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24 results for “DDoS Attacks”
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Research ArticleOpen accessPhrase in the titleDeep 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 · 5,338 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleCorrelation Based Approach with a Sliding Window Model to Detect and Mitigate Ddos AttacksD. Ayyamuthukumar, S. KarthikDDoS attacks have become very popular since the turn of this millennium and has stayed in the headlines due to ever increasing and sometimes devastating attacks on popular web servers. In this study, we deal with DDoS attacks by proposing a correlation based approach with a sliding window model to detect and mitigate DDoS attack. The proposed scheme identifies malicious … …Journal of Computer Science, Vol. 11, Issue 2 · 2 Feb 2015 · 6,745 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA 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
Review ArticleOpen accessIn the keywordsDDoS Mitigation Using Machine Learning in Software-Defined NetworksAhmed Gaber Abu Abd-Allah, Noureldin Omar Mohamed, Mohamed Samir Mohamed et al.With the escalating frequency and sophistication of Distributed Denial of Service (DDoS) attacks, the realm of cyber security has witnessed a paradigm shift towards innovative solutions. This review explores the potential of machine learning as a powerful defense mechanism in the field of DDoS mitigation within Software-Defined Networks (SDNs). The study methodically examines a variety of machine learning algorithms used … …Journal of Computer Science, Vol. 21, Issue 4 · 23 Mar 2025 · 6,774 accessesView PDFCite
Research ArticleOpen accessIn the keywordsEfficiency 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 keywordsFlooding Distributed Denial of Service Attacks-A ReviewKhadijah Wan Mohd Ghazali, Rosilah HassanProblem statement: Flaws either in users’ implementation of a network or in the standard specification of protocols has resulted in gaps that allow various kinds of network attack to be launched. Of the kinds of network attacks, denial-of-service flood attacks have caused the most severe impact. Approach: This study reviews recent researches on flood attacks and their mitigation, classifying such … …Journal of Computer Science, Vol. 7, Issue 8 · 15 Jul 2011 · 6,847 accessesView PDFCite
Research ArticleOpen accessIn the abstractThe Optimized Extreme Learning Machine (GA-OELM) for DDoS Attack Detection in Cloud EnvironmentMeryem Ec-Sabery, Adil Ben Abbou, Abdelali Boushaba et al.The widespread adoption of cloud computing has increased the attack surface and raised significant security concerns. A Distributed Denial of Service (DDoS) is a serious attack that depletes the network and server resources in cloud computing, causing service downtime or reduced performance. Therefore, defending against DDoS attacks becomes an urgent need. In this present paper, we propose an Optimized Extreme … …Journal of Computer Science, Vol. 21, Issue 1 · 19 Dec 2024 · 5,033 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Deep Ensemble Framework for DDoS Attack Recognition and Mitigation in Cloud SDN EnvironmentS. Annie Christila, R. SivakumarMuch research has been done in the recent past on the absolute shift of Internet infrastructure in order to make it more significantly programmable, configurable and make it more conveniently feasible. Software Defined Networking (SDN) forms the basis for this absolute shift in Internet infrastructure. When you look at the benefits of an SDN-based cloud environment they are monumental. Namely, … …Journal of Computer Science, Vol. 20, Issue 10 · 5 Aug 2024 · 5,337 accessesView PDFCite
Research ArticleOpen accessIn the abstractDDoS Attack Detection Using Enhanced Neural Network Algorithm in Software-Defined NetworksHema Surendrakumar Dhadhal, Paresh P KotakWith the uncommon advancement of technology and networking, the world today is totally relying on it. The most obvious drawback of this technical progress resulted in several possible dangers. A Distributed Denial of Service (DDoS) attack is one in which a large number of compromised systems work together to prevent service from being provided to the targeted system. Consequently, to … …Journal of Computer Science, Vol. 19, Issue 6 · 24 May 2023 · 5,721 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 · 5,659 accessesView PDFCite