Ayaz Hussain¹, Asad Hayat², Muhammad Hasnain^1,*

Journal on Artificial Intelligence, Vol.7, pp. 485-498, 2025, DOI:10.32604/jai.2025.071933 - 17 November 2025

Abstract Violent hate speech and scapegoating people against one another have emerged as a rising worldwide issue. But identifying and combating such content is crucial to create safer and more inclusive societies. The current study conducted research using Machine Learning models to classify hate speech and overcome the limitations posed in the existing detection techniques. Logistic Regression (LR), Random Forest (RF), K-Nearest Neighbour (KNN) and Decision Tree were used on top of a publicly available hate speech dataset. The data was preprocessed by cleaning the text and tokenization and using normalization techniques to efficiently train the… More >

Hafiz Muhammad Waqas¹, Tahir Mahmood^1,2, Walid Emam³, Ubaid ur Rehman⁴, Dragan Pamucar^5,*

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 4699-4727, 2025, DOI:10.32604/cmc.2025.065011 - 30 July 2025

Abstract Cyber threat detection is a crucial aspect of contemporary cybersecurity due to the depth and complexity of cyberattacks. It is the identification of malicious activity, unauthorized access, and possible intrusions in networks and systems. Modern detection methods employ artificial intelligence and machine learning to study vast amounts of data, learn patterns, and anticipate potential threats. Real-time monitoring and anomaly detection improve the capacity to react to changing threats more rapidly. Cyber threat detection systems aim to reduce false positives and provide complete coverage against the broadest possible attacks. This research advocates for proactive measures and… More >

Thaer Thaher^1,*, Majdi Mafarja², Muhammed Saffarini³, Abdul Hakim H. M. Mohamed⁴, Ayman A. El-Saleh⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 2615-2673, 2025, DOI:10.32604/cmes.2025.064857 - 30 June 2025

Abstract Detecting faces under occlusion remains a significant challenge in computer vision due to variations caused by masks, sunglasses, and other obstructions. Addressing this issue is crucial for applications such as surveillance, biometric authentication, and human-computer interaction. This paper provides a comprehensive review of face detection techniques developed to handle occluded faces. Studies are categorized into four main approaches: feature-based, machine learning-based, deep learning-based, and hybrid methods. We analyzed state-of-the-art studies within each category, examining their methodologies, strengths, and limitations based on widely used benchmark datasets, highlighting their adaptability to partial and severe occlusions. The review… More >

Jiaqi Wang, Jian Su^*

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 125-152, 2025, DOI:10.32604/cmc.2025.064309 - 09 June 2025

Abstract The Intelligent Transportation System (ITS), as a vital means to alleviate traffic congestion and reduce traffic accidents, demonstrates immense potential in improving traffic safety and efficiency through the integration of Internet of Things (IoT) technologies. The enhancement of its performance largely depends on breakthrough advancements in object detection technology. However, current object detection technology still faces numerous challenges, such as accuracy, robustness, and data privacy issues. These challenges are particularly critical in the application of ITS and require in-depth analysis and exploration of future improvement directions. This study provides a comprehensive review of the development… More >

Mahmood Ul Haq¹, Muhammad Athar Javed Sethi¹, Sadique Ahmad², Naveed Ahmad³, Muhammad Shahid Anwar^4,*, Alpamis Kutlimuratov⁵

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1-24, 2025, DOI:10.32604/cmc.2025.063341 - 09 June 2025

Abstract Face recognition has emerged as one of the most prominent applications of image analysis and understanding, gaining considerable attention in recent years. This growing interest is driven by two key factors: its extensive applications in law enforcement and the commercial domain, and the rapid advancement of practical technologies. Despite the significant advancements, modern recognition algorithms still struggle in real-world conditions such as varying lighting conditions, occlusion, and diverse facial postures. In such scenarios, human perception is still well above the capabilities of present technology. Using the systematic mapping study, this paper presents an in-depth review More >

Zhimao Lai^1,2, Saad Arif³, Cong Feng⁴, Guangjun Liao⁵, Chuntao Wang^6,*

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 73-102, 2025, DOI:10.32604/cmc.2024.059370 - 03 January 2025

Abstract With the rapid advancement of visual generative models such as Generative Adversarial Networks (GANs) and stable Diffusion, the creation of highly realistic Deepfake through automated forgery has significantly progressed. This paper examines the advancements in Deepfake detection and defense technologies, emphasizing the shift from passive detection methods to proactive digital watermarking techniques. Passive detection methods, which involve extracting features from images or videos to identify forgeries, encounter challenges such as poor performance against unknown manipulation techniques and susceptibility to counter-forensic tactics. In contrast, proactive digital watermarking techniques embed specific markers into images or videos, facilitating More >

Muhammad Dawood¹, Shanshan Tu¹, Chuangbai Xiao¹, Muhammad Haris², Hisham Alasmary³, Muhammad Waqas^4,5,*, Sadaqat Ur Rehman⁶

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4513-4542, 2024, DOI:10.32604/cmc.2024.050049 - 12 September 2024

Abstract The DNS over HTTPS (Hypertext Transfer Protocol Secure) (DoH) is a new technology that encrypts DNS traffic, enhancing the privacy and security of end-users. However, the adoption of DoH is still facing several research challenges, such as ensuring security, compatibility, standardization, performance, privacy, and increasing user awareness. DoH significantly impacts network security, including better end-user privacy and security, challenges for network security professionals, increasing usage of encrypted malware communication, and difficulty adapting DNS-based security measures. Therefore, it is important to understand the impact of DoH on network security and develop new privacy-preserving techniques to allow More >

Singamaneni Krishnapriya^*, Sukhvinder Singh

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2675-2719, 2024, DOI:10.32604/cmc.2024.052447 - 15 August 2024

Abstract The increase in number of people using the Internet leads to increased cyberattack opportunities. Advanced Persistent Threats, or APTs, are among the most dangerous targeted cyberattacks. APT attacks utilize various advanced tools and techniques for attacking targets with specific goals. Even countries with advanced technologies, like the US, Russia, the UK, and India, are susceptible to this targeted attack. APT is a sophisticated attack that involves multiple stages and specific strategies. Besides, TTP (Tools, Techniques, and Procedures) involved in the APT attack are commonly new and developed by an attacker to evade the security system.… More >

Sheetal Sharma^1,2, Kamali Gupta¹, Deepali Gupta¹, Shalli Rani^1,*, Gaurav Dhiman^3,4,5,6,7,*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2029-2059, 2024, DOI:10.32604/cmes.2023.029997 - 15 December 2023

Abstract The widespread adoption of the Internet of Things (IoT) has transformed various sectors globally, making them more intelligent and connected. However, this advancement comes with challenges related to the effectiveness of IoT devices. These devices, present in offices, homes, industries, and more, need constant monitoring to ensure their proper functionality. The success of smart systems relies on their seamless operation and ability to handle faults. Sensors, crucial components of these systems, gather data and contribute to their functionality. Therefore, sensor faults can compromise the system’s reliability and undermine the trustworthiness of smart environments. To address… More > Graphic Abstract

Shayla Islam¹, Anil Kumar Budati^1,*, Mohammad Kamrul Hasan², Saoucene Mahfoudh³, Syed Bilal Hussian Shah³

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 813-825, 2023, DOI:10.32604/cmes.2023.027595 - 23 April 2023

Abstract In wireless communications, the Ambient Backscatter Communication (AmBC) technique is a promising approach, detecting user presence accurately at low power levels. At low power or a low Signal-to-Noise Ratio (SNR), there is no dedicated power for the users. Instead, they can transmit information by reflecting the ambient Radio Frequency (RF) signals in the spectrum. Therefore, it is essential to detect user presence in the spectrum for the transmission of data without loss or without collision at a specific time. In this paper, the authors proposed a novel Spectrum Sensing (SS) detection technique in the Cognitive… More >