Reliable distinguishing DDOS flood traffic from aggregated traffic is desperately desired by reliable prevention of DDOS attacks. By reliable distinguishing, we mean that flood traffic can be distinguished from aggregated one for a predetermined probability. The basis to reliably distinguish flood traffic from aggregated one is reliable detection of signs of DDOS flood attacks. As is known, rel...

A Distributed Denial of Service (DDoS) attack is a major security threat for networks and Internet services. Attackers can generate attack traffic similar to normal network traffic using sophisticated attacking tools. In such a situation, many intrusion detection systems fail to identify DDoS attack in real time. However, DDoS attack traffic behaves differently from legitimate network traffic i...

Distributed Denial of Service attacks (DDoS) overwhelm network resources with useless or harmful packets and prevent normal users from accessing these network resources. These attacks jeopardize the confidentiality, privacy and integrity of information on the internet. Since it is very difficult to set any predefined rules to correctly identify genuine network traffic, an anomaly-based Intrusio...

Although the prevention of Distributed Denial of Service (DDoS) attacks is not possible, detection of such attacks plays main role in preventing their progress. In the flooding attacks, especially new sophisticated DDoS, the attacker floods the network traffic toward the target computer by sending pseudo-normal packets. Therefore, multi-purpose IDSs do not offer a good performance (and accuracy...

Intrusion tolerance is the ability of a system to continue providing (possibly degraded but) adequate services after a penetration. With the rapid development of network technology, distributed denial of service (DDoS) attacks become one of the most important issues today. In this paper, we propose a DDoS ontology to provide a common terminology for describing the DDoS models consisting of the ...

In this poster, we firstly put forward to an effective anomaly detection method based on TCM-KNN (Transductive Confidence Machines for K-Nearest Neighbors) algorithm to fulfill DDoS attacks detection task towards ensuring the QoS of web server. The method is good at detecting network anomalies with high detection rate, high confidence and low false positives than traditional methods, because it...

DDoS attacks temporarily make the target system unavailable to the legitimate users. They don’t steal anything. But they cause big headache for targeted companies and network engineers. Application layer DDoS attacks are difficult to detect because they mimic normal traffic. This paper proposes a novel method of detection of DDoS attacks based on Chaos theory and Artificial neural networks. Key...

Distributed Denials of Service (DDoS) attacks have become the daunting problem for businesses, state administrator and computer system users. Prevention and detection of a DDoS attack is a major research topic for researchers throughout the world. As new remedies are developed to prevent or mitigate DDoS attacks, invaders are continually evolving new methods to circumvent these new procedures. ...

Spoofing source IP addresses is always utilized to perform Distributed Denial-of-Service (DDoS) attacks. Most of current detection and prevention methods against DDoS ignore the innocent side, whose IP is utilized as the spoofed IP by the attacker. In this paper, a novel method has been proposed to against the direct DDoS attacks, which consists of two components: the client detector and the se...

mod_security (an open source intrusion detection and prevention engine for to the Internet, securing your systems against attackers must be a high priority. An Intrusion Detection System against DDOS for MANETs attacks MANET also contains wireless sensor nodes, these highly secure IDS to detect attacks. 2. knowledge from the packet flow and packet details to detect DDOS attacks.