cs papers | Gist.Science

A Design Science Approach to Zero Trust Cyber Risk Governance in Digital Government Platforms: Development and Evaluation of the CRGMM Framework

This paper presents the development and preliminary validation of the Cyber Risk Governance Maturity Model (CRGMM), a novel Design Science framework that integrates Zero Trust principles to assess and guide the cyber risk governance of multi-agency digital government platforms, as demonstrated through its application to Kuwait's Sahel system.

Abdullah F. Alenezi2026-07-10

💻 computer science

CEDF-CS: Class-Balanced Prototype Condensationfor Resource-Efficient and Leak-Free Intrusion Detection in Industrial IoT and Enterprise Networks

The paper introduces CEDF-CS, a leak-free, class-balanced prototype condensation framework that significantly compresses massive intrusion detection datasets while preserving minority attack structures, enabling resource-efficient models to achieve performance equal to or exceeding full-data training on industrial IoT and enterprise network benchmarks.

George Karraz, Anas Shahin2026-07-10

💻 computer science

Secure Data Sharing for Real Estate Valuation Using Blockchain Technology

This paper proposes the Valuation Data Ledger (VDL), a permissioned blockchain framework that integrates hybrid storage, access control, and token incentives to securely unify fragmented real estate valuation data, demonstrating through synthetic evaluation that it enhances automated valuation accuracy, enables effective fraud detection, and supports privacy-preserving collaborative learning.

Khaled Almi'ani, Nedal Ababneh, Tawfiq Alrawashdeh, Nur Siyam2026-07-10

💻 computer science

Mixed Neural Rendering: Interactive Mixed Reality Capture and Curation for Neural 3D Reconstruction

This paper introduces Mixed Neural Rendering (MiNeR), an interactive Mixed Reality pipeline using HoloLens 2 that integrates real-time capture, in-situ inspection, and promptable segmentation to overcome traditional acquisition limitations and enable robust, object-centric neural 3D reconstruction.

Alessio Paolucci, Lorenzo Stacchio, Emanuele Balloni, Pasquale Cascarano, Primo Zingaretti2026-07-10

💻 computer science

HashGuard-FL: Learnable Hash-Based GAN Discriminator with Post-Quantum Audit Trail for Federated Learning Integrity

HashGuard-FL is a novel federated learning framework that integrates a learnable hash-based GAN discriminator for fine-grained, multi-class attack detection with a post-quantum audit layer using SHAKE-256 and CRYSTALS-Dilithium signatures to ensure tamper-evident, quantum-resistant integrity across diverse benchmarks.

Nilima Dongre2026-07-09

💻 computer science

Beyond Aggregate Metrics Diagnosing the Long-Tailed Failure of Oracle Bone Character Detection and Recognition

This paper diagnoses the severe performance gap in Oracle bone character detection caused by extreme long-tailed class distribution and proposes FAR-YOLO, a decoupled baseline that significantly improves few-shot recognition accuracy through frequency-aware sampling and morphology-preserving augmentation without compromising overall localization performance.

Dan Sui, Yuhang Xing, Penglan Liu, Bang Li2026-07-09

💻 computer science

DP-DCGAN: Differential Privacy-Deep Convolutional Generative Adversarial Networks with Adaptive Gradient Perturbation

This paper proposes DP-DCGAN, a differential privacy-enhanced Deep Convolutional Generative Adversarial Network that employs adaptive gradient clipping and noise injection to achieve a superior balance between privacy protection and high-quality image synthesis on standard datasets.

Libo Zhu, Xiang Chen2026-07-09

💻 computer science

Introducing a Novel Feature in CloudSimPlus: Enhancing Load Balancer Efficiency based on AI

This paper introduces an AI-driven adaptive load balancing feature for CloudSimPlus that utilizes a pre-trained Decision Tree model to dynamically select the most suitable strategy from a unified framework of policies based on real-time metrics and user-defined objectives, thereby enhancing efficiency and decision-making in dynamic cloud environments.

Anouar Ben Halima, Hafssa Benaboud2026-07-09

💻 computer science

Privacy-Preserving Intrusion Detection in SDN-IoT Networks: Machine Learning, Deep Learning, Differential Privacy, and Inference Attacks

This paper argues that prioritizing strong model generalization to prevent overfitting is a more effective strategy for mitigating membership and attribute inference attacks in SDN-IoT intrusion detection systems than relying solely on differential privacy, proposing a hybrid AOPRF-XGBoost cascade model to achieve high detection accuracy while preserving privacy.

Zerguine Younes, Noureddine Haithem, Gherbi Chirihane2026-07-09

💻 computer science

Multi-objective Cluster Head Selection in Underwater Wireless Sensor Networks: An Influence Maximization Perspective with Adaptive Evolutionary Optimization

This paper proposes LA-MOCHS, a lifetime-aware evolutionary framework that addresses multi-objective cluster-head selection in underwater wireless sensor networks by modeling service capability as a submodular influence maximization problem, thereby achieving superior long-term network sustainability through burden-aware deployment strategies rather than single-round optimality.

Pham Cong Hoang, Ho Viet Duc Luong, Nguyen Minh Quan2026-07-09

← Previous Next →