blockchain-enabled immutable logging, and application-aware traffic regulation. Methodologically, it synergistically combines Hyperledger Fabric—a permissioned blockchain—with multiple IDS models (Random Forest, XGBoost, CatBoost, and CNN-BiLSTM) to achieve high-accuracy attack detection with low false positives, while ensuring tamper-proof, auditable, and traceable log provenance. Furthermore, the framework dynamically optimizes QoS provisioning and bandwidth allocation based on application-layer features. A prototype system is implemented atop Mininet with OpenDaylight/Ryu controllers and evaluated on the InSDN dataset. Results demonstrate real-time detection of diverse attacks—including DDoS and port scanning—and sustained QoS assurance for critical services under resource-constrained conditions.

0 citationsRead paper
Recent publications

Latest Papers

SmartSecChain-SDN: A Blockchain-Integrated Intelligent Framework for Secure and Efficient Software-Defined Networks

Oct 31, 2025International Journal of Electronics and Communication Engineering

SDN networks suffer from weak security guarantees and coarse-grained traffic control. To address these challenges, this paper proposes an intelligent security framework integrating machine learning–based intrusion detection, blockchain-enabled immutable logging, and application-aware traffic regulation. Methodologically, it synergistically combines Hyperledger Fabric—a permissioned blockchain—with multiple IDS models (Random Forest, XGBoost, CatBoost, and CNN-BiLSTM) to achieve high-accuracy attack detection with low false positives, while ensuring tamper-proof, auditable, and traceable log provenance. Furthermore, the framework dynamically optimizes QoS provisioning and bandwidth allocation based on application-layer features. A prototype system is implemented atop Mininet with OpenDaylight/Ryu controllers and evaluated on the InSDN dataset. Results demonstrate real-time detection of diverse attacks—including DDoS and port scanning—and sustained QoS assurance for critical services under resource-constrained conditions.

0 citationsRead paper