The distributed denial of service attack poses a significant threat to network security. Despite the availability of various methods for detecting DDoS attacks, the challenge remains in creating real-time detectors with minimal computational overhead...
The Hypertext Transfer Protocol (HTTP) is a common target of distributed denial-of-service (DDoS) attacks in today’s cloud computing environment (CCE). However, most existing datasets for Intrusion Detection System (IDS) evaluations are not sui...
The exponential growth of the Internet of Things (IoT) has led to the rapid expansion of interconnected systems, which has also increased the vulnerability of IoT devices to security threats such as distributed denial-of-service (DDoS) attacks. In th...
In recent years, the occurrence and complexity of Distributed Denial of Service (DDoS) attacks have escalated significantly, posing threats to the availability, performance, and security of networked systems. With the rapid progression of Artificial...
The early and accurate detection of Distributed Denial of Service (DDoS) attacks is a fundamental area of research to safeguard the integrity and functionality of organizations’ digital ecosystems. Despite the growing importance of neural netwo...
Imbalanced data is a major challenge in network security applications, particularly in DDoS (Distributed Denial of Service) traffic classification, where detecting minority classes is critical for timely and cost-effective defense. Existing machine l...
Nowadays, the Internet of Things (IoT) concept plays a pivotal role in society and brings new capabilities to different industries. The number of IoT solutions in areas such as transportation and healthcare is increasing and new services are under de...
With the increasing severity and frequency of cyberattacks, the rapid expansion of smart objects intensifies cybersecurity threats. The vast communication traffic data between Internet of Things (IoT) devices presents a considerable challenge in defe...
As the world increasingly becomes more interconnected, the demand for safety and security is ever-increasing, particularly for industrial networks. This has prompted numerous researchers to investigate different methodologies and techniques suitable...
Within our academic high-speed network infrastructure which is used for connecting all universities and high schools in our country to the Internet, there are thousands of cybersecurity attacks occurring every day. That is why, within our SANET II pr...
With the emergence of technology, the usage of IoT (Internet of Things) devices is said to be increasing in people’s lives. Such devices can benefit the average individual, who does not necessarily have to have technical knowledge. The IoT can...
Internet of Things (IoT) security is becoming important with the growing popularity of IoT devices and their wide applications. Recent network security reports revealed a sharp increase in the type, frequency, sophistication, and impact of distribute...
Distributed Denial of Service (DDoS) attacks, advanced persistent threats, and malware actively compromise the availability and security of Internet services. Thus, this paper proposes an intelligent agent system for detecting DDoS attacks using auto...
Aiming at the problems of single detection target of existing distributed denial of service (DDoS) attacks, incomplete detection datasets and privacy caused by shared datasets, we propose a trusted multi-domain DDoS detection method based on federate...
Internet security is a major concern these days due to the increasing demand for information technology (IT)-based platforms and cloud computing. With its expansion, the Internet has been facing various types of attacks. Viruses, denial of service (D...
Software Defined Networking (SDN) offers several advantages such as manageability, scaling, and improved performance. However, SDN involves specific security problems, especially if its controller is defenseless against Distributed Denial of Service...
Application Layer Distributed Denial of Service (DDoS) attacks are very challenging to detect. The shortfall at the application layer allows formation of HTTP DDoS as the request headers are not compulsory to be attached in an HTTP request. Furthermo...
Optimizing the monitoring of network traffic features to detect abnormal traffic is critical. We propose a two-stage monitoring and classification (MOCA) system requiring fewer features to detect and classify malicious network attacks. The first stag...
The software defined network (SDN) collects network traffic data and proactively manages networks. SDN’s programmability makes it excellent for developing distributed applications, cybersecurity, and decentralized network control in multitenant...
DDoS attacks remain a persistent cybersecurity threat, blocking services to legitimate users and causing significant damage to reputation, finances, and potential customers. For the detection of DDoS attacks, machine learning techniques such as super...
Distributed denial of service (DDoS) attacks pose an increasing threat to businesses and government agencies. They harm internet businesses, limit access to information and services, and damage corporate brands. Attackers use application layer DDoS a...
Software-defined networking (SDN) is becoming the standard for the management of networks due to its scalability and flexibility to program the network. SDN provides many advantages but it also involves some specific security problems; for example, t...
Distributed Denial of Service (DDoS) attacks disrupt service availability, leading to significant financial setbacks for individuals and businesses. This paper introduces Eye-Net, a deep learning-based system optimized for DDoS attack detection that...
The great commitment in different areas of computer science for the study of computer networks used to fulfill specific and major business tasks has generated a need for their maintenance and optimal operability. Distributed denial of service (DDoS)...
The increasing threat of Distributed DDoS attacks necessitates robust, big data-driven methods to detect and mitigate complex Network and Transport Layer (NTL) attacks. This paper proposes EffiGRU-GhostNet, a deep-learning ensemble model for high-acc...
In the contemporary landscape, Distributed Denial of Service (DDoS) attacks have emerged as an exceedingly pernicious threat, particularly in the context of network management centered around technologies like Software-Defined Networking (SDN). With...
With the development of the Internet of Things, a huge number of devices are connected to the network, network traffic is exhibiting massive and low latency characteristics. At the same time, it is becoming cheaper and cheaper to launch DDoS attacks,...
The development of 5G environments has several advantages, including accelerated data transfer speeds, reduced latency, and improved energy efficiency. Nevertheless, it also increases the risk of severe cybersecurity issues, including a complex and e...
A typical Software-Defined Vehicular Network (SDVN) is open to various cyberattacks because of its centralized controller-based framework. A cyberattack, such as a Distributed Denial of Service (DDoS) attack, can easily overload the central SDVN cont...
The rapid growth of cloud computing has led to the development of the Software-Defined Network (SDN), which is a network strategy that offers dynamic management and improved performance. However, security threats are a growing concern, particularly w...
The problem of identifying Distributed Denial of Service (DDos) attacks is fundamentally a classification problem in machine learning. In relevance to Cloud Computing, the task of identification of DDoS attacks is a significantly challenging problem...
The distributed denial of service (DDoS) attack is one of the most pernicious threats in cyberspace. Catastrophic failures over the past two decades have resulted in catastrophic and costly disruption of services across all sectors and critical infra...
The 5G networks aim to realize a massive Internet of Things (IoT) environment with low latency. IoT devices with weak security can cause Tbps-level Distributed Denial of Service (DDoS) attacks on 5G mobile networks. Therefore, interest in automatic n...
The modern digitized world is mainly dependent on online services. The availability of online systems continues to be seriously challenged by distributed denial of service (DDoS) attacks. The challenge in mitigating attacks is not limited to identify...
The recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security a...
Software-defined networking (SDN) has emerged in recent years as a form of Internet architecture. Its scalability, dynamics, and programmability simplify the traditional Internet structure. This architecture realizes centralized management by separat...
With the escalating global cyber threats, Distributed Denial of Service (DDoS) attacks have become one of the most disruptive and prevalent network attacks. Traditional DDoS detection systems face significant challenges due to the unpredictable natur...
The rapid growth of cyberattacks necessitates the development of more sophisticated detection techniques. DoS and DDoS are well-known harmful attacks that affect organizations. This paper proposes a proactive, behavior-based DoS and DDoS detection fr...
Software-defined networking (SDN) has reformed the traditional approach to managing and configuring networks by isolating the data plane from control plane. This isolation helps enable centralized control over network resources, enhanced programmabil...
The rapid proliferation of Internet of Things (IoT) devices has significantly increased vulnerability to Distributed Denial of Service (DDoS) attacks, which can severely disrupt network operations. DDoS attacks in IoT networks disrupt communication a...
Distributed denial-of-service (DDoS) attack is one of the major threats to the web server. The rapid increase of DDoS attacks on the Internet has clearly pointed out the limitations in current intrusion detection systems or intrusion prevention syste...
The study in this paper characterizes lightweight IoT networks as being established by devices with few computer resources, such as reduced battery life, processing power, memory, and, more critically, minimal security and protection, which are easil...
In modern network infrastructure, Distributed Denial of Service (DDoS) attacks are considered as severe network security threats. For conventional network security tools it is extremely difficult to distinguish between the higher traffic volume of a...
The smart grid (SG) offers potential benefits for utilities, electric generators, and customers alike. However, the prevalence of cyber-attacks targeting the SG emphasizes its dark side. In particular, distributed denial-of-service (DDoS) attacks can...
In this paper, we investigate the use of Bent functions, particularly the Maiorana–McFarland (M–M) construction, as a nonlinear preprocessing method to enhance machine learning-based detection systems for Distributed Denial of Service (DD...
Distributed Denial of Service (DDoS) attacks are one of the most important cybersecurity problems today since they are one of the biggest threats against network service continuity and accessibility. Increasing network traffic volume combined with he...
In detecting Distributed Denial of Service (DDoS), deep learning faces challenges and difficulties such as high computational demands, long training times, and complex model interpretation. This research focuses on overcoming these challenges by prop...
Distributed Denial-of-Service (DDoS) attacks represent a pervasive and critical threat to autonomous vehicles, jeopardizing their operational functionality and passenger safety. The ease with which these attacks can be launched contrasts sharply with...
Today, the development of the Internet of Things has grown, and the number of related IoT devices has reached the order of tens of billions. Most IoT devices are vulnerable to attacks, especially DdoS (Distributed Denial of Service attack) attacks. D...
This study proposes a machine learning and deep learning framework to detect application layer DDoS attacks using web server access logs. A realistic dataset was generated using eight DDoS tools, along with benign traffic. Multiple ML models, includi...
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