Zhaoxin Zhang

SABH-FL: a secure attribute-based hierarchical federated learning

Ping Yu, Aojie Yang, Zhaoxin Zhang, Wenmin Li

cn (code pays fourni par la source)

HMCGeo: IP Region Prediction Based on Hierarchical Multi-Label Classification

Tianzi Zhao, Xinran Liu, Zhaoxin Zhang, Dong Zhao et autres

Fine-grained IP geolocation plays a critical role in applications such as location-based services and cybersecurity. Most existing fine-grained IP geolocation methods treat the task as a coordinate regression problem. However, due to inherent noise in the IP features, they frequently produce kilometer-scale …

cn (code pays fourni par la source)

MG-HGNN: A Heterogeneous GNN Framework for Indoor Wi-Fi Fingerprint-Based Localization

Zhaoxin Zhang, Ning Li, Xinlong Zhao, Dong Zhao et autres

Received signal strength indicator (RSSI) is the primary representation of Wi-Fi fingerprints and serves as a crucial tool for indoor localization. However, existing RSSI-based positioning methods often suffer from reduced accuracy due to environmental complexity and challenges in processing multi-source information. To …

Training‐free few‐shot construction tool and material detection using pre‐trained vision‐language model

Zhaoxin Zhang, Yantao Yu, Zaolin Pan, Maxwell Fordjour Antwi‐Afari

Direct visual understanding of construction entities, such as tools and materials (T&M), underpin construction management and resource scheduling. Traditional supervised learning methods suffer from high annotation cost, severe computational demands, and limited datasets. In contrast, training-free approaches offer an effective alternative well-suited …

hk, cn, gb (code pays fourni par la source)

Machine Learning-Based Detection of Gambling-Like Mobile Applications and Their Resource Coordination

Hanjing Su, ZhengYao Ning, Zhaoxin Zhang, ZuoLi Xi et autres

Mobile gambling applications constitute a significant component of the online black and grey industries. They lure users into illegal activities through covert distribution channels, causing substantial financial losses and social harm. To evade detection, these applications often employ techniques like code obfuscation, …

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Knowledge-enhanced Vision-Language Models for Few-Shot Object Detection in Construction Site

Zhaoxin Zhang, Yantao Yu

Visual understanding of complex construction site objects is critical for project safety management and worker-robot collaboration within the construction domain. However, deploying deep learning algorithms on construction sites presents significant challenges due to high data annotation costs, substantial computational requirements, and the …

hk, cn (code pays fourni par la source)

Botnet Traffic Detection via Deep Neural Networks with Multi-Category Feature Fusion and Multi-Head Self-Attention Mechanism

Dongwei Fu, Hao Chen, Qiang He, Zhaoxin Zhang et autres

With the continuous evolution of botnet attack techniques, traditional detection methods based on signature matching and single-feature analysis are increasingly inadequate in handling complex and dynamic network threats, resulting in limited accuracy and robustness. Effectively integrating heterogeneous features from multiple sources to …

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Cross-Layer Data Transmission Enhancement Techniques for Secure Communication

Mu Qin, Hao Chen, Zhaoxin Zhang, Yanan Cheng et autres

As the demand for secure data communication in cyberspace continues to grow, the concealment of the communication origin has become a critical indicator. Existing communication systems face issues such as static path structures and fixed communication exits, which pose risks of being …

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Transformer-Based Detection of DGA Domains Enhanced by Semantic and Structural Branches

Tenglong Lu, Qiang He, Hao Chen, Zhaoxin Zhang et autres

Domain Generation Algorithms (DGAs) pose a persistent challenge in detecting botnet communications, particularly as certain families generate domain names that closely resemble natural language. To address this issue, this paper presents a Transformer-based detection architecture enhanced with semantic and structural auxiliary branches. …

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6Hound: An Efficient IPv6 DNS Resolver Discovery Model Based on Reinforcement Learning

Zhichao Zhang, Yanan Cheng, Zhaoxin Zhang, Xin-Ran Liu

DNS resolvers are an important measurement targets in the IPv4/IPv6 Internet for cybersecurity and network management. However, due to the vast address space of IPv6, it is infeasible to discover IPv6 DNS resolvers using brute-force Internet-wide scanning as in IPv4. To address …

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METC: A Hybrid Deep Learning Framework for Cross-Network Encrypted DNS over HTTPS Traffic Detection and Tunnel Identification

Ming Zuo, Changyong Guo, Haiyan Xu, Zhaoxin Zhang et autres

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Identifying and analysis the core structure of the internet

Yuancheng Xie, Zhaoxin Zhang, Haoyang Gao, Ning Li et autres

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