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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 · 4,692 accessesView PDFCite
Research ArticleOpen accessIn the abstractMolecular Identification of Domestic and Wild Boars Using Cytochrome-b Specific Primers for Halal AuthenticationRifqi, Edi Suryanto, Ari Surya Sukarno et al.The subject of adulterating wild boar and pig meat products with other animal meat is delicate, particularly in the Muslim nation of Indonesia. In recent years, there has been a lot of concern over halal meat products that contain wild boar and pig meat due to Economically Motivated Adulteration (EMA). However, there are limited studies of PCR-DNA-based to discriminate between … …American Journal of Animal and Veterinary Sciences, Vol. 20, Issue 3 · 14 Nov 2025 · 2,388 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning Approach to Mitigate DDoS Attacks in SDNHema Surendrakumar Dhadhal, Paresh Kotak, Parvez Faruki, Atul GonsaiThe rise of Distributed Denial of Service (DDoS) attacks remains a significant obstacle to network security and availability. This abstract presents a new hybrid model for DDoS mitigation in Software-Defined Networking (SDN) environments, combining a Semi-supervised Deep Extreme Learning Machine (Semi-Deep ELM) with a hybrid architecture. SDN's centralized control and programmability create an ideal platform for implementing advanced mitigation strategies. … …Journal of Computer Science, Vol. 20, Issue 9 · 5 Jul 2024 · 5,345 accessesView PDFCite
Research ArticleOpen accessIn the abstractPersonalized Recommendation System: Web of Things Using Modular Density-Based Community DiscoveryVinod Patidar, Jayashree A. Patil, Sonika Thapak et al.Community discovery is the cornerstone and core of study in customized recommendation, assembling group features and social network analysis on the web of things. Conventional community discovery methods, however, struggle with difficulties including low accuracy, delayed convergence, modularity resolution limits and more when dealing with more complicated social networks. Because of this, differential evolution and module density are included in … …Journal of Computer Science, Vol. 20, Issue 9 · 21 Jun 2024 · 5,644 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Survey on Event Detection Models for Text Data StreamsWafa Zubair AL-Dyani, Farzana Kabir Ahmad, Siti Sakira KamaruddinEvent Detection (ED) is a study area that attracts the attention of decision-makers from various disciplines in order to help them in taking the right decision. ED has been examined on various text streams like Twitter, Facebook, Emails, Blogs, Web Forums and newswires. Many ED models have been proposed in literature. In general, ED model consists of six main phases: … …Journal of Computer Science, Vol. 16, Issue 7 · 14 Jul 2020 · 7,044 accessesView PDFCite
Review ArticleOpen accessIn the abstractAI-Based Techniques for DDoS Attack Detection in WSN: A Systematic Literature ReviewMohammed Al-Naeem, Mohammed Ashikur Rahman, Adamu AbuBakar Ibrahim, M.M. Hafizur RahmanWireless Sensor Networks (WSNs) are currently being used in various industries such as healthcare, engineering, the environment and so on. Security is a significant issue for WSN due to its infrastructure and limited physical security. Distributed Denial of Service (DDoS) is one of the most vulnerable attacks that can be defined as attacks launched from multiple ends into a set … …Journal of Computer Science, Vol. 16, Issue 6 · 29 Jun 2020 · 8,378 accessesView PDFCite
Research ArticleOpen accessIn the abstractDetection of Commercial Fraud in Processed Meat Products Using Rapid TechniquesAli M. Ahmed, Takwa H. Ismail, Reham R. Abouelmaatti et al.Meat adulteration with different species has become a considerable problem worldwide. It means that meat products contain undeclared meat species; so, the meat ingredients are not consistent with the label. It has direct impact on public health, religious faith, fair-trades and food safety standers. This study focused on species adulteration detection in meat products by applying accurate, slandered and fast … …American Journal of Biochemistry and Biotechnology, Vol. 16, Issue 2 · 4 Jun 2020 · 7,821 accessesView PDFCite
Research ArticleOpen accessIn the abstractPanoramic Video Surveillance: An Analysis of Burglary Detection Based on YOLO Framework in Residential AreasPavithra S, B. MurugananthamArtificial Intelligence (AI) is a technique that incorporates human intelligence into mundane activities. And there is no question that AI is significantly affecting security and surveillance. Although relying on numerous resources, finding answers, and implementing technology for decades, our security and surveillance systems still have flaws. In every country around the globe, the use of video security and surveillance is … …Journal of Computer Science, Vol. 19, Issue 11 · 2 Oct 2023 · 6,044 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Regularization Mechanism for Combating Class Imbalance Problem in Intrusion Detection System for Defending DDoS Attack in SDNNarender M, Yuvaraju B NIntegration of deep learning into Intrusion Detection Systems (IDS) for Software Defined Networking (SDN) is an emerging field of research. Most of the datasets used to build IDS are highly imbalanced, especially in the case of DDoS attacks, which account for a larger percentage of malicious samples than normal traffic. As a result of a class imbalance, the classification result … …Journal of Computer Science, Vol. 19, Issue 3 · 24 Feb 2023 · 5,668 accessesView PDFCite
Review ArticleOpen accessIn the abstractMachine Learning-Based Detection of Credit Card Fraud: A Comparative StudyZainab Khamees Alkhateeb, Abeer Tariq MaoloodOne of the fastest-growing problems with a high impact on the financial sector is financial fraud. Recently, data mining has been identified as one of the effective ways of detecting fraudulent credit card transactions. As a data mining problem, the detection of fraudulent credit card transaction is a challenging task due to the following reasons: (i) The frequent changes in … …American Journal of Engineering and Applied Sciences, Vol. 12, Issue 4 · 25 Dec 2019 · 7,783 accessesView PDFCite