Related papers: Detecting Distributed Denial of Service Attacks Us…

In the authors' opinion, anomaly detection systems, or ADS, seem to be the most perspective direction in the subject of attack detection, because these systems can detect, among others, the unknown (zero-day) attacks. To detect anomalies,…

Cloud environments face frequent DDoS threats due to centralized resources and broad attack surfaces. Modern cloud-native DDoS attacks further evolve rapidly and often blend multi-vector strategies, creating an operational dilemma:…

With massive data being generated daily and the ever-increasing interconnectivity of the world's Internet infrastructures, a machine learning based intrusion detection system (IDS) has become a vital component to protect our economic and…

Volumetric attacks, which overwhelm the bandwidth of a destination, are among the most common DDoS attacks today. Despite considerable effort made by both research and industry, our recent interviews with over 100 potential DDoS victims in…

More and more industrial devices are connected to IP-based networks, as this is essential for the success of Industry 4.0. However, this interconnection also results in an increased attack surface for various network-based attacks. One of…

The distributed denial of service (DDoS) attack is detrimental to businesses and individuals as people are heavily relying on the Internet. Due to remarkable profits, crackers favor DDoS as cybersecurity weapons to attack a victim. Even…

This research investigates the impact of Denial of Service (DoS) attacks, specifically Internet Control Message Protocol (ICMP) flood attacks, on Autonomous Driving (AD) systems, focusing on their control modules. Two experimental setups…

Distributed machine learning algorithms play a significant role in processing massive data sets over large networks. However, the increasing reliance on machine learning on information and communication technologies (ICTs) makes it…

Increasing interest in the adoption of cloud computing has exposed it to cyber-attacks. One of such is distributed denial of service (DDoS) attack that targets cloud bandwidth, services and resources to make it unavailable to both the cloud…

DDoS attacks are increasingly used by `hackers' and `hacktivists' for various purposes. A number of on-line tools are available to launch an attack of significant intensity. These attacks lead to a variety of losses at the victim's end. We…

The development and implementation of Internet of Things (IoT) devices have been accelerated dramatically in recent years. As a result, a super-network is required to handle the massive volumes of data collected and transmitted to these…

The Internet Threat Monitoring (ITM) is an efficient monitoring system used globally to measure, detect, characterize and track threats such as denial of service (DoS) and distributed Denial of Service (DDoS) attacks and worms. . To block…

Distributed intrustion detection systems detect attacks on computer systems by analyzing data aggregated from distributed sources. The distributed nature of the data sources allows patterns in the data to be seen that might not be…

DDoS attacks have become a major threat to the security of IoT devices and can cause severe damage to the network infrastructure. IoT devices suffer from the inherent problem of resource constraints and are therefore susceptible to such…

The Tor network offers network anonymity to its users by routing their traffic through a sequence of relays. A group of nine directory authorities maintains information about all available relay nodes using a distributed directory protocol.…

IoT devices have become popular targets for various network attacks due to their lack of industry-wide security standards. In this work, we focus on smart home IoT device identification and defending them against Distributed Denial of…

This paper deals with denial of service attack. Overview of the existing attacks and methods is proposed. Classification scheme is presented for a different denial of service attacks. There is considered agent-based intrusion detection…

It is important to be able to detect and classify malicious network traffic flows such as DDoS attacks from benign flows. Normally the task is performed by using supervised classification algorithms. In this paper we analyze the usage 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…

One of the most significant threats faced by enterprise networks today is from Bots. A Bot is a program that operates as an agent for a user and runs automated tasks over the internet, at a much higher rate than would be possible for a…