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31 results for “generative model”
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Review ArticleOpen accessIn the abstractDeepfake Technology: A Comprehensive Review of Trends, Applications, Ethical Concerns, and ChallengesBattula Thirumaleshwari Devi, Rajkumar RajasekaranThe digital age has fundamentally transformed how information is created and disseminated, raising critical concerns about the authenticity and trustworthiness of online content. Recent advances in Artificial Intelligence (AI), particularly deep learning, have given rise to deepfakes: highly realistic synthetic media generated by manipulating or replacing faces, voices, and actions in videos. While deepfake technology offers innovative applications across various … …Journal of Computer Science, Vol. 22, Issue 1 · 17 Feb 2026 · 4,861 accessesView PDFCite
Research ArticleOpen accessIn the abstractRobust Adversarial Attack Detection via Generative Adversarial Network With Residual Multi-Layer Aggregation Based Contrastive Loss FunctionAmudha Gopalakrishnan, Nalini JosephAdversarial attacks in medical imaging refer to subtle modifications to images that mislead diagnostic systems, resulting in inaccurate diagnoses and assessments. These attacks exploit vulnerabilities in image processing, leading to misclassification or altered visual features that often go unnoticed. This raises serious concerns about the security and reliability of medical diagnosis, directly impacting clinical decision-making and patient safety. This research … …Journal of Computer Science, Vol. 22, Issue 1 · 10 Feb 2026 · 1,742 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimized Fractal Fusion Driven Deep Neural Network: An Efficient Hybrid Methodology for Disease Detection and Classification in Plant LeavesDeepkiran Munjal, Mrinal Pandey, Laxman SinghPlant diseases and pest attacks are among the major issues in agriculture, which have a great impact on crop growth and yield. Early and correct detection of these diseases is vital for effective management and keeping plant health at the desired level. This research proposes a new method for detection and classification of plant diseases, the Optimized Fractional Fusion Deep … …Journal of Computer Science, Vol. 21, Issue 12 · 8 Jan 2026 · 2,223 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Sense: Deep Learning for Early Staging the Onset of Diabetes Emanating Recognition of Activity PatternsMohammed Shamsul Alam, Erfanul Hoque Bahadur, Md Fokrul Islam Khan et al.This study presents a comprehensive framework for Human Activity Recognition (HAR) using smartphone sensor data, with a specific focus on identifying activities associated with diabetic risk factors. We investigate the efficacy of two deep learning architectures (Long Short-Term Memory (LSTM) networks and Graph Convolutional Networks (GCNs)) for activity recognition under conditions of limited training data. To address data scarcity, we … …Journal of Computer Science, Vol. 21, Issue 10 · 15 Dec 2025 · 2,268 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing the CIC IoT Dataset 2023 for Improved Attack Detection through GANs Augmentation and Federated LearningShahad Alahmari, Noura AleisaThe escalating frequency and sophistication of cyber-attacks on Internet of Things (IoT) devices present a pressing challenge to cybersecurity. With IoT device connections projected to exceed 42 billion by 2025, the vulnerability of these devices to cyber-attacks has never been more evident. This paper investigates the integration of Machine Learning (ML) and data augmentation, specifically Generative Adversarial Networks (GAN) and … …Journal of Computer Science, Vol. 21, Issue 7 · 18 Jul 2025 · 9,111 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Succinct Review on Identification of Network Anomalies and Protection in Cyber-Physical SystemsShalini Kumari, Chander Prabha, Prakash Srivastava et al.Advanced cyberattacks outperform traditional threat detection methods in the rapidly expanding cybersecurity field. Advanced Machine Learning (ML) algorithms can detect network traffic and system problems using AI-based Anomaly Detection (AD) for cybersecurity in real-time. Signature-based systems may overlook new and subtle threats. This paper examines Artificial Intelligence (AI) driven AD systems' design, methodology, and efficacy. The process includes data preprocessing … …Journal of Computer Science, Vol. 21, Issue 6 · 29 May 2025 · 5,234 accessesView PDFCite
Review ArticleOpen accessIn the abstractCybercrime in the AI Era: Definitions, Classification, Severity Assessment and the Role of AI in Combating ThreatsNorah Sultan Alshahrani, Fahd Saleh Alotaibi, Khaled Hamed Alyoubi, Muhammad Sher RamzanThe growing prevalence, complexity and financial impact of cybercrimes pose significant challenges for law enforcement agencies worldwide. Many organizations are utilizing different technologies such as cloud technology to improve speed, accuracy, and reliability. However, without proper security measures, the risk is still vital against cyberattacks. Cybercrime can lead to various negative outcomes, including theft, fraud, financial losses, a decline in … …Journal of Computer Science, Vol. 21, Issue 3 · 12 Feb 2025 · 7,155 accessesView PDFCite
Research ArticleOpen accessIn the abstractScalable and Advanced Framework for Hate Speech Detection on Social Media Using BERT and GPT-2 through Encoder and Decoder ArchitecturesUsman, Nabeela Hasan, Syed Mohammad Khurshid QuadriHate speech is a major problem on social media platforms. Every day, numerous instances of hateful behavior based on race, ethnicity, religion, or gender are witnessed on social media. Most of the leading social media platforms like Instagram, Facebook, Twitter Reddit, etc., have strong community guidelines that condemn and restrict the exchange of hateful language/content in any form. Despite the … …Journal of Computer Science, Vol. 21, Issue 3 · 7 Feb 2025 · 7,325 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimizing Mobile Edge Computing Efficiency through Multidimensional Generative Adversarial NetworkAnitha Premkumar, Sowmya Vemagal Lakshminarayana, Shankar Rajagopal et al.Big data Processing and the IoT have recently gained popularity as study topics in MEC and thorough research is sought for well-informed decisions. Mobile edge equipment, such as base stations, routers, and edge servers, usually have limited processing capabilities compared to traditional data centers. According to this perspective, this research constructs MEC using Intelligent Outlier Detection with a Multidimensional Generative … …Journal of Computer Science, Vol. 21, Issue 2 · 18 Jan 2025 · 4,686 accessesView PDFCite