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10 results for “Multi-Attack Detection”
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Research ArticleOpen accessPhrase in the titleSecuring IoT Networks: Multi-Attack Detection of RPL Routing Threats Using Deep LearningAyoub Krari, Abdelmajid Hajami, Ayoub Toubi, Marouane Ait SaidThe growing frequency of cyber threats in Internet of Things (IoT) networks, including attacks on RPL routing, requires the creation of strong detection systems to safeguard network integrity and provide dependable communication. This study is driven by the pressing necessity to tackle the security weaknesses in IoT networks, where threats such as black holes, version number alteration, DIS flooding, and … …Journal of Computer Science, Vol. 21, Issue 4 · 6 Mar 2025 · 5,397 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleRobust 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 keywordsSoft Marking Scheme of SVM Hierarchical Classifiers for Attack ClassificationAzizi Abdullah, Warhamni Jani@MokhtarClassification is a predictive modelling problem that involves assigning a class label to an instance correctly. There exist several strategies in machine learning to deal with the multi-class classification problems for attack detection. One of the popular strategies is the one-vs-one that decomposes the multi-class problem into multiple binary ones. The approach has been applied in many popular supervised learning … …Journal of Computer Science, Vol. 17, Issue 9 · 27 Sep 2021 · 6,000 accessesView PDFCite
Research ArticleOpen accessIn the abstractEfficiency Assessment of Software-Defined Networking for Real-Time Network SystemsNeelam Gupta, Sarvesh Tanwar, Sumit BadotraSoftware Networking (SDN) is growing in popularity due to its benefits, which include portability, mobility, analytics, and ease of creation. But it needs to be adequately shielded from security risks. One of the main vulnerabilities to the SDN network is the Distributed Denial-of-Service (DDoS) attack. To fulfill the demands of the complex and demanding security concerns of today, a new … …Journal of Computer Science, Vol. 20, Issue 6 · 8 Apr 2024 · 4,918 accessesView PDFCite
Research ArticleOpen accessIn the abstractTetracycline Resistance Profile in Darwin Finches in the Galapagos IslandsMaría Inés Baquero, Marylin Cruz, Viviana Duque et al.Antimicrobial Resistance (AMR), which is the ability of microorganisms to withstand attack by antimicrobial drugs, has a worldwide impact. Thus, it is important to identify resistance mechanisms circulating in the environment. Among antimicrobials widely used in human and veterinary health, tetracycline is ideal due to its safety and has been categorized by the WHO as a critically important antimicrobial. Based … …American Journal of Animal and Veterinary Sciences, Vol. 17, Issue 4 · 19 Dec 2022 · 5,791 accessesView PDFCite
Research ArticleOpen accessIn the abstractMULTI SCALE TIME SERIES PREDICTION FOR INTRUSION DETECTIONG. Palanivel, K. DuraiswamyWe propose an anomaly-based network intrusion detection system, which analyzes traffic features to detect anomalies. The proposed system can be used both in online as well as off-line mode for detecting deviations from the expected behavior. Although our approach uses network packet or flow data, it is general enough to be adaptable for use with any other network variable, which … …American Journal of Applied Sciences, Vol. 11, Issue 8 · 27 Jun 2014 · 6,776 accessesView PDFCite
Research ArticleOpen accessIn the abstractINTRUSION DETECTION SYSTEM IN SECURE SHELL TRAFFIC IN CLOUD ENVIRONMENTMehdi Barati, Azizol Abdullah, NurIzura Udzir et al.Due to growth of Cloud computing usage, the need to apply encrypted protocols to provide confidentiality and integrity of data increases dramatically. Attacker can take advantage of these protocols to hide the intrusion and evade detection. Many traditional attack detection techniques have been proposed to provide security in the networks but none of them can be implemented properly in encrypted … …Journal of Computer Science, Vol. 10, Issue 10 · 26 Jun 2014 · 7,851 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordAn 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 accessAll words, across the recordEnhancing IoT RPL Protocol Security Against Black Hole Attacks with Deep Learning TechniquesKrari Ayoub, Hajami Abdelmajid, Toubi Ayoub, Mihi SoukainaAs the Internet of Things (IoT) extends its reach into critical infrastructures, it encounters escalating security threats, particularly black hole attacks that jeopardize network communication. The growing use of IoT in essential services underscores the need for robust network integrity. Driven by this urgency, our research has developed a sophisticated detection framework that effectively identifies black hole attacks within IoT … …Journal of Computer Science, Vol. 20, Issue 11 · 18 Oct 2024 · 5,000 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordDeep 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 · 5,659 accessesView PDFCite