Guan Yang¹, Shiyan Kang¹, Bo Chen^2,3, Yu Wang^4,*

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.084499 - 13 August 2026

Abstract Web honeypots serve as foundational technologies for active deception, attracting attackers and extracting actionable threat intelligence. To address the challenges associated with manual and labor-intensive frontend construction, this paper presents the HFG framework, a security-oriented frontend generation framework designed for the large-scale deployment of heterogeneous Web-service decoy nodes. HFG utilizes a vision-to-code architecture integrating a PVT-CoT visual encoder, multi-scale adaptive fusion, visual token compression, a visual prefix bridge, and a Qwen2-LoRA code decoder. The model is trained on WebSight-derived data and evaluated on both the WebSight-derived test set and the Design2Code benchmark. General reconstruction metrics,… More >

Xiaoyun Yuan^1,2,3,*, Zhengge Yi^1,2, Jingxi Zhang^1,2, Hairui Zhang³

CMC-Computers, Materials & Continua, Vol.88, No.3, 2026, DOI:10.32604/cmc.2026.072275 - 23 July 2026

Abstract Website Fingerprinting (WF) has emerged as a promising technique for identifying user access patterns to Hidden Services (HS). Despite growing interest in WF for HS, the absence of well-established foundations and systematic guidelines for feature selection undercuts the robustness of WF techniques in the face of concept drift. To address this gap, we present an empirical study focusing on feature resilience under concept drift in WF for HS. Specifically, we categorize features into network-specific and network-agnostic groups and quantify their information leakage potential via mutual information. We further assess each feature’s resilience to concept drift More >

Xingyun Hu^1,2, Siqi Lu^1,2,*, Liujia Cai^1,2, Ye Feng^1,2, Shuhao Gu^1,2, Tao Hu¹, Yongjuan Wang^1,2,*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.079484 - 08 May 2026

Abstract With the widespread adoption of web applications and cloud services, the OAuth 2.0-based OpenID Connect (OIDC) Single Sign-on (SSO) protocol has become the core of modern digital identity authentication. Although the OIDC protocol itself has strict security specifications, its implementation in real-world web frameworks can introduce critical vulnerabilities, particularly the improper omission of the state parameter, which leads to severe authentication forgery risks. Existing research often overlooks these implementation-level flaws, especially from a formal analysis perspective. This paper addresses this gap by formally analyzing the authentication forgery attack resulting from the missing state parameter. We construct… More >

Samer R. Sabbah¹, Mohammad Rasmi Al-Mousa¹, Ala’a Al-Shaikh², Ahmad Al Smadi^3,*, Suhaila Abuowaida⁴, Amina Salhi^5,*, Arij Alfaidi⁶

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.079241 - 08 May 2026

Abstract Web 4.0 platforms introduce intelligent, decentralized agents and real-time interactions that increase both utility and attack surface. This paper presents a comprehensive, reproducible AI blockchain hybrid designed to (1) detect SQL injection attacks at scale using a textual TFIDF + machine-learning pipeline, (2) incorporate reputation signals from a real-world Bitcoin OTC trust dataset to compute a TrustAlert Score (TAS) that prioritizes alerts and guides logging policy, and (3) record privacy-preserving audit digests on blockchain, optionally attested via a zero-knowledge proof (ZKP) pipeline. We evaluate the system on a 148 k SQL corpus and Soc-SignBitcoinOTC reputation More >

Liang Yin^1,*, Youjia Gao², Jie Ding¹, Sichao Su¹

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.4, 2026, DOI:10.32604/fdmp.2026.079847 - 07 May 2026

Abstract To address the thermal management challenges associated with localized high heat flux in electronic chips, this study proposes a bionic spider-web microchannel heat sink using deionized water as the coolant. Numerical simulations are conducted for two configurations, one with pinfins at the hotspot (Model A) and one without pinfins (Model B). The effects of Reynolds number and hotspot heat flux on flow distribution, pumping power, thermal resistance and temperature uniformity are systematically analyzed. Results show that the flow distribution varies significantly among channels, with higher flow rates near the inlet. Increasing the Reynolds number raises More >

Muhammad Waqar¹, Zeshan Aslam Khan^1,*, Arthur Chang^2,*, Zhishan Guo³, Chun-Liang Lai⁴, Chuan-Yu Chang⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.078892 - 27 April 2026

Abstract Lung cancer (LC) is among the dangerous cancers spreading progressively, and a timely LC diagnosis becomes a dire need of the time. Various imaging-based studies have been conducted for accurate LC examination through computed tomography (CT), X-ray, and histopathology. Worldwide, the proportion of LC-affected patients in hospitals is growing, thereby increasing imaging data for fast processing and early examination. To facilitate histopathological imaging-based automated and timely decision making for accurate LC prediction, a Context Aware Fusion Network (CAFNet) for holistic feature learning and spatially localized feature learning is proposed in this study for the efficient… More >

Daiki Nobayashi^1,*, Meiya Tanaka², Naoki Tanaka², Riku Nakamura², Kazuya Tsukamoto³, Takeshi Ikenaga¹, Shu Sekigawa⁴, Myung Lee⁵

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.077008 - 09 April 2026

Abstract To realize local production and consumption of Spatio-temporal data (STD), it is essential to address two key challenges: (1) maintaining data locality by retaining and distributing STD close to their generation area, and (2) enabling application execution on heterogeneous and resource-constrained devices through a lightweight and portable execution platform. To address these challenges, we developed a Floating Cyber-Physical System (F-CPS) that retains both STD and the functions required to process and use the STD within a specific area. In the F-CPS, the STD Retention System directly distributes STD from the generation location and maintains the… More >

Jaeho Hwang¹, Moohong Min^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.3, 2026, DOI:10.32604/cmes.2026.078940 - 30 March 2026

Abstract Illicit web ecosystems, encompassing phishing, illegal online gambling, scam platforms, and malicious advertising, have rapidly expanded in scale and complexity, creating severe social, financial, and cybersecurity risks. Traditional rule-based and blacklist-driven detection approaches struggle to cope with polymorphic, multilingual, and adversarially manipulated threats, resulting in increasing demand for Artificial Intelligence (AI)-based solutions. This review provides a comprehensive synthesis of research on AI-driven threat detection for illicit web environments. It surveys detection models across multiple modalities, including text-based analysis of Uniform Resource Locator (URL) and HyperText Markup Language (HTML), vision-based recognition of webpage layouts and logos,… More >

Goodness Adediran¹, Kenny Awuson-David², Yussuf Ahmed^1,*

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2026.077606 - 12 March 2026

Abstract Amazon Web Services (AWS) CloudTrail auditing service provides detailed records of operational and security events, enabling cloud administrators to monitor user activity and manage compliance. Although signature-based threat detection methods have been enhanced with machine learning and Large Language Models (LLMs), these approaches remain limited in addressing emerging threats. This study evaluates a two-step Retrieval Augmented Generation (RAG) approach using Gemini 2.5 Pro to enhance threat detection accuracy and contextual relevance. The RAG system integrates external cybersecurity knowledge sources including the MITRE ATT&CK framework, AWS Threat Technique Catalogue, and threat reports to overcome limitations of… More >

Randika K. Makumbura¹, Hasanthi Wijesundara², Hirushan Sajindra¹, Upaka Rathnayake^1,*, Vikram Kumar³, Dineshbabu Duraibabu¹, Sumit Sen³

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2026.075539 - 12 March 2026

Abstract Accurate streamflow prediction is essential for flood warning, reservoir operation, irrigation scheduling, hydropower planning, and sustainable water management, yet remains challenging due to the complexity of hydrological processes. Although data-driven models often outperform conventional physics-based hydrological modelling approaches, their real-world deployment is limited by cost, infrastructure demands, and the interdisciplinary expertise required. To bridge this gap, this study developed QPred, a regional, lightweight, cost-effective, web-delivered application for daily streamflow forecasting. The study executed an end-to-end workflow, from field data acquisition to accessible web-based deployment for on-demand forecasting. High-resolution rainfall data were recorded with tipping-bucket gauges… More >