887 resultados para DDoS attack defense


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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.

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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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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.

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Recent advances in electronic and computer technologies lead to wide-spread deployment of wireless sensor networks (WSNs). WSNs have wide range applications, including military sensing and tracking, environment monitoring, smart environments, etc. Many WSNs have mission-critical tasks, such as military applications. Thus, the security issues in WSNs are kept in the foreground among research areas. Compared with other wireless networks, such as ad hoc, and cellular networks, security in WSNs is more complicated due to the constrained capabilities of sensor nodes and the properties of the deployment, such as large scale, hostile environment, etc. Security issues mainly come from attacks. In general, the attacks in WSNs can be classified as external attacks and internal attacks. In an external attack, the attacking node is not an authorized participant of the sensor network. Cryptography and other security methods can prevent some of external attacks. However, node compromise, the major and unique problem that leads to internal attacks, will eliminate all the efforts to prevent attacks. Knowing the probability of node compromise will help systems to detect and defend against it. Although there are some approaches that can be used to detect and defend against node compromise, few of them have the ability to estimate the probability of node compromise. Hence, we develop basic uniform, basic gradient, intelligent uniform and intelligent gradient models for node compromise distribution in order to adapt to different application environments by using probability theory. These models allow systems to estimate the probability of node compromise. Applying these models in system security designs can improve system security and decrease the overheads nearly in every security area. Moreover, based on these models, we design a novel secure routing algorithm to defend against the routing security issue that comes from the nodes that have already been compromised but have not been detected by the node compromise detecting mechanism. The routing paths in our algorithm detour those nodes which have already been detected as compromised nodes or have larger probabilities of being compromised. Simulation results show that our algorithm is effective to protect routing paths from node compromise whether detected or not.

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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.

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In this work we introduce a new mathematical tool for optimization of routes, topology design, and energy efficiency in wireless sensor networks. We introduce a vector field formulation that models communication in the network, and routing is performed in the direction of this vector field at every location of the network. The magnitude of the vector field at every location represents the density of amount of data that is being transited through that location. We define the total communication cost in the network as the integral of a quadratic form of the vector field over the network area. With the above formulation, we introduce a mathematical machinery based on partial differential equations very similar to the Maxwell's equations in electrostatic theory. We show that in order to minimize the cost, the routes should be found based on the solution of these partial differential equations. In our formulation, the sensors are sources of information, and they are similar to the positive charges in electrostatics, the destinations are sinks of information and they are similar to negative charges, and the network is similar to a non-homogeneous dielectric media with variable dielectric constant (or permittivity coefficient). In one of the applications of our mathematical model based on the vector fields, we offer a scheme for energy efficient routing. Our routing scheme is based on changing the permittivity coefficient to a higher value in the places of the network where nodes have high residual energy, and setting it to a low value in the places of the network where the nodes do not have much energy left. Our simulations show that our method gives a significant increase in the network life compared to the shortest path and weighted shortest path schemes. Our initial focus is on the case where there is only one destination in the network, and later we extend our approach to the case where there are multiple destinations in the network. In the case of having multiple destinations, we need to partition the network into several areas known as regions of attraction of the destinations. Each destination is responsible for collecting all messages being generated in its region of attraction. The complexity of the optimization problem in this case is how to define regions of attraction for the destinations and how much communication load to assign to each destination to optimize the performance of the network. We use our vector field model to solve the optimization problem for this case. We define a vector field, which is conservative, and hence it can be written as the gradient of a scalar field (also known as a potential field). Then we show that in the optimal assignment of the communication load of the network to the destinations, the value of that potential field should be equal at the locations of all the destinations. Another application of our vector field model is to find the optimal locations of the destinations in the network. We show that the vector field gives the gradient of the cost function with respect to the locations of the destinations. Based on this fact, we suggest an algorithm to be applied during the design phase of a network to relocate the destinations for reducing the communication cost function. The performance of our proposed schemes is confirmed by several examples and simulation experiments. In another part of this work we focus on the notions of responsiveness and conformance of TCP traffic in communication networks. We introduce the notion of responsiveness for TCP aggregates and define it as the degree to which a TCP aggregate reduces its sending rate to the network as a response to packet drops. We define metrics that describe the responsiveness of TCP aggregates, and suggest two methods for determining the values of these quantities. The first method is based on a test in which we drop a few packets from the aggregate intentionally and measure the resulting rate decrease of that aggregate. This kind of test is not robust to multiple simultaneous tests performed at different routers. We make the test robust to multiple simultaneous tests by using ideas from the CDMA approach to multiple access channels in communication theory. Based on this approach, we introduce tests of responsiveness for aggregates, and call it CDMA based Aggregate Perturbation Method (CAPM). We use CAPM to perform congestion control. A distinguishing feature of our congestion control scheme is that it maintains a degree of fairness among different aggregates. In the next step we modify CAPM to offer methods for estimating the proportion of an aggregate of TCP traffic that does not conform to protocol specifications, and hence may belong to a DDoS attack. Our methods work by intentionally perturbing the aggregate by dropping a very small number of packets from it and observing the response of the aggregate. We offer two methods for conformance testing. In the first method, we apply the perturbation tests to SYN packets being sent at the start of the TCP 3-way handshake, and we use the fact that the rate of ACK packets being exchanged in the handshake should follow the rate of perturbations. In the second method, we apply the perturbation tests to the TCP data packets and use the fact that the rate of retransmitted data packets should follow the rate of perturbations. In both methods, we use signature based perturbations, which means packet drops are performed with a rate given by a function of time. We use analogy of our problem with multiple access communication to find signatures. Specifically, we assign orthogonal CDMA based signatures to different routers in a distributed implementation of our methods. As a result of orthogonality, the performance does not degrade because of cross interference made by simultaneously testing routers. We have shown efficacy of our methods through mathematical analysis and extensive simulation experiments.

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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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The study was carried out at the UNESP Rio Claro campus (SP), where biotests consisting of simulated ant attacks were performed in colonies of Mischocyttarus cerberus. The behaviors of the wasps were recorded with a camcorder, for further analysis. This analysis was done using the Mann-Whitney U test and the Principal Component Analysis. In the pre-emergence development stage, colonies with a single foundress defend the nest only after the first larvae appear. When there are only eggs in the nest, the wasp abandons the nest. Before leaving, the wasp rubs its gaster against the nest, releasing the ant repellent secretion. When the nest contains larvae or larvae and pupae, the foundress defends the colony, vibrating its wings, pumping her abdomen and biting the ant.

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Fatty acid derivatives are of central importance for plant immunity against insect herbivores; however, majorregulatory genes and the signals that modulate these defense metabolites are vastly understudied, especiallyin important agro-economic monocot species. Here we show that products and signals derived from a singleZea mays (maize) lipoxygenase (LOX), ZmLOX10, are critical for both direct and indirect defenses to herbiv-ory. We provide genetic evidence that two 13-LOXs, ZmLOX10 and ZmLOX8, specialize in providing substratefor the green leaf volatile (GLV) and jasmonate (JA) biosynthesis pathways, respectively. Supporting the spe-cialization of these LOX isoforms, LOX8 and LOX10 are localized to two distinct cellular compartments, indi-cating that the JA and GLV biosynthesis pathways are physically separated in maize. Reduced expression ofJA biosynthesis genes and diminished levels of JA in lox10 mutants indicate that LOX10-derived signaling isrequired for LOX8-mediated JA. The possible role of GLVs in JA signaling is supported by their ability to par-tially restore wound-induced JA levels in lox10 mutants. The impaired ability of lox10 mutants to produceGLVs and JA led to dramatic reductions in herbivore-induced plant volatiles (HIPVs) and attractiveness toparasitoid wasps. Because LOX10 is under circadian rhythm regulation, this study provides a mechanistic linkto the diurnal regulation of GLVs and HIPVs. GLV-, JA- and HIPV-deficient lox10 mutants display compro-mised resistance to insect feeding, both under laboratory and field conditions, which is strong evidence thatLOX10-dependent metabolites confer immunity against insect attack. Hence, this comprehensive gene toagro-ecosystem study reveals the broad implications of a single LOX isoform in herbivore defense.

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Mode of access: Internet.

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Division 1 "prepared under Subcontract 669-1 with Stanford Research Institute [by] Lehigh University, the Institute of Research."

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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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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.