945 resultados para low-rate distributed denial of service (DDoS) attack


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A new niche of densely populated, unprotected networks is becoming more prevalent in public areas such as Shopping Malls, defined here as independent open-access networks, which have attributes that make attack detection more challenging than in typical enterprise networks. To address these challenges, new detection systems which do not rely on knowledge of internal device state are investigated here. This paper shows that this lack of state information requires an additional metric (The exchange timeout window) for detection of WLAN Denial of Service Probe Flood attacks. Variability in this metric has a significant influence on the ability of a detection system to reliably detect the presence of attacks. A parameter selection method is proposed which is shown to provide reliability and repeatability in attack detection in WLANs. Results obtained from ongoing live trials are presented that demonstrate the importance of accurately estimating probe request and probe response timeouts in future Independent Intrusion Detection Systems.

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We report, for the first time, extensive biologically-mediated phosphate removal from wastewater during high-rate anaerobic digestion (AD). A hybrid sludge bed/fixed-film (packed pumice stone) reactor was employed for low-temperature (12°C) anaerobic treatment of synthetic sewage wastewater. Successful phosphate removal from the wastewater (up to 78% of influent phosphate) was observed, mediated by biofilms in the reactor. Scanning electron microscopy and energy dispersive X-ray analysis revealed the accumulation of elemental phosphorus (~2%) within the sludge bed and fixed-film biofilms. 4’, 6-diamidino-2-phenylindole (DAPI) staining indicated phosphorus accumulation was biological in nature and mediated through the formation of intracellular inorganic polyphosphate (polyP) granules within these biofilms. DAPI staining further indicated that polyP accumulation was rarely associated with free cells. Efficient and consistent chemical oxygen demand (COD) removal was recorded, throughout the 732-day trial, at applied organic loading rates between 0.4-1.5 kg COD m-3 d-1 and hydraulic retention times of 8-24 hours, while phosphate removal efficiency ranged from 28-78% on average per phase. Analysis of protein hydrolysis kinetics and the methanogenic activity profiles of the biomass revealed the development, at 12˚C, of active hydrolytic and methanogenic populations. Temporal microbial changes were monitored using Illumina Miseq analysis of bacterial and archaeal 16S rRNA gene sequences. The dominant bacterial phyla present in the biomass at the conclusion of the trial were the Proteobacteria and Firmicutes and the dominant archaeal genus was Methanosaeta. Trichococcus and Flavobacterium populations, previously associated with low temperature protein degradation, developed in the reactor biomass. The presence of previously characterised polyphosphate accumulating organisms (PAOs) such as Rhodocyclus, Chromatiales, Actinobacter and Acinetobacter was recorded at low numbers. However, it is unknown as yet if these were responsible for the luxury polyP uptake observed in this system. The possibility of efficient phosphate removal and recovery from wastewater during AD would represent a major advance in the scope for widespread application of anaerobic wastewater treatment technologies.

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The scarcity and diversity of resources among the devices of heterogeneous computing environments may affect their ability to perform services with specific Quality of Service constraints, particularly in dynamic distributed environments where the characteristics of the computational load cannot always be predicted in advance. Our work addresses this problem by allowing resource constrained devices to cooperate with more powerful neighbour nodes, opportunistically taking advantage of global distributed resources and processing power. Rather than assuming that the dynamic configuration of this cooperative service executes until it computes its optimal output, the paper proposes an anytime approach that has the ability to tradeoff deliberation time for the quality of the solution. Extensive simulations demonstrate that the proposed anytime algorithms are able to quickly find a good initial solution and effectively optimise the rate at which the quality of the current solution improves at each iteration, with an overhead that can be considered negligible.

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This paper proposes a practical approach to the enhancement of Quality of Service (QoS) routing by means of providing alternative or repair paths in the event of a breakage of a working path. The proposed scheme guarantees that every Protected Node (PN) is connected to a multi-repair path such that no further failure or breakage of single or double repair paths can cause any simultaneous loss of connectivity between an ingress node and an egress node. Links to be protected in an MPLS network are predefined and a Label Switched path (LSP) request involves the establishment of a working path. The use of multi-protection paths permits the formation of numerous protection paths allowing greater flexibility. Our analysis examined several methods including single, double and multi-repair routes and the prioritization of signals along the protected paths to improve the Quality of Service (QoS), throughput, reduce the cost of the protection path placement, delay, congestion and collision. Results obtained indicated that creating multi-repair paths and prioritizing packets reduces delay and increases throughput in which case the delays at the ingress/egress LSPs were low compared to when the signals had not been classified. Therefore the proposed scheme provided a means to improve the QoS in path restoration in MPLS using available network resources. Prioritizing the packets in the data plane has revealed that the amount of traffic transmitted using a medium and low priority Label Switch Paths (LSPs) does not have any impact on the explicit rate of the high priority LSP in which case the problem of a knock-on effect is eliminated.

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The p-median problem is often used to locate p service centers by minimizing their distances to a geographically distributed demand (n). The optimal locations are sensitive to geographical context such as road network and demand points especially when they are asymmetrically distributed in the plane. Most studies focus on evaluating performances of the p-median model when p and n vary. To our knowledge this is not a very well-studied problem when the road network is alternated especially when it is applied in a real world context. The aim in this study is to analyze how the optimal location solutions vary, using the p-median model, when the density in the road network is alternated. The investigation is conducted by the means of a case study in a region in Sweden with an asymmetrically distributed population (15,000 weighted demand points), Dalecarlia. To locate 5 to 50 service centers we use the national transport administrations official road network (NVDB). The road network consists of 1.5 million nodes. To find the optimal location we start with 500 candidate nodes in the network and increase the number of candidate nodes in steps up to 67,000. To find the optimal solution we use a simulated annealing algorithm with adaptive tuning of the temperature. The results show that there is a limited improvement in the optimal solutions when nodes in the road network increase and p is low. When p is high the improvements are larger. The results also show that choice of the best network depends on p. The larger p the larger density of the network is needed. 

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A good intrusion system gives an accurate and efficient classification results. This ability is an essential functionality to build an intrusion detection system. In this paper, we focused on using various training functions with feature selection to achieve high accurate results. The data we used in our experiments are NSL-KDD. However, the training and testing time to build the model is very high. To address this, we proposed feature selection based on information gain, which can detect several attack types with high accurate result and low false rate. Moreover, we executed experiments to category each of the five classes (probe, denial of service (DoS), user to super-user (U2R), and remote to local (R2L), normal). Our proposed outperform other state-of-art methods.

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 Security is a major challenge in Opportunistic Networks (OppNets) due to its characteristics of being an open medium with dynamic topology, there is neither a centralized management nor clear lines of defence. A packet dropping attack is one of the major security threats in OppNets as neither source nodes nor destination nodes have any knowledge of when or where a packet will be dropped. In this paper, we present a novel attack and detection mechanism against a special type of packet dropping where the malicious node drops one packet or more and injects a new fake packet instead. Our novel detection mechanism is very powerful and has very high accuracy. It relies on a very simple yet powerful idea; the creation time of each packet. Significant results show this robust mechanism achieves a very high accuracy and detection rate.

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Security is a major challenge in Opportunistic Networks (OppNets) because of its characteristics, such as open medium, dynamic topology, no centralized management and absent clear lines of defense. A packet dropping attack is one of the major security threats in OppNets since neither source nodes nor destination nodes have the knowledge of where or when the packet will be dropped. In our previous novel attack (Packet Faking Attack [1]) we presented a special type of packet dropping where the malicious node drops one or more packets and then injects new fake packets instead. In this paper, we present an efficient detection mechanism against this type of attack where each node can detect the attack instead of the destination node. Our detection mechanism is very powerful and has very high accuracy. It relies on a very simple yet powerful idea, that is, the packet creation time of each packet. Simulation results show this robust mechanism achieves a very high accuracy, detection rate and good network traffic reduction.

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Security is a major challenge in Opportunistic Networks (OppNets) because of its characteristics, such as open medium, dynamic topology, no centralized management and absent clear lines of defense.A packet dropping attack is one of the major security threats in OppNets since neither source nodes nor destination nodes have the knowledge of where or when the packet will be dropped. In this paper, we present a novel attack and traceback mechanism against a special type of packet dropping where the malicious node drops one or more packets and then injects new fake packets instead. We call this novel attack a Catabolism Attack and we call our novel traceback mechanism against this attack Anabolism Defense. Our novel detection and traceback mechanism is very powerful and has very high accuracy. Each node can detect and then traceback the malicious nodes based on a solid and powerful idea that is, hash chain techniques. In our defense techniques we have two stages. The first stage is to detect the attack, and the second stage is to find the malicious nodes. Simulation results show this robust mechanism achieves a very high accuracy and detection rate.

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Introduction: Many experimental models using lung lavage have been developed for the study of acute respiratory distress syndrome (ARDS). The original technique has been modified by many authors, resulting in difficulties with reproducibility. There is insufficient detail on the lung injury models used, including hemodynamic stability during animal preparation and drawbacks encountered such as mortality. The authors studied the effects of the pulmonary recruitment and the use of fixed tidal volume (Vt) or fixed inspiratory pressure in the experimental ARDS model installation. Methods: Adult rabbits were submitted to repeated lung lavages with 30 ml/kg warm saline until the ARDS definition (PaO2/FiO(2) <= 100) was reached. The animals were divided into three groups, according to the technique used for mechanical ventilation: 1) fixed Vt of 10 ml/kg; 2) fixed inspiratory pressure (IP) with a tidal volume of 10 ml/kg prior to the first lung lavage; and 3) fixed Vt of 10 ml/kg with pulmonary recruitment before the first lavage. Results: The use of alveolar recruitment maneuvers, and the use of a fixed Vt or IP between the lung lavages did not change the number of lung lavages necessary to obtain the experimental model of ARDS or the hemodynamic stability of the animals during the procedure. A trend was observed toward an increased mortality rate with the recruitment maneuver and with the use of a fixed IP. Discussion: There were no differences between the three study groups, with no disadvantage in method of lung recruitment, either fixed tidal volume or fixed inspiratory pressure, regarding the number of lung lavages necessary to obtain the ARDS animal model. Furthermore, the three different procedures resulted in good hemodynamic stability of the animals, and low mortality rate. (C) 2012 Elsevier Inc. All rights reserved.

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The wide diffusion of cheap, small, and portable sensors integrated in an unprecedented large variety of devices and the availability of almost ubiquitous Internet connectivity make it possible to collect an unprecedented amount of real time information about the environment we live in. These data streams, if properly and timely analyzed, can be exploited to build new intelligent and pervasive services that have the potential of improving people's quality of life in a variety of cross concerning domains such as entertainment, health-care, or energy management. The large heterogeneity of application domains, however, calls for a middleware-level infrastructure that can effectively support their different quality requirements. In this thesis we study the challenges related to the provisioning of differentiated quality-of-service (QoS) during the processing of data streams produced in pervasive environments. We analyze the trade-offs between guaranteed quality, cost, and scalability in streams distribution and processing by surveying existing state-of-the-art solutions and identifying and exploring their weaknesses. We propose an original model for QoS-centric distributed stream processing in data centers and we present Quasit, its prototype implementation offering a scalable and extensible platform that can be used by researchers to implement and validate novel QoS-enforcement mechanisms. To support our study, we also explore an original class of weaker quality guarantees that can reduce costs when application semantics do not require strict quality enforcement. We validate the effectiveness of this idea in a practical use-case scenario that investigates partial fault-tolerance policies in stream processing by performing a large experimental study on the prototype of our novel LAAR dynamic replication technique. Our modeling, prototyping, and experimental work demonstrates that, by providing data distribution and processing middleware with application-level knowledge of the different quality requirements associated to different pervasive data flows, it is possible to improve system scalability while reducing costs.

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Elevated rates of methicillin-resistant Staphylococcus aureus (MRSA) carriage have been reported in veterinary personnel, suggesting an occupational colonization risk. Hong Kong veterinary personnel (n = 150) were sampled for coagulase-positive staphylococci (CPS) nasal colonization. Risk factors for colonization were assessed by questionnaire. Isolates were identified and antibiotic susceptibility determined. All CPS isolates were investigated for mecA carriage, SCCmec type and PVL genes. Two subjects were colonized with methicillin-resistant CPS: one with MRSA (spa type t002 (CC5), SCCmec type II) and one with methicillin-resistant Staphylococcus pseudintermedius (MRSP) (MLST type ST71, SCCmec type II-III). MLST type ST71 S. pseudintermedius strain is the predominant MRSP clone circulating in dogs in Europe and in Hong Kong. The low MR-CPS colonization rate may be associated with low levels of large animal exposure or low rates of MRSA colonization of companion animals in Hong Kong. Colonization with non-aureus CPS, which may cause human infection, must also be considered in veterinary personnel.

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Models are an effective tool for systems and software design. They allow software architects to abstract from the non-relevant details. Those qualities are also useful for the technical management of networks, systems and software, such as those that compose service oriented architectures. Models can provide a set of well-defined abstractions over the distributed heterogeneous service infrastructure that enable its automated management. We propose to use the managed system as a source of dynamically generated runtime models, and decompose management processes into a composition of model transformations. We have created an autonomic service deployment and configuration architecture that obtains, analyzes, and transforms system models to apply the required actions, while being oblivious to the low-level details. An instrumentation layer automatically builds these models and interprets the planned management actions to the system. We illustrate these concepts with a distributed service update operation.

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"This report is submitted in compliance with section 16-106 of the Electric Customer Choice and Rate Relief Law of 1997."