{"ID":2844883,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.05133","arxiv_id":"2511.05133","title":"A Secured Intent-Based Networking (sIBN) with Data-Driven Time-Aware Intrusion Detection","abstract":"While Intent-Based Networking (IBN) promises operational efficiency through autonomous and abstraction-driven network management, a critical unaddressed issue lies in IBN's implicit trust in the integrity of intent ingested by the network. This inherent assumption of data reliability creates a blind spot exploitable by Man-in-the-Middle (MitM) attacks, where an adversary intercepts and alters intent before it is enacted, compelling the network to orchestrate malicious configurations. This study proposes a secured IBN (sIBN) system with data driven intrusion detection method designed to secure legitimate user intent from adversarial tampering. The proposed intent intrusion detection system uses a ML model applied for network behavioral anomaly detection to reveal temporal patterns of intent tampering. This is achieved by leveraging a set of original behavioral metrics and newly engineered time-aware features, with the model's hyperparameters fine-tuned through the randomized search cross-validation (RSCV) technique. Numerical results based on real-world data sets, show the effectiveness of sIBN, achieving the best performance across standard evaluation metrics, in both binary and multi classification tasks, while maintaining low error rates.","short_abstract":"While Intent-Based Networking (IBN) promises operational efficiency through autonomous and abstraction-driven network management, a critical unaddressed issue lies in IBN's implicit trust in the integrity of intent ingested by the network. This inherent assumption of data reliability creates a blind spot exploitable by...","url_abs":"https://arxiv.org/abs/2511.05133","url_pdf":"https://arxiv.org/pdf/2511.05133v1","authors":"[\"Urslla Uchechi Izuazu\",\"Mounir Bensalem\",\"Admela Jukan\"]","published":"2025-11-07T10:28:01Z","proceeding":"cs.CR","tasks":"[\"cs.CR\",\"cs.NI\"]","methods":"[]","has_code":false}