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44 results for “Traffic Attacks”
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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 abstractGenerating IoT Specific Anomaly Datasets Using Cooja Simulator (Contiki-OS) and Performance Evaluation of Deep Learning Model Coupled with Aquila OptimizerVandana Choudhary, Sarvesh Tanwar, Tanupriya ChoudhuryIn recent times, the massive expansion of the Internet of Things (IoT) has transformed various facets of everyday life and industries. The compelling cause behind the widespread adoption of IoT is the increasing availability of affordable, compact, and energy-efficient computing devices. While these devices offer significant benefits, they also raise substantial security and privacy challenges. Consequently, safeguarding IoT networks and … …Journal of Computer Science, Vol. 20, Issue 4 · 1 Feb 2024 · 6,850 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 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
Research ArticleOpen accessIn the abstractComprehensive Assessment of Spatial Distribution of Road-Network Vulnerability in South AsiaPan Yuqi, Jiang Penghui, Li Manchun, Chen DengshuaiUnexpected phenomena-natural disasters, accidents and wars-can disrupt regional traffic systems because of the incapacities of road networks to sustain inflicted impacts. Therefore, the assessment of road-network vulnerability becomes integral to traffic-safety-maintenance and accident-prevention procedures. This study demonstrates the development of a comprehensive network system based on suggested improvements in node extraction, road construction and network attribution. An indicator system for … …American Journal of Environmental Sciences, Vol. 17, Issue 6 · 24 Dec 2021 · 6,446 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Hybrid Method for Network Anomaly Detection Based on Traffic Prediction and Change Point DetectionMouhammd AlkasassbehIn recent years, computer networks have become more and more advanced in terms of size, applications, complexity and level of heterogeneity. Moreover, availability and performance are important issues for end users. New types of cyber-attacks that can affect and damage network performance and availability are constantly emerging and some threats, such as Distributed Denial of Service (DDoS) attacks, can be … …Journal of Computer Science, Vol. 14, Issue 2 · 3 Jan 2018 · 8,404 accessesView PDFCite
Research ArticleOpen accessIn the abstractCorrelation 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 abstractA Survey of Anomaly Detection Using Data Mining Methods for Hypertext Transfer Protocol Web ServicesMohsen Kakavand, Norwati Mustapha, Aida Mustapha et al.In contrast to traditional Intrusion Detection Systems (IDSs), data mining anomaly detection methods/techniques has been widely used in the domain of network traffic data for intrusion detection and cyber threat. Data mining is widely recognized as popular and important intelligent and automatic tools to assist humans in big data security analysis and anomaly detection over IDSs. In this study we … …Journal of Computer Science, Vol. 11, Issue 1 · 22 Jan 2015 · 9,252 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