855 research outputs found

    CloneSpot: Fast detection of Android repackages

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    Repackaging of applications is one of the key attack vectors for mobile malware. This is particularly easy and popular in Android Markets, where applications can be downloaded, decompiled, modified and re-uploaded at a very low cost. Detecting clones and victims is often a hard task, especially in markets with several million of applications to analyze, such as Google Play Store. This work proposes CloneSpot, a novel methodology to efficiently detect Repackaged versions of Android apps using Min-Hashing techniques applied to applications’ meta-data publicly available at Google Play. We validate our approach by analyzing 1.3 Million of applications collected from Google Play in September 2017, from which around 420K are detected as potential repackaged or victim versions of other applications.The authors would like to acknowledge the support of the national project TEXEO (TEC2016-80339-R), funded by the Ministerio de Economia y Competitividad of SPAIN and the EU-funded project SMOOTH (Grant no. H2020-786741). In addition, Ignacio Martin would like to acknowledge the support of the Spanish Ministry of Education by means of the FPU grant he holds (FPU15/03518)

    Conflictos

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    Las disputas por el agua , podrían agravarse en aquellas zonas con alto crecimiento demográfico y densidad poblacional. en tal sentido, la Organización Mundial de la Salud (OMS) en su informe correspondiente al año 2010 reportó la muerte de cinco millones de personas a causa de enfermedades hidrotransmitidas y severamente sobre-explotados (CONAGUA, 2010).en el mundo, los conflictos por la administración; abastecimiento, consumo, reutilización y reciclaje de agua se han concentrado en África, Europa y América (Aquastat, 2010). En el norte del continente americano, los conflictos se han intensificado en la frontera entre México y Estados Unidos de América dada la situación de escasez y sequias prolongadas registradas en los últimos 25 años (ONU, 2010).Universidad Autónoma del Estado de México, Unidad Académica Profesional Chimalhuacá

    Using transparent WDM metro rings to provide an out-of-band control network for OpenFlow in MAN

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    OpenFlow is a protocol that enables networks to evolve and change flexibly, by giving a remote controller the capability of modifying the behavior of network devices. In an OpenFlow network, each device needs to maintain a dedicated and separated connection with a remote controller. All these connections can be described as the OpenFlow control network, that is the data network which transports control plane information, and can be deployed together with the data infrastructure plane (in-band) or separated (out-of-band), with advantages and disadvantages in both cases. The control network is a critical subsystem since the communication with the controller must be reliable and ideally should be protected against failures. This paper proposes a novel ring architecture to efficiently transport both the data plane and an out-of-band control network.The authors would like to acknowledge the support of the Spanish projects CRAMnet (grant no. TEC2012-38362-C03-01) and FIERRO (grant no. TEC2010-12250-E) to the development of this work

    Fronthaul network modeling and dimensioning meeting ultra-low latency requirements for 5G

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    Enabling the transport of fronthaul traffic in next-generation cellular networks [fifth-generation (5G)] following the cloud radio access network (C-RAN) architecture requires a redesign of the fronthaul network featuring high capacity and ultra-low latency. With the aim of leveraging statistical multiplexing gains, infrastructure reuse, and, ultimately, cost reduction, the research community is focusing on Ethernet-based packet-switch networks. To this end, we propose using the high queuing delay percentiles of the G/G/1 queuing model as the key metric in fronthaul network dimensioning. Simulations reveal that Kingman's exponential law of congestion provides accurate estimates on such delays for the particular case of aggregating a number of evolved Common Public Radio Interface fronthaul flows, namely functional splits Iu and IID. We conclude that conventional 10 G, 40 G, and 100 G transponders can cope with multiple legacy 10-20 MHz radio channels with worst-case delay guarantees. Conversely, scaling to 40 and 100 MHz channels will require the introduction of 200G, 400G, and even 1T high-speed transponders.The authors would like to acknowledge the support of the Spanish project TEXEO (grant no. TEC2016-80339-R), and the H2020 EU-funded project BlueSPACE (grant no. 762055)

    Network Planning for Dual Residential-Business Exploitation of Next-Generation Passive Optical Networks to Provide Symmetrical 1 Gb/s Services

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    Demand for high-speed access for business and residential subscribers has grown rapidly in recent years; thus, service providers need to offer cost-effective solutions to cover this demand. Convergence within the same infrastructure for clients requiring different service levels may have benefits in terms of cost, but their respective service-level specifications need to be guaranteed. This article compares different flavors of next-generation passive optical networks (PONs), namely, gigabit PON (GPON), 10-gigabit PON (XG-PON), time and wavelength division multiplexing PON (TWDM-PON), and wavelength division multiplexing PON (WDM-PON), and evaluates which one can provide 1 Gb/s symmetrical service at the more affordable cost when there is a mix of residential and business subscribers. Results show that the recommended technology depends on the percentage of business subscribers in the scenario.The authors would like to acknowledge the support of the Spanish projects CRAMnet (grant no. TEC2012-38362-C03-01), Elastic Networks (grant no. TEC2015-71932-REDT), TIGRE-5CM (grant no. S2013/ICE-2919), and Fed4FIRE EU Project 318389 for the development of this work. The views expressed in this article are those of the authors and do not reflect the opinion of the authors’ employers, specifically in terms of architectural and engineering design or experience.European Community's Seventh Framework Progra

    Troubleshooting PON networks effectively with carrier-grade ethernet and WDM-PON

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    WDM-PONs have recently emerged to provide dedicated and separated point-to-point wavelengths to individual optical network units. In addition, the recently standardized Ethernet OAM capabilities under the IEEE 802.1ag standard and ITU-T Recommendation Y.1731, together with state-of-the-art optical timedomain reflectometry provide new link-layer and physical tools for the effective troubleshooting of WDM-PONs. This article proposes an integrated troubleshooting box (ITB) for the effective combination of both physical and link-layer information into an effective and efficient set of management procedures for WDM-PONs. We show its applicability in a number of realistic troubleshooting scenarios, including failure situations involving either the feeder fiber, one of its branches, or even Ethernet links after the ONU.The authors would like to acknowledge the support of the CRAMnet project, funded by the Spanish government under grant no. TEC2012-38362-C03-01, to the development of this work. Also, the authors would like to thank Mr. Russ Jones from Ericsson-LG for his valuable support, especially concerning the laboratory trial setup of an earlier section

    On the effect of sudden data bursts in the upstream channel of Ethernet PONs employing IPACT under the gated-service discipline

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    The Interleaved Polling with Adapted Cycle Times (IPACT) algorithm for dynamic bandwidth allocation proposed for Ethernet Passive Optical Networks (EPONs) has been deeply analysed in the literature under Poisson traffic. However, the case when ONUs suddenly offer bursty traffic in the upstream channel of a PON has not been considered in such detail.This paper studies the performance behaviour of the upstream channel of EPONs employing IPACT with the gated-service disciple, under Poisson traffic together with sudden bursts. We show that one burst arrival produces a peak in the average transmission window of every ONU, lasting its effects for several cycle times, depending on the burst size and the average network load. Such a burst has a direct impact on the delay experienced by the packets of other ONUs. This is mathematically modelled using a modification of the formerly studied M/G/1 queue with vacations and validated with simulation.The authors would like to thank the reviewers for their valuable comments through the reviewing process of this paper. The authors would also like to acknowledge the Spanish-funded CRAMnet (Grant no. TEC2012-38362-C03-01) and the Madrid Community MEDIANET (S2009-TIC1468) projects for their support to this work

    Optimizing Learned Bloom Filters: How Much Should Be Learned?

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    The learned Bloom filter (LBF) combines a machine learning model (learner) with a traditional Bloom filter to improve the false positive rate (FPR) that can be achieved for a given memory budget. The LBF has recently been generalized by making use of the full spectrum of the learner's prediction score. However, in all those designs, the machine learning model is fixed. In this letter, for the first time, the design of LBFs is proposed and evaluated by considering the machine learning model as one of the variables in the process. In detail, for a given memory budget, several LBFs are constructed using different machine learning models and the one with the lowest FPR is selected. We demonstrate that our approach can achieve much better performance than existing LBF designs providing reductions of the FPR of up to 90% in some settings.This work was supported by the EU H2020 Project PIMCITY under Grant H2020-871370. This manuscript was recommended for publication by A. Kumar

    Voting margin: A scheme for error-tolerant k nearest neighbors classifiers for machine learning

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    Machine learning (ML) techniques such as classifiers are used in many applications, some of which are related to safety or critical systems. In this case, correct processing is a strict requirement and thus ML algorithms (such as for classification) must be error tolerant. A naive approach to implement error tolerant classifiers is to resort to general protection techniques such as modular redundancy. However, modular redundancy incurs in large overheads in many metrics such as hardware utilization and power consumption that may not be acceptable in applications that run on embedded or battery powered systems. Another option is to exploit the algorithmic properties of the classifier to provide protection and error tolerance at a lower cost. This paper explores this approach for a widely used classifier, the k Nearest Neighbors ( k NNs), and proposes an efficient scheme to protect it against errors. The proposed technique is based on a time-based modular redundancy (TBMR) scheme. The proposed scheme exploits the intrinsic redundancy of k NNs to drastically reduce the number of re-computations needed to detect errors. This is achieved by noting that when voting among the k nearest neighbors has a large majority, an error in one of the voters cannot change the result, hence voting margin (VM). This observation has been refined and extended in the proposed VM scheme to also avoid re-computations in some cases in which the majority vote is tight. The VM scheme has been implemented and evaluated with publicly available data sets that cover a wide range of applications and settings. The results show that by exploiting the intrinsic redundancy of the classifier, the proposed scheme is able to reduce the cost compared to modular redundancy by more than 60 percent in all configurations evaluated.Pedro Reviriego and Josée Alberto Hernández would like to acknowledge the support of the TEXEO project TEC2016-80339-R funded by the Spanish Ministry of Economy and Competitivity and of the Madrid Community research project TAPIR-CM Grant no. P2018/TCS-4496
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