Related papers: Lightweight CNN-Based DDoS Detection for Resource-…
Software-defined networking (SDN) is a promising technology to overcome many challenges in wireless sensor networks (WSN), particularly with respect to flexibility and reuse. Conversely, the centralization and the planes' separation turn…
Cyber-attacks have been one of the deadliest attacks in today's world. One of them is DDoS (Distributed Denial of Services). It is a cyber-attack in which the attacker attacks and makes a network or a machine unavailable to its intended…
Distributed Denial of Service (DDoS) attacks pose a significant threat to the stability and reliability of online systems. Effective and early detection of such attacks is pivotal for safeguarding the integrity of networks. In this work, we…
The concept of Software Defined Networking (SDN) represents a modern approach to networking that separates the control plane from the data plane through network abstraction, resulting in a flexible, programmable and dynamic architecture…
Distributed denial-of-service (DDoS) attacks threaten the availability of Internet of Things (IoT) infrastructures, particularly under resource-constrained deployment conditions. Although transfer learning models have shown promising…
Distributed Denial-of-Service (DDoS) attacks represent a persistent threat to modern telecommunications networks: detecting and counteracting them is still a crucial unresolved challenge for network operators. DDoS attack detection is…
The increasing complexity of IoT edge networks presents significant challenges for anomaly detection, particularly in identifying sophisticated Denial-of-Service (DoS) attacks and zero-day exploits under highly dynamic and imbalanced…
Software-defined networking (SDN) was devised to simplify network management and automate infrastructure sharing in wired networks. These benefits motivated the application of SDN in wireless sensor networks to leverage solutions for…
This study introduces a robust solution for the detection of Distributed Denial of Service (DDoS) attacks in Internet of Things (IoT) systems, leveraging the capabilities of Graph Convolutional Networks (GCN). By conceptualizing IoT devices…
This study focuses on a method for detecting and classifying distributed denial of service (DDoS) attacks, such as SYN Flooding, ACK Flooding, HTTP Flooding, and UDP Flooding, using neural networks. Machine learning, particularly neural…
Recent years witnessed a surge in network traffic due to the emergence of new online services, causing periodic saturation and complexity problems. Additionally, the growing number of IoT devices further compounds the problem. Software…
Software Defined Networking (SDN) is a network paradigm shift that facilitates comprehensive network programmability to cope with emerging new technologies such as cloud computing and big data. SDN facilitates simplified and centralized…
This paper presents a hardware-efficient deep neural network (DNN), optimized through hardware-aware neural architecture search (HW-NAS); the DNN supports the classification of session-level encrypted traffic on resource-constrained…
The Software-defined networking(SDN) paradigm centralizes control decisions to improve programmability and simplify network management. However, this centralization turns the network vulnerable to denial of service (DoS) attacks, and in the…
Protecting the networks of tomorrow is set to be a challenging domain due to increasing cyber security threats and widening attack surfaces created by the Internet of Things (IoT), increased network heterogeneity, increased use of…
The distributed denial-of-service (DDoS) attack stands out as a highly formidable cyber threat, representing an advanced form of the denial-of-service (DoS) attack. A DDoS attack involves multiple computers working together to overwhelm a…
The (logically) centralised architecture of the software-defined networks makes them an easy target for packet injection attacks. In these attacks, the attacker injects malicious packets into the SDN network to affect the services and…
Slow-running attacks against network applications are often not easy to detect, as the attackers behave according to the specification. The servers of many network applications are not prepared for such attacks, either due to missing…
The possibility of programming the control and data planes, enabled by the Software-Defined Networking (SDN) paradigm, represents a fertile ground on top of which novel operation and management mechanisms can be fully explored, being…
In recent years, Convolutional Neural Networks (CNN) have proven to be efficient analysis tools for processing point clouds, e.g., for reconstruction, segmentation and classification. In this paper, we focus on the classification of edges…