Related papers: A flow-based IDS using Machine Learning in eBPF
System call filtering is a widely used security mechanism for protecting a shared OS kernel against untrusted user applications. However, existing system call filtering techniques either are too expensive due to the context switch overhead…
Despite the great developments in information technology, particularly the Internet, computer networks, global information exchange, and its positive impact in all areas of daily life, it has also contributed to the development of…
One of the key challenges of machine learning (ML) based intrusion detection system (IDS) is the expensive computational complexity which is largely due to redundant, incomplete, and irrelevant features contain in the IDS datasets. To…
The eBPF technology in the Linux kernel has been widely adopted for different applications, such as networking, tracing, and security, thanks to the programmability it provides. By allowing user-supplied eBPF programs to be executed…
Network Intrusion Detection Systems (NIDS) play an important role as tools for identifying potential network threats. In the context of ever-increasing traffic volume on computer networks, flow-based NIDS arise as good solutions for…
Linux is the foundation of the digital age, accounting for the majority of the cloud and mobile OS markets. Any device that runs Linux uses the Linux page cache, a central pillar in OS and application performance, serving to reduce…
The rise of programmable data plane (PDP) and in-network computing (INC) paradigms paves the way for the development of network devices (switches, network interface cards, etc.) capable of performing advanced processing tasks. This allows…
Network Intrusion Detection Systems (IDS) aim to detect the presence of an intruder by analyzing network packets arriving at an internet connected device. Data-driven deep learning systems, popular due to their superior performance compared…
As an inevitable trend of future 5G networks, Software Defined architecture has many advantages in providing central- ized control and flexible resource management. But it is also confronted with various security challenges and potential…
The use of Machine Learning (ML) techniques in Intrusion Detection Systems (IDS) has taken a prominent role in the network security management field, due to the substantial number of sophisticated attacks that often pass undetected through…
Learning-based Network Intrusion Detection Systems (NIDSs) are widely deployed for defending various cyberattacks. Existing learning-based NIDS mainly uses Neural Network (NN) as a classifier that relies on the quality and quantity of…
The rise of deep learning has led to various successful attempts to apply deep neural networks (DNNs) for important networking tasks such as intrusion detection. Yet, running DNNs in the network control plane, as typically done in existing…
Several machine learning-based Network Intrusion Detection Systems (NIDS) have been proposed in recent years. Still, most of them were developed and evaluated under the assumption that the training context is similar to the test context.…
Extended Berkeley Packet Filter (BPF) has emerged as a powerful method to extend packet-processing functionality in the Linux operating system. BPF allows users to write code in high-level languages (like C or Rust) and execute them at…
Network Intrusion Detection Systems (NIDSs) detect intrusion attacks in network traffic. In particular, machine-learning-based NIDSs have attracted attention because of their high detection rates of unknown attacks. A distributed processing…
Network security engineers work to keep services available all the time by handling intruder attacks. Intrusion Detection System (IDS) is one of the obtainable mechanism that used to sense and classify any abnormal actions. Therefore, the…
Modern vehicles are increasingly connected, and in this context, automotive Ethernet is one of the technologies that promise to provide the necessary infrastructure for intra-vehicle communication. However, these systems are subject to…
Existing software-based memory tiering systems decide which pages to place on the slower or faster tier. However, they do not take into account two important factors that greatly influence application performance: the size of the migrated…
As an active network security protection scheme, intrusion detection system (IDS) undertakes the important responsibility of detecting network attacks in the form of malicious network traffic. Intrusion detection technology is an important…
Network Intrusion Detection Systems (NIDS) have progressively shifted from signature-based techniques toward machine learning and, more recently, deep learning methods. Meanwhile, the widespread adoption of encryption has reduced payload…