36 resultados para DDoS
Resumo:
This work-in-progress paper presents an ensemble-based model for detecting and mitigating Distributed Denial-of-Service (DDoS) attacks, and its partial implementation. The model utilises network traffic analysis and MIB (Management Information Base) server load analysis features for detecting a wide range of network and application layer DDoS attacks and distinguishing them from Flash Events. The proposed model will be evaluated against realistic synthetic network traffic generated using a software-based traffic generator that we have developed as part of this research. In this paper, we summarise our previous work, highlight the current work being undertaken along with preliminary results obtained and outline the future directions of our work.
Resumo:
Web threats are becoming a major issue for both governments and companies. Generally, web threats increased as much as 600% during last year (WebSense, 2013). This appears to be a significant issue, since many major businesses seem to provide these services. Denial of Service (DoS) attacks are one of the most significant web threats and generally their aim is to waste the resources of the target machine (Mirkovic & Reiher, 2004). Dis-tributed Denial of Service (DDoS) attacks are typically executed from many sources and can result in large traf-fic flows. During last year 11% of DDoS attacks were over 60 Gbps (Prolexic, 2013a). The DDoS attacks are usually performed from the large botnets, which are networks of remotely controlled computers. There is an increasing effort by governments and companies to shut down the botnets (Dittrich, 2012), which has lead the attackers to look for alternative DDoS attack methods. One of the techniques to which attackers are returning to is DDoS amplification attacks. Amplification attacks use intermediate devices called amplifiers in order to amplify the attacker's traffic. This work outlines an evaluation tool and evaluates an amplification attack based on the Trivial File Transfer Proto-col (TFTP). This attack could have amplification factor of approximately 60, which rates highly alongside other researched amplification attacks. This could be a substantial issue globally, due to the fact this protocol is used in approximately 599,600 publicly open TFTP servers. Mitigation methods to this threat have also been consid-ered and a variety of countermeasures are proposed. Effects of this attack on both amplifier and target were analysed based on the proposed metrics. While it has been reported that the breaching of TFTP would be possible (Schultz, 2013), this paper provides a complete methodology for the setup of the attack, and its verification.
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A run through various aspects of Distributed Denial of Service attacks
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A summary timeline by Arbor Networks of how DDoS attacks have evolved.
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An effective Distributed Denial of Service (DDoS) defense mechanism must guarantee legitimate users access to an Internet service masking the effects of possible attacks. That is, it must be able to detect threats and discard malicious packets in a online fashion. Given that emerging data streaming technology can enable such mitigation in an effective manner, in this paper we present STONE, a stream-based DDoS defense framework, which integrates anomaly-based DDoS detection and mitigation with scalable data streaming technology. With STONE, the traffic of potential targets is analyzed via continuous data streaming queries maintaining information used for both attack detection and mitigation. STONE provides minimal degradation of legitimate users traffic during DDoS attacks and it also faces effectively flash crowds. Our preliminary evaluation based on an implemented prototype and conducted with real legitimate and malicious traffic traces shows that STONE is able to provide fast detection and precise mitigation of DDoS attacks leveraging scalable data streaming technology.
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This paper proposes a technique to defeat Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks in Ad Hoc Networks. The technique is divided into two main parts and with game theory and cryptographic puzzles. Introduced first is a new client puzzle to prevent DoS attacks in such networks. The second part presents a multiplayer game that takes place between the nodes of an ad hoc network and based on fundamental principles of game theory. By combining computational problems with puzzles, improvement occurs in the efficiency and latency of the communicating nodes and resistance in DoS and DDoS attacks. Experimental results show the effectiveness of the approach for devices with limited resources and for environments like ad hoc networks where nodes must exchange information quickly.
Resumo:
Denial-of-service attacks (DoS) and distributed denial-of-service attacks (DDoS) attempt to temporarily disrupt users or computer resources to cause service un- availability to legitimate users in the internetworking system. The most common type of DoS attack occurs when adversaries °ood a large amount of bogus data to interfere or disrupt the service on the server. The attack can be either a single-source attack, which originates at only one host, or a multi-source attack, in which multiple hosts coordinate to °ood a large number of packets to the server. Cryptographic mechanisms in authentication schemes are an example ap- proach to help the server to validate malicious tra±c. Since authentication in key establishment protocols requires the veri¯er to spend some resources before successfully detecting the bogus messages, adversaries might be able to exploit this °aw to mount an attack to overwhelm the server resources. The attacker is able to perform this kind of attack because many key establishment protocols incorporate strong authentication at the beginning phase before they can iden- tify the attacks. This is an example of DoS threats in most key establishment protocols because they have been implemented to support con¯dentiality and data integrity, but do not carefully consider other security objectives, such as availability. The main objective of this research is to design denial-of-service resistant mechanisms in key establishment protocols. In particular, we focus on the design of cryptographic protocols related to key establishment protocols that implement client puzzles to protect the server against resource exhaustion attacks. Another objective is to extend formal analysis techniques to include DoS- resistance. Basically, the formal analysis approach is used not only to analyse and verify the security of a cryptographic scheme carefully but also to help in the design stage of new protocols with a high level of security guarantee. In this research, we focus on an analysis technique of Meadows' cost-based framework, and we implement DoS-resistant model using Coloured Petri Nets. Meadows' cost-based framework is directly proposed to assess denial-of-service vulnerabil- ities in the cryptographic protocols using mathematical proof, while Coloured Petri Nets is used to model and verify the communication protocols using inter- active simulations. In addition, Coloured Petri Nets are able to help the protocol designer to clarify and reduce some inconsistency of the protocol speci¯cation. Therefore, the second objective of this research is to explore vulnerabilities in existing DoS-resistant protocols, as well as extend a formal analysis approach to our new framework for improving DoS-resistance and evaluating the performance of the new proposed mechanism. In summary, the speci¯c outcomes of this research include following results; 1. A taxonomy of denial-of-service resistant strategies and techniques used in key establishment protocols; 2. A critical analysis of existing DoS-resistant key exchange and key estab- lishment protocols; 3. An implementation of Meadows's cost-based framework using Coloured Petri Nets for modelling and evaluating DoS-resistant protocols; and 4. A development of new e±cient and practical DoS-resistant mechanisms to improve the resistance to denial-of-service attacks in key establishment protocols.
Resumo:
Distributed Denial of Services DDoS, attacks has become one of the biggest threats for resources over Internet. Purpose of these attacks is to make servers deny from providing services to legitimate users. These attacks are also used for occupying media bandwidth. Currently intrusion detection systems can just detect the attacks but cannot prevent / track the location of intruders. Some schemes also prevent the attacks by simply discarding attack packets, which saves victim from attack, but still network bandwidth is wasted. In our opinion, DDoS requires a distributed solution to save wastage of resources. The paper, presents a system that helps us not only in detecting such attacks but also helps in tracing and blocking (to save the bandwidth as well) the multiple intruders using Intelligent Software Agents. The system gives dynamic response and can be integrated with the existing network defense systems without disturbing existing Internet model. We have implemented an agent based networking monitoring system in this regard.
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High-rate flooding attacks (aka Distributed Denial of Service or DDoS attacks) continue to constitute a pernicious threat within the Internet domain. In this work we demonstrate how using packet source IP addresses coupled with a change-point analysis of the rate of arrival of new IP addresses may be sufficient to detect the onset of a high-rate flooding attack. Importantly, minimizing the number of features to be examined, directly addresses the issue of scalability of the detection process to higher network speeds. Using a proof of concept implementation we have shown how pre-onset IP addresses can be efficiently represented using a bit vector and used to modify a “white list” filter in a firewall as part of the mitigation strategy.
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The Denial of Service Testing Framework (dosTF) being developed as part of the joint India-Australia research project for ‘Protecting Critical Infrastructure from Denial of Service Attacks’ allows for the construction, monitoring and management of emulated Distributed Denial of Service attacks using modest hardware resources. The purpose of the testbed is to study the effectiveness of different DDoS mitigation strategies and to allow for the testing of defense appliances. Experiments are saved and edited in XML as abstract descriptions of an attack/defense strategy that is only mapped to real resources at run-time. It also provides a web-application portal interface that can start, stop and monitor an attack remotely. Rather than monitoring a service under attack indirectly, by observing traffic and general system parameters, monitoring of the target application is performed directly in real time via a customised SNMP agent.
Resumo:
Distributed Denial-of-Service (DDoS) attacks continue to be one of the most pernicious threats to the delivery of services over the Internet. Not only are DDoS attacks present in many guises, they are also continuously evolving as new vulnerabilities are exploited. Hence accurate detection of these attacks still remains a challenging problem and a necessity for ensuring high-end network security. An intrinsic challenge in addressing this problem is to effectively distinguish these Denial-of-Service attacks from similar looking Flash Events (FEs) created by legitimate clients. A considerable overlap between the general characteristics of FEs and DDoS attacks makes it difficult to precisely separate these two classes of Internet activity. In this paper we propose parameters which can be used to explicitly distinguish FEs from DDoS attacks and analyse two real-world publicly available datasets to validate our proposal. Our analysis shows that even though FEs appear very similar to DDoS attacks, there are several subtle dissimilarities which can be exploited to separate these two classes of events.
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A Flash Event (FE) represents a period of time when a web-server experiences a dramatic increase in incoming traffic, either following a newsworthy event that has prompted users to locate and access it, or as a result of redirection from other popular web or social media sites. This usually leads to network congestion and Quality-of-Service (QoS) degradation. These events can be mistaken for Distributed Denial-of-Service (DDoS) attacks aimed at disrupting the server. Accurate detection of FEs and their distinction from DDoS attacks is important, since different actions need to be undertaken by network administrators in these two cases. However, lack of public domain FE datasets hinders research in this area. In this paper we present a detailed study of flash events and classify them into three broad categories. In addition, the paper describes FEs in terms of three key components: the volume of incoming traffic, the related source IP-addresses, and the resources being accessed. We present such a FE model with minimal parameters and use publicly available datasets to analyse and validate our proposed model. The model can be used to generate different types of FE traffic, closely approximating real-world scenarios, in order to facilitate research into distinguishing FEs from DDoS attacks.
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This thesis investigates and develops techniques for accurately detecting Internet-based Distributed Denial-of-Service (DDoS) Attacks where an adversary harnesses the power of thousands of compromised machines to disrupt the normal operations of a Web-service provider, resulting in significant down-time and financial losses. This thesis also develops methods to differentiate these attacks from similar-looking benign surges in web-traffic known as Flash Events (FEs). This thesis also addresses an intrinsic challenge in research associated with DDoS attacks, namely, the extreme scarcity of public domain datasets (due to legal and privacy issues) by developing techniques to realistically emulate DDoS attack and FE traffic.