Related papers: An Efficient Analytical Solution to Thwart DDoS At…
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…
A considerable portion of the machine learning literature applied to intrusion detection uses outdated data sets based on a simulated network with a limited environment. Moreover, flaws usually appear in datasets and the way we handle them…
This paper explores the critical issue of enhancing cybersecurity measures for low-cost, Wi-Fi-based Unmanned Aerial Vehicles (UAVs) against Distributed Denial of Service (DDoS) attacks. In the current work, we have explored three variants…
We unveil the existence of a vulnerability in Wi-Fi, which allows an adversary to remotely launch a Denial-of-Service (DoS) attack that propagates both in time and space. This vulnerability stems from a coupling effect induced by hidden…
Since it is impossible to predict and identify all the vulnerabilities of a network beforehand, and penetration into a system by malicious intruders cannot always be prevented, intrusion detection systems (IDSs) are essential entities to…
Multi-access Edge Computing (MEC) is a 5G-enabling solution that aims to bring cloud-computing capabilities closer to the end-users. This paper focuses on mitigation techniques against Distributed Denial-of-Service (DDoS) attacks in the…
The network security analyzers use intrusion detection systems (IDSes) to distinguish malicious traffic from benign ones. The deep learning-based IDSes are proposed to auto-extract high-level features and eliminate the time-consuming and…
Motivated by the impressive but diffuse scope of DDoS research and reporting, we undertake a multistakeholder (joint industry-academic) analysis to seek convergence across the best available macroscopic views of the relative trends in two…
While collaborative systems provide convenience to our lives, they also face many security threats. One of them is the Low-rate Distributed Denial-of-Service (LDDoS) attack, which is a worthy concern. Unlike volumetric DDoS attacks that…
As IoT deployments grow in scale for applications such as smart cities, they face increasing cyber-security threats. In particular, as evidenced by the famous Mirai incident and other ongoing threats, large-scale IoT device networks are…
Denial of service (DoS) and Distributed Denial of Service (DDoS) attacks continue to threaten the reliability of networking systems. Previous approaches for protecting networks from DoS attacks are reactive in that they wait for an attack…
Distributed Denial-of-Service (DDoS) is a menace for service provider and prominent issue in network security. Defeating or defending the DDoS is a prime challenge. DDoS make a service unavailable for a certain time. This phenomenon harms…
Defending against distributed denial of service (DDoS) attacks in the Internet is a fundamental problem. However, recent industrial interviews with over 100 security experts from more than ten industry segments indicate that DDoS problems…
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…
Cloud Computing is a recent computing model provides consistent access to wide area distributed resources. It revolutionized the IT world with its services provision infrastructure, less maintenance cost, data and service availability…
The paper considers a problem of detecting and mitigating biasing attacks on networks of state observers targeting cooperative state estimation algorithms. The problem is cast within the recently developed framework of distributed…
Mitigating Denial-of-Service (DoS) attacks is vital for online service security and availability. While machine learning (ML) models are used for DoS attack detection, new strategies are needed to enhance their performance. We suggest an…
The progress and integration of intelligent transport systems (ITS) have therefore been central to creating safer and more efficient transport networks. The Internet of Vehicles (IoV) has the potential to improve road safety and provide…
Insider Attack Detection in commercial networks is a critical problem that does not have any good solutions at this current time. The problem is challenging due to the lack of visibility into live networks and a lack of a standard feature…
Deep learning (DL)-based Network Intrusion Detection System (NIDS) has demonstrated great promise in detecting malicious network traffic. However, they face significant security risks due to their vulnerability to adversarial examples…