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61 results for “security features”
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Research ArticleOpen accessIn the abstractOptimized Feature Reduction Techniques for Enhanced Network Threat Detection in Wireless Sensor NetworksBikash Kalita, Satyajit SarmahThe security of Wireless Sensor Networks (WSNs) is currently seriously threatened by numerous threats. Consequently, a number of applications are offered to regulate data and information sharing along with the related security features that need to be maintained throughout data transfer. This study suggests an intelligent feature reduction methodology based on machine learning that uses Modified Principal Component Analysis (MPCA) … …Journal of Computer Science, Vol. 21, Issue 8 · 10 Oct 2025 · 2,290 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Intrusion Detection System Using Optimized Deep Learning for IoT NetworksChempavathy B., Mouleeswaran S. K.In the rapidly evolving landscape of Internet of Things (IoT) networks, assuring security is paramount. Cyber-attacks on IoT networks are evolving in complexity and scale. Intruders employ diverse tactics, including malware, Denial of Service (DoS) attacks, along with unauthorized access. This research aims to propose an optimized Deep Learning (DL) based Intrusion Detection System (IDS) to bolster security within IoT … …Journal of Computer Science, Vol. 21, Issue 8 · 9 Oct 2025 · 2,993 accessesView PDFCite
Research ArticleOpen accessIn the abstractPeriodic Service Behavior Strain Analysis-Based Intrusion Detection in CloudS. Priya, R. S. PonmagalThe problem of intrusion detection in cloud environments has been well studied. The presence of adversaries would challenge data security in the cloud by generating intrusion attacks towards the cloud data and should be mitigated for the development of the cloud environment. In mitigating intrusion attacks, there exist several techniques in the literature. The method uses different features like frequency … …Journal of Computer Science, Vol. 20, Issue 2 · 28 Dec 2023 · 5,082 accessesView PDFCite
Research ArticleOpen accessIn the abstractEfficient Detection and Mitigation of Rushing Attacks in VANETs Using RAID: A Novel Intrusion Detection SystemVamshi Krishna Kapu, Ganesh Reddy KarriThe vehicle manufacturing hub has evolved over the last decade with the emergence of self-driving vehicles and human-driven vehicles that use the concept of Artificial Intelligence (AI). Vehicular Ad Hoc Network (VANET) is a subset of Mobile Ad Hoc Network (MANET) that allows vehicles to communicate with one another and the Road Side Unit (RSU). VANET has been a game … …Journal of Computer Science, Vol. 19, Issue 9 · 26 Aug 2023 · 5,746 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Feature Extraction Dual DCT-DWT Image Watermarking Combined with Chaos-Based CryptosystemKumari Rinki, Pushpneel Verma, Tanupriya Choudhury, Bhupesh Kumar SinghAs a result of the emerging technologies such as Internet-of-Things (IoT), data analysis and automation in many aspects of identity, watermarking has become increasingly important. A majority of prior systems focused on watermark embedding and recovery techniques for binary and grey-scale images in one specified region of the cover image, making the system less dependable. This study develops a novel … …Journal of Computer Science, Vol. 17, Issue 10 · 13 Nov 2021 · 6,094 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Scalable Hybrid CNN-LSTM and SDN Based Architecture for Real-Time DDoS Defence in IoT and Cloud NetworksSujit Sutradhar, Joy Lal Sarkar, Rajesh Kumar VermaDistributed Denial-of-Service (DDoS) is one of the most significant threats to the security of IoT, cloud, and Software-Defined Network (SDN) environments because it can aggravate network unavailability and disrupt the continuity of services. This study presents a hybrid CNN-LSTM-based DDoS detection and mitigation system for real-time DDoS detection in the context of heterogeneous network environments, which is integrated with SDN … …Journal of Computer Science, Vol. 22, Issue 10 · 19 Oct 2026 · 508 accessesView PDFCite
Research ArticleOpen accessIn the abstractBenchmarking Lightweight Deep Learning Models for Field Based Sorghum Leaf Disease DetectionPrince Daughin Ngqabutho NcubeSorghum is a climate-resilient cereal crop central to food and livelihood security across Southern Africa, yet its productivity is frequently reduced by foliar diseases that smallholder farmers struggle to diagnose reliably in the field. While deep learning has demonstrated strong potential for automated plant disease identification, sorghum remains underrepresented in the literature, and no prior study has provided a comprehensive, … …Journal of Computer Science, Vol. 22, Issue 10 · 29 Sep 2026 · 535 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Optimized Multi-Layer Perceptron Framework for Detecting and Classifying IoT AttacksSanchit Vashisht, Shalli RaniThe Internet of Things (IoT) is revolutionizing industries by connecting billions of smart devices, enabling automation and information exchange. The expansion of IoT ecosystems has simultaneously increased the surface area for cyberattacks. These environments are particularly vulnerable to a wide range of threats, such as Distributed Denial-of-Service (DDoS), poisoning, brute-force SSH intrusions, and various network reconnaissance techniques. The dynamic nature … …Journal of Computer Science, Vol. 21, Issue 12 · 11 Feb 2026 · 1,333 accessesView PDFCite
Research ArticleOpen accessIn the abstractSecurity based Approach of SHA 384 and SHA 512 Algorithms in Cloud EnvironmentThambusamy Velmurugan, Sivakumar KarthigaCloud computing is going to be the next big thing in the era of internet world. As the world moves ahead towards enhancement of the cloud features we also have to take a serious consideration of the enhancing cloud securities to protect the end-user’s data. The major usage of this cloud feature are widely applied in the cloud based IT … …Journal of Computer Science, Vol. 16, Issue 10 · 28 Oct 2020 · 6,841 accessesView PDFCite
Research ArticleOpen accessIn the abstractPHASEY: A Contrastive Learning Approach for Enhanced Human Gait Phases RecognitionUrvashi, Deepak Kumar, Vinay Kukreja, Ayush DograHuman gait has gained much attention in behavioral biometrics as it possesses unique and distinctive characteristics. Gait phases, which describe the different patterns of human walking, are significant for the analysis and understanding of movement in an individual. Hence, the identification of gait phases is important for the accurate determination and interpretation of walking patterns, ranging from healthcare and security … …Journal of Computer Science, Vol. 21, Issue 8 · 16 Sep 2025 · 4,638 accessesView PDFCite