cs papers | Gist.Science

Sequence-, Epoch-, and Integrity-Aware Detection of Replay and Peer-Spoofing Attacks in Decentralized UAV Mesh Networks: A Software-Validated Security Framework

This paper presents and validates a software-implemented security framework for decentralized UAV swarms that prevents replay and peer-spoofing attacks through a strict packet-admission chain combining HMAC-SHA256 authentication, epoch validation, and monotonic sequence checking, while quantifying its performance overhead and identifying shared-secret compromise as the primary residual risk.

Md Shahanur Islam Shagor2026-08-26

💻 computer science

OmniGuard V2X: A Hybrid-Security Prototype Framework with Assumption-Aware Validation for Smart Vehicle Systems

This paper introduces OmniGuard V2X, a six-layer hybrid-security prototype framework for smart vehicle systems that prioritizes assumption-aware validation and machine-readable security boundaries to enhance the reproducibility and interpretability of complex, multi-mechanism V2X security evaluations using post-quantum cryptography.

Md Shahanur Islam Shagor2026-08-26

💻 computer science

Architectural Framework for ERP-WMS Integration: Mitigating Data Latency and Transactional Asymmetry in Integrated Logistics Systems

This paper introduces the SAIL framework, a novel stateful orchestration architecture that mitigates data latency and transactional asymmetry in integrated ERP-WMS logistics systems by replacing stateless middleware with active, state-retaining layers featuring heuristic validation and dual-handshake protocols, ultimately reducing manual inventory remediation by up to 90% while ensuring ledger integrity.

Arijit Das2026-08-26

💻 computer science

Genetic Fragmentation Gradient Descent: Failure-Constrained Scheduling for GPU-Sharing Clusters

This paper proposes Genetic Fragmentation Gradient Descent (GFGD), an efficient offline-online scheduler that uses a genetic algorithm to evolve lightweight, failure-constrained policies for GPU-sharing clusters, significantly reducing scheduling latency while improving job completion rates and resource utilization compared to prior simulation-heavy approaches.

Soeun Choi, Jaehyeong Sim2026-08-26✓ Author reviewed ⓘ

💻 computer science

A Lightweight Time--Frequency Fusion Network for Accurate Wastewater Quality Forecasting

This paper introduces TSF-Resonator, a lightweight time-frequency fusion network that achieves accurate and efficient wastewater quality forecasting by combining adaptive multi-scale temporal encoding with low-rank spectral analysis to overcome the computational and modeling limitations of existing Transformer-based approaches.

Jiahao Fu, Jianjun Sun, Gaunlin Li2026-08-26✓ Author reviewed ⓘ

💻 computer science

Agentic AI System for Hospital Management

This paper proposes and evaluates a cooperative Multi-Agent Reinforcement Learning framework for hospital administration, demonstrating that its four specialized agents significantly outperform traditional systems by optimizing resource allocation, reducing patient waiting times, and achieving high operational efficiency with minimal conflict.

Ashis Kumar Pati, Kaibalya Mohapatra, Mukesh Kumar Padhi, Shreya Tripathy2026-08-26

💻 computer science

Trustworthy Few-Shot Transfer Learning withExplainable AI for PCOS Ultrasound Classification

This paper proposes a trustworthy few-shot transfer learning framework using ResNet50 and Grad-CAM that effectively classifies PCOS from ultrasound images with high accuracy and reliable explanations, even under severe data scarcity.

S. M. Nihal Ahmed, Afrim Hossen Khan, Sabikun Nahar Sinthia2026-08-26

💻 computer science

TrustFedKG-Health: Explainability-Aware Personalized Federated Knowledge Graph Neural Network with Uncertainty-Guided Clinical Reasoning

TrustFedKG-Health is an explainability-aware, personalized federated learning framework that integrates a medical knowledge graph, uncertainty-guided reasoning, and quality-weighted aggregation to achieve superior disease risk prediction and generate clinically grounded narratives while addressing data heterogeneity and quality issues across hospitals.

ARITRIK GHOSH2026-08-26

💻 computer science

Network Dominance and the MITM Exception: A Modality-Aware Analysis of IIoT Intrusion Detection on the DataSense Benchmark

This paper demonstrates that on the DataSense IIoT benchmark, network traffic features alone are nearly sufficient for high-accuracy intrusion detection across most attack categories, with device telemetry adding minimal value except for distinguishing man-in-the-middle (MITM) attacks.

Okoi Michael Obeten, Omowumi Hafsat Aliu2026-08-26

💻 computer science

Cross-Group Aligned Problem Difficulty Clustering Using Attention-Weighted Feature Learning

This paper proposes a proficiency-group-aware framework that combines feature-attention-guided K-means clustering with a global alignment step to effectively categorize programming problem difficulties on Online Judge platforms, significantly improving clustering quality and cross-group consistency compared to standard baselines.

Md. Shahajada Mia, Yutaka Watanobe, Md. Mostafizer Rahman, Md Faizul Ibne Amin, Daniel M. Muepu, Fang Liu2026-08-26

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