Related papers: Predict And Prevent DDOS Attacks Using Machine Lea…

Current backdoor defense methods are evaluated against a single attack at a time. This is unrealistic, as powerful machine learning systems are trained on large datasets scraped from the internet, which may be attacked multiple times by one…

DoS and DDoS attacks have been growing in size and number over the last decade and existing solutions to mitigate these attacks are in general inefficient. Compared to other types of malicious cyber attacks, DoS and DDoS attacks are…

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…

Software-Defined Networking (SDN) provides flexible and programmable network management; however, its centralized control architecture remains highly vulnerable to Distributed Denial-of-Service (DDoS) attacks, particularly Carpet-Bombing…

Volumetric distributed Denial-of-Service (DDoS) attacks have become one of the most significant threats to modern telecommunication networks. However, most existing defense systems require that detection software operates from a centralized…

Distributed machine learning algorithms that employ Deep Neural Networks (DNNs) are widely used in Industry 4.0 applications, such as smart manufacturing. The layers of a DNN can be mapped onto different nodes located in the cloud, edge and…

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…

In this paper, we analyze existing feature selection methods to identify the key elements of network traffic data that allow intrusion detection. In addition, we propose a new feature selection method that addresses the challenge of…

In this paper, we consider the resilient multi-dimensional consensus and distributed optimization problems of multi-agent systems (MASs) in the presence of both agent-based and denial-of-service (DoS) attacks. The considered agent-based…

With the increasing amount of reliance on digital data and computer networks by corporations and the public in general, the occurrence of cyber attacks has become a great threat to the normal functioning of our society. Intrusion detection…

Corporate mail services are designed to perform better than public mail services. Fast mail delivery, large size file transfer as an attachments, high level spam and virus protection, commercial advertisement free environment are some of…

Cloud computing relies on sharing computing resources rather than having local servers or personal devices to handle applications. Nowadays, cloud computing has become one of the fastest growing fields in information technology. However,…

Modern DDoS defense systems rely on probabilistic monitoring algorithms to identify flows that exceed a volume threshold and should thus be penalized. Commonly, classic sketch algorithms are considered sufficiently accurate for usage in…

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…

Network intrusion detection is the process of identifying malicious behaviors that target a network and its resources. Current systems implementing intrusion detection processes observe traffic at several data collecting points in the…

The integration of communication networks and the Internet of Things (IoT) in Industrial Control Systems (ICSs) increases their vulnerability towards cyber-attacks, causing devastating outcomes. Traditional Intrusion Detection Systems…

Distributed Denial of Service (DDoS) attacks form a serious threat to the security of Internet services. However, despite over a decade of research, and the existence of several proposals to address this problem, there has been little…

IoT devices are known to be vulnerable to various cyber-attacks, such as data exfiltration and the execution of flooding attacks as part of a DDoS attack. When it comes to detecting such attacks using network traffic analysis, it has been…

With the growing realization that current Internet protocols are reaching the limits of their senescence, a number of on-going research efforts aim to design potential next-generation Internet architectures. Although they vary in maturity…

As network attacks have increased in number and severity over the past few years, intrusion detection system (IDS) is increasingly becoming a critical component to secure the network. Due to large volumes of security audit data as well as…