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As cyber threats like Distributed Denial of Service (DDoS) attacks escalate, developing intelligent detection systems is imperative for securing cloud computing. This research proposes a Deep Recurrent Neural Network (Deep RNN) model with Long ...

A testbed with open-source tools and commercial equipment is designed to investigate the timing of ML-based xApp operations in DDoS attack detection during the Random Access procedure. Results show high-precision and high-recall ML classifiers operating ...

Distributed Denial of Service (DDoS) attacks pose a major threat to organizations by overwhelming their networks and servers. Effective identification of DDoS attacks is crucial for timely mitigation. This paper proposes a novel approach using ...

DDoS attack have always been a popular topic in the field of network security. As an emerging networking paradigm, SDN’s characteristics such as centralized control and management and monitoring flow-based traffic make it an ideal platform to ...

In this paper, we propose a deep learning model based on a novel Divide and Conquer Attention (DCA) mechanism, for efficient detection of Distributed Denial of Service (DDoS) attacks in a virtual Software Defined Networking(SDN) environment. DDoS ...

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• Development of mechanism that focus on important parts of traffic data in the SDN environment.
• Evaluation of the proposed model performance with diverse DDoS attacks in the SDN environments.
• Validation of the proposed detection ...

With IoV’s rapid growth and widespread use, securing it has become a key focus in scholarly research. In vehicle networking, DDoS attacks are prevalent and impactful. Existing deep learning methods for DDoS detection in IoV often yield superior results. ...

In recent years, smart grid-based Electric Vehicle (EV) charging systems have increasingly faced vulnerabilities to Distributed Denial of Service (DDoS) attacks, especially through malicious authentication failures. These attacks typically ...

In the evolving cybersecurity landscape, the rising frequency of Distributed Denial of Service (DDoS) attacks requires robust defense mechanisms to safeguard network infrastructure availability and integrity. Deep Learning (DL) models have ...

eBPF and XDP are promising technologies that are capable of accelerating packet processing inside the Linux kernel. Despite these benefits, eBPF is constrained by a number of rigorous restrictions that are imposed to protect the kernel. One such ...

Vehicular networks are vulnerable to Distributed Denial of Service (DDoS), an extension of a Denial of Service (DoS) attack. The existing solutions for DDoS detection in vehicular networks use various Machine Learning (ML) algorithms. However, ...

Distributed Denial-of-Service (DDoS) attacks are a major threat to computer networks. These attacks can be carried out by flooding a network with malicious traffic, overwhelming its resources, and/or making it unavailable to legitimate users. ...

The Internet of Things (IoT) is a rapidly emerging technology that has become more valuable and vital in our daily lives. This technology enables connection and communication between objects and devices and allows these objects to exchange ...

In recent years, QUIC protocol has emerged as a promising alternative to traditional transport protocols like TCP and UDP, offering significant performance improvements in latency and throughput. Additionally, QUIC provides strong security protection ...

IoT application uses MQTT, an application layer protocol that facilitates machine-to-machine communication using a central entity called broker. The vulnerability lies in the broker being susceptible to intrusion attempts, where a potential ...

The exponential growth of internet-enabled devices and their interconnectedness heightens the vulnerability of technology to cyber threats. The simplicity of communication lures attackers to execute numerous attacks, with Distributed Denial of ...

Software-Defined Network (SDN) is a perception of networking that separates the network into different layers responsible for applications, control, and data, thus providing a flexible and programmable architecture and making the network more ...

• Detail of DoS/DDoS attacks across SDN layers and boundaries.
• Review the existing solutions for dealing with DoS/DDoS attacks in SDN.
• Security Issues and Challenges in the SDN environment are discussed.
• Vision for addressing DoS/...

The rising danger of Distributed Denial of Service (DDoS) attacks in Software-Defined Networking (SDN) environments stresses advanced detection strategies to safeguard network availability and service integrity. By utilizing ensemble learning ...

This research builds a realtime and multi-agent system to handle Distributed Denial of Service (DDoS) attacks. The integration of an Intrusion Detection System (IDS), Security Information and Event Management (SIEM), and Security Orchestration, ...

DDoS attacks are a type of cloud incursion that lessen service degradation. DDoS attacks target the cloud network with invalid requests, rejecting legitimate requests. Such attacks disrupt the entire cloud architecture, thus it needs efficient ...

Distributed Denial of Service (DDoS) attacks in IoT networks are one of the most devastating and challenging cyber-attacks. The number of IoT users is growing exponentially due to the increase in IoT devices over the past years. Consequently, ...