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.

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…

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…

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…

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…

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 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…

This paper demonstrates the integration of the quantum-resistant FALCON digital signature scheme into an MQTT-based IoT network using Raspberry Pi 5s to secure communications against future quantum at…

This paper demonstrates that the Euston secure inference framework, which uses SVD-based matrix transmission to save bandwidth, leaks private input data by exploiting subspace leakage of random masks.

The paper introduces CCLab, an adversarial testing framework, to systematically evaluate the robustness of both learning-based and traditional congestion controllers, finding that learning-based contr…

This paper analyzes RPKI specifications, demonstrating that vague or conflicting requirements in dozens of RFCs cause systemic vulnerabilities in real-world implementations, leading to 61 undocumented…

This study analyzed I2P's routing topology and found no significant evidence that peer selection is influenced by geographic location, suggesting highly random global mixing.

Pepper is a novel, high-bandwidth anonymous broadcast protocol that achieves cryptographic sender anonymity and significantly improves messaging throughput compared to existing state-of-the-art system…

The paper identifies and demonstrates the existence of a covert sublayer, called the Exclusive Network, within the I2P anonymous network, which allows nodes to host services without being discoverable…

The paper proposes a cross-layer behavioral fingerprinting framework that fuses physical and network data to detect comprehensive attacks in dense LEO satellite constellations, achieving high detectio…