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A Deployment-Oriented Framework for Explainable AI-Assisted eBPF/XDP Mitigation at the IoT Edge

arXiv Security Archived Jun 10, 2026 ✓ Full text saved

arXiv:2606.10508v1 Announce Type: new Abstract: Internet of Things (IoT) deployments combine heterogeneous, resource-constrained devices with weak security configurations, exposed services, limited logging, patching constraints, and long lifecycles. Signature- and threshold-based controls remain useful baselines, but they are insufficient as standalone mechanisms in dynamic IoT networks. Likewise, offline artificial intelligence (AI) benchmark performance alone does not establish operational dep

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    Computer Science > Cryptography and Security [Submitted on 9 Jun 2026] A Deployment-Oriented Framework for Explainable AI-Assisted eBPF/XDP Mitigation at the IoT Edge Abdurrahman Tolay Internet of Things (IoT) deployments combine heterogeneous, resource-constrained devices with weak security configurations, exposed services, limited logging, patching constraints, and long lifecycles. Signature- and threshold-based controls remain useful baselines, but they are insufficient as standalone mechanisms in dynamic IoT networks. Likewise, offline artificial intelligence (AI) benchmark performance alone does not establish operational deployability. This article presents a conceptual framework and research agenda for a Linux-based IoT edge gateway that combines resource-aware flow-level AI-assisted risk scoring, event-level explainability, and bounded mitigation through eBPF/XDP. The controller applies reversible, time-limited actions subject to critical-device safeguards, updates packet-level enforcement state, and records structured logs. The architecture separates complex reasoning and policy control in user space from concise packet-handling decisions in the kernel. It also defines a future hardware-aware evaluation pathway covering detection quality, resource cost, response timing, rollback behaviour, and legitimate-traffic preservation. The paper does not report new experimental meas Comments: 59 pages, 2 figures, 12 tables. Conceptual framework and research agenda for explainable AI-assisted eBPF/XDP mitigation at the IoT edge Subjects: Cryptography and Security (cs.CR); Networking and Internet Architecture (cs.NI) Cite as: arXiv:2606.10508 [cs.CR]   (or arXiv:2606.10508v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2606.10508 Focus to learn more Submission history From: Abdurrahman Tolay [view email] [v1] Tue, 9 Jun 2026 07:36:16 UTC (1,031 KB) Access Paper: view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-06 Change to browse by: cs cs.NI References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
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    arXiv Security
    Category
    ◬ AI & Machine Learning
    Published
    Jun 10, 2026
    Archived
    Jun 10, 2026
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