Related papers: Machine Learning-Based Detection of DDoS Attacks i…
Recent developments in intelligent transport systems (ITS) based on smart mobility significantly improves safety and security over roads and highways. ITS networks are comprised of the Internet-connected vehicles (mobile nodes), roadside…
Unsupervised anomaly detection is widely used to detect Distributed Denial-of-Service (DDoS) attacks in cloud-native 5G networks, yet most studies assume a fixed traffic representation, either temporal or structural, without validating…
Distributed Denial of Service (DDoS) is a common type of Cybercrime. It can strongly damage a company reputation and increase its costs. Attackers improve continuously their strategies. They doubled the amount of unleashed communication…
We present a comprehensive study on applying machine learning to detect distributed Denial of service (DDoS) attacks using large-scale Internet of Things (IoT) systems. While prior works and existing DDoS attacks have largely focused on…
This thesis addresses the use of Cooperative Intelligent Transport Systems (CITS) to improve road safety and efficiency by enabling vehicle-to-vehicle communication, highlighting the importance of secure and accurate data exchange. To…
The detection of Denial of Service (DoS) attacks remains a challenge for the cloud environment, affecting a massive number of services and applications hosted by such virtualized infrastructures. Typically, in the literature, the detection…
Mobile Ad hoc Networks (MANETs) are considered as a new paradigm of infrastructure-less mobile wireless communication systems. MANETs are being widely studied and it is the technology that is attracting a large variety of applications.…
In this paper, an analytical model for DDoS attacks detection is proposed, in which propagation of abrupt traffic changes inside public domain is monitored to detect a wide range of DDoS attacks. Although, various statistical measures can…
Unmanned Aerial Vehicles (UAVs) are becoming more dependent on mission success than ever. Due to their increase in demand, addressing security vulnerabilities to both UAVs and the Flying Ad-hoc Networks (FANET) they form is more important…
Most non-safety applications deployed in Vehicular Ad-hoc Network (VANET) use vehicle-to-infrastructure (V2I) and I2V communications to receive various forms of content such as periodic traffic updates, advertisements from adjacent…
In order to satisfy diverse quality-of-service (QoS) requirements of complex real-time video applications, civilian and tactical use cases are employing software-defined hybrid edge-cloud systems. One of the primary QoS requirements of such…
We developed a distributed data mining system to elaborate a decision concerning the cause of urban traffic congestion via emerging connected vehicle (CV) technology. We observe this complex phenomena through the interactions between…
In this paper we introduce an intrusion detection system for Denial of Service (DoS) attacks against Domain Name System (DNS). Our system architecture consists of two most important parts: a statistical preprocessor and a neural network…
Most autonomous vehicles (AVs) rely on LiDAR and RGB camera sensors for perception. Using these point cloud and image data, perception models based on deep neural nets (DNNs) have achieved state-of-the-art performance in 3D detection. The…
Deep Neural Networks (DNNs) are widely used for traffic sign recognition because they can automatically extract high-level features from images. These DNNs are trained on large-scale datasets obtained from unknown sources. Therefore, it is…
Disruption from service caused by DDoS attacks is an immense threat to Internet today. These attacks can disrupt the availability of Internet services completely, by eating either computational or communication resources through sheer…
This paper deals with broadcasting problem in vehicular ad hoc networks (VANETs). This communication mode is commonly used for sending safety messages and traffic information. However, designing an efficient broadcasting protocol is hard to…
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…
Vehicle Ad-hoc Networks (VANETs) have experienced significant development in recent years, playing a crucial role in enhancing the driving experience by enabling safer and more efficient inter-vehicle interactions through information…
Nowadays, Vehicle Ad - hoc Nets (VANET) applications have become very important in our lives because VANET provides drivers with safety messages, warnings, and instructions to ensure drivers have a safe and enjoyable journey. VANET Security…