Networking

The paper proposes a two-timescale governance framework using a multi-agent LLM to safely update and guide RL agents for SDN-IoT defense, significantly improving performance and stability under advers…

TIP introduces a decentralized, declarative protocol that enables flexible IoT interoperability by resolving abstract intents and performing on-the-fly, sandboxed schema adaptation across heterogeneou…

MeshGuard is a framework that extends MUD-based network access control to complex, large-scale Thread IoT networks by adapting the MLE protocol and using SDN for scalable policy enforcement.

This paper compares Google's BBR-v3 Congestion Control Algorithm to eight others over SpaceX's Starlink network, demonstrating its fairness and throughput maximization in high-latency, variable satell…

The paper proposes MLDAS, a framework that dynamically selects the optimal Machine Learning algorithm for Intrusion Detection Systems within Software-Defined Networking to enhance adaptive network sec…

This paper introduces an attribution-driven analysis of encoder-based Large Language Models (LLMs) for network intrusion detection, demonstrating that the models make decisions based on meaningful tra…

The paper proposes SDNGuardStack, an explainable ensemble learning framework that achieves high-accuracy intrusion detection (99.98%) in Software-Defined Networks using the InSDN dataset.

The paper proposes a novel Retrieval-Augmented Generation (RAG) framework utilizing Large Language Models (LLMs) for real-time, intelligent detection and mitigation of evasive Carpet-Bombing DDoS atta…

OrbitBFT introduces a novel two-stage hierarchical BFT consensus protocol that enables scalable and robust Byzantine Fault-Tolerant coordination for large-scale Low Earth Orbit satellite constellation…

This paper presents TRUAV, a distributed multi-agent reinforcement learning framework for joint UAV trajectory planning and routing enhancement in UAV-aided VANETs, eliminating the need for global sta…

The paper proposes and evaluates efficient, quantum-safe variants of the Internet Key Exchange (IKE) protocol tailored for the unique resource constraints and latency challenges of satellite communica…

The paper proposes a novel identity-based public key management framework, IPK-pq, utilizing NIST ML-DSA and random matrix theory to enhance the scalability and efficiency of Public Key Infrastructure…

This paper presents AlphaRoute, a multi-objective adaptive search framework for VLSI global routing using Large Language Models as semantic policy optimizers.

This paper proposes a two-stage machine learning system that accurately detects I2P traffic and subsequently classifies it as data exfiltration or legitimate activity, achieving high accuracy in both…

ShieldShare is a novel, non-root Android application that enables secure, VPN-backed hotspot sharing with accurate per-user traffic accounting, addressing limitations in current mobile VPN implementat…

This paper presents CoEvoP&R, a framework that uses a large language model to automatically evolve analytical placement objectives, reducing post-route routed wirelength, congestion, and improving tim…

This paper introduces Virtual Time-Sensitive Networking (V-TSN), a software-defined overlay for gPTP-based synchronization and TSN traffic shaping over general-purpose networks without specialized har…

This paper proposes CAPS, a scheduling layer for data centers that separates rate computation and packet scheduling, reducing queue occupancy by up to 10x without throughput loss.

This paper introduces Predictive Exposure and Cryptographic Readiness (PECR), a method for prioritizing vulnerabilities in software-defined wide-area networking based on nine normalized factors, and e…

This paper proposes a lightweight architectural enhancement for FPGA designs to improve data movement between block RAMs and digital signal processing units for deep learning workloads, incurring negl…