278,320 research outputs found

    Advanced threat hunting over software-defined networks in smart cities

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    The emergence of Software-Defined Networking (SDN) has brought along a wave of new technologies and developments in the field of networking with hopes of dealing with network resources more efficiently and providing a foundation of programmability. SDN allows for both flexibility and adaptability by separating the control and data planes in a network environment by virtualizing network hardware. Threat hunting is a technique that allows for the detection of advanced network threats through forensic analysis. We present an advanced threat hunting model by combining the SDN infrastructure with threat hunting techniques and machine learning models aiming to intelligently handle advanced network threats such as lateral movement. We found that our approach outperforms current threat hunting models in vital areas such as the detection to mitigation time. Our results show that we are able to detect advanced threats with 93.4% accuracy and begin mitigation within 10 seconds of detection

    Software defined cities: A novel paradigm for smart cities through IoT clouds

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    © 2015 IEEE.A Smart City represents an improvement of today cities that strategically exploits many smart factors to increase the city sustainable growth and strengthen city functions, while ensuring citizen quality of life and health. Cities can be perceived as an ecosystem of "things" which citizens daily interact with: street furniture, public buildings, transportation, monuments, public lighting as well as personal smartphones. Thanks to recent advances in ICT such things can be considered always interconnected also providing sensing and actuating facilities according to the Internet of Things and Cyber Physical Systems models. Creating smart services that exploit such a complex infrastructure is a fundamental and current challenge. To this end, aim of this paper is the design and implementation of the Software Defined Cities approach: a Cloud-based infrastructure that, starting from the well known concept of Software Defined paradigms, is able to transform this complex ecosystem in a simple and "programmable" environment where municipalities, companies, scientists, and citizens can easily collaborate in developing innovative smart services. The overall architecture is presented focusing on both the function virtualization and infrastructure aspects also giving details about the software stacks used (e.g., Open Stack) while a use case is laid out to demonstrate the advantages of the proposed approach

    Software Defined Media: Virtualization of Audio-Visual Services

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    Internet-native audio-visual services are witnessing rapid development. Among these services, object-based audio-visual services are gaining importance. In 2014, we established the Software Defined Media (SDM) consortium to target new research areas and markets involving object-based digital media and Internet-by-design audio-visual environments. In this paper, we introduce the SDM architecture that virtualizes networked audio-visual services along with the development of smart buildings and smart cities using Internet of Things (IoT) devices and smart building facilities. Moreover, we design the SDM architecture as a layered architecture to promote the development of innovative applications on the basis of rapid advancements in software-defined networking (SDN). Then, we implement a prototype system based on the architecture, present the system at an exhibition, and provide it as an SDM API to application developers at hackathons. Various types of applications are developed using the API at these events. An evaluation of SDM API access shows that the prototype SDM platform effectively provides 3D audio reproducibility and interactiveness for SDM applications.Comment: IEEE International Conference on Communications (ICC2017), Paris, France, 21-25 May 201

    Mobility management enhancement in smart cities using software defined networks

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    Achieving sustainability in cities relies on effective mobility management (MM) that serves current and future generations. It involves establishing an inclusive transportation system to address many issues, like traffic congestion, air pollution, and greenhouse gas emissions. Beyond environmental concerns, robust mobility management has social and economic advantages, fostering improved access to vital services like healthcare, education, and employment. Softwaredefined networking (SDN) presents a viable solution for enhancing MM within networks. Unlike traditional setups, SDN merges MM through a programmable control plane, streamlining network configurations and enabling features like handover, load balancing, and quality of service (QoS). The utilization of SDN technology extends to various facets of sustainable city networks, encompassing areas like network security, performance optimization, big data processing, energy efficiency, emergency management, carbon emissions reduction, intelligent services, and MM in vehicular networks. Despite the advantages of SDN-based mobility management, it’s crucial to acknowledge the challenges and limitations posed by traditional MM methods that SDN aims to overcome. The paper explores SDN’s potential in sustainable cities, focusing on how it can transform mobile device management, support various networking technologies, and evaluate the impact of SDN methods on existing MM systems, considering factors like scalability and compatibility. The paper asserts that SDN-based MM has substantial potential for promoting sustainable urban development. By centralizing control, adapting to changing conditions, and optimizing resource allocation, SDN can contribute to reduced energy consumption, lower carbon emissions, and more efficient urban mobility. It emphasizes the importance of addressing potential drawbacks to ensure successful implementation in sustainable cities

    Dynamic capacity planning of wireless networks using user mobility behavior in smart cities

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    Paper published for the IEEE Smart Cities Workshop: Crossing Discipline Boundaries for Smart Cities, Kansas City, MO, Feb. 8-9, 2016.Smart cities are envisioned as the organic integration of systems to provide valuable information for its citizens and service providers. One such example is user mobility behavior information (use of user location data) related to wireless network consumption and demands. In this paper, we propose the use of this data in a novel manner for capacity planning purposes in wireless networks. We approach fifth generation (5G) capacity planning by considering Cloud Radio Access Networks and Software Defined Mobile Networks to improve dynamic resource allocation. Privacy concerns are also addressed

    Software Defined Network-based control system for an efficient traffic management for emergency situations in smart cities

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    [EN] Smart cities provide new applications based on Internet of Things (loT) technology. Moreover, Software Defined Networks (SDNs) offer the possibility of controlling the network based on applications requirements. One of the main problems that arise when an emergency happens is minimizing the delay time in emergency resource forwarding so as to reduce both human and material damages. In this paper, a new control system based on the integration of SDN and loT in smart city environments is proposed. This control system actuates when an emergency happens and modifies dynamically the routes of normal and emergency urban traffic in order to reduce the time that the emergency resources need to get to the emergency area. The architecture is based on a set of loT networks composed by traffic lights, traffic cameras and an algorithm. The algorithm controls the request of resources and the modification of routes in order to ease the movement of emergency service units. Afterwards, the proposal is tested by emulating a Smart City as a SDN-utilizing Mininet. The experiments show that the delay of the emergency traffic improves in a 33% when the algorithm is running. Moreover, the energy consumed by the loT nodes is modeled and the obtained results display that it increases linearly with the number of nodes, therefore, the proposal is scalable. (C) 2018 Elsevier B.V. All rights reserved.This work has been partially supported by the " Ministerio de Educacion, Cultura y Deporte", through the "Ayudas para contratos predoctorales de Formacion del Profesorado Universitario FPU (Convocatoria 2015)". Grant number FPU15/06837, by the "Ministerio de Economia y Competitividad", through the "Convocatoria 2014. Proyectos I+D - P rograma Estatal de Investigacion Cientifica y Tecnica de Excelencia" in the "Subprograma Estatal de Generacion de Conocimiento", project TIN 2014-57991- C 3 - 1 - P and through the "Convocatoria 2016 - Proyectos I+D+I - P rograma Estatal De Investigacion, Desarrollo e Innovacion Orientada a los retos de la sociedad" (Project TEC 2016 - 76795 - C 6 - 4 - R). This work has also been partially supported by the "Ministerio de Economia y Competitividad" in the "Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia, Subprograma Estatal de Generacion de Conocimiento" within the project under Grant TIN2017-84802-C2-1-P.Rego Mañez, A.; García-García, L.; Sendra, S.; Lloret, J. (2018). Software Defined Network-based control system for an efficient traffic management for emergency situations in smart cities. Future Generation Computer Systems. 88:243-253. https://doi.org/10.1016/j.future.2018.05.054S2432538

    S-MANAGE Protocol for Software-Defined IoT

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    © 2018 IEEE. The Internet of Things (IoT) has started to make a real impact with many IoT-based services in agriculture, smart farming, smart cities, personal health, and critical infrastructures. Sensor/IoT devices form one of the indispensable elements in these IoT systems and services. An effective IoT system requires the interoperability among its heterogeneous physical devices, but this presents a significant challenge regarding various communication protocols, networking management policies, as well as data processing approaches. Software-defined paradigm is considered essential for managing and provisioning IoT services on demand. An emerging solution is the application of software-defined networking (SDN) and Network Function Virtualization (NFV) in programming WSN/IoT systems. However, these technologies cannot be directly deployed due to the differences in the functionality of SDN network devices and sensor/IoT devices as well as the limitation of resources in IoT devices. We proposed the software-defined IoT(SD-IoT) model in our earlier work. This paper focuses on the S-MANAGE protocol that enables an SD-IoT controller to control and manage sensor/IoT devices via their virtual representation, called software-defined virtual sensors (SDVS). The paper presents in detail the design and the implementation of the S-MANAGE southbound protocol

    Re-use of an ontology for modelling urban energy systems

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    The use of ontologies for the interoperability of software models is widespread, with many applications also in the energy domain. By formulating a shared data structure and a definition of concepts and their properties, a language is created that can be used between modellers and - formalised in an ontology - between model components. When modelling energy systems, connections between different infrastructures are critical, e.g. the interaction between the gas and electricity markets or the need for various infrastructures including power, heat, water and transport in cities. While a commonly shared ontology of energy systems would be highly desirable, the fact is that different existing models or applications already use dedicated ontologies, and have been demonstrated to work well using them. To benefit from linking data sources and connecting models developed with different ontologies, a translation between concepts can be made. In this paper a model of an urban energy system built upon one ontology is initialised using energy transformation technologies defined in another ontology, thus illustrating how this common perspective might benefit researchers in the energy domain. ©2010 IEEE

    Measuring the Quality of Machine Learning and Optimization Frameworks

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    Software frameworks are daily and extensively used in research, both for fundamental studies and applications. Researchers usually trust in the quality of these frameworks without any evidence that they are correctly build, indeed they could contain some defects that potentially could affect to thousands of already published and future papers. Considering the important role of these frameworks in the current state-of-the-art in research, their quality should be quantified to show the weaknesses and strengths of each software package. In this paper we study the main static quality properties, defined in the product quality model proposed by the ISO 25010 standard, of ten well-known frameworks. We provide a quality rating for each characteristic depending on the severity of the issues detected in the analysis. In addition, we propose an overall quality rating of 12 levels (ranging from A+ to D-) considering the ratings of all characteristics. As a result, we have data evidence to claim that the analysed frameworks are not in a good shape, because the best overall rating is just a C+ for Mahout framework, i.e., all packages need to go for a revision in the analysed features. Focusing on the characteristics individually, maintainability is by far the one which needs the biggest effort to fix the found defects. On the other hand, performance obtains the best average rating, a result which conforms to our expectations because frameworks’ authors used to take care about how fast their software runs.University of Malaga. Campus de Excelencia Internacional Andalucía Tech. We would like to say thank you to all authors of these frameworks that make research easier for all of us. This research has been partially funded by CELTIC C2017/2-2 in collaboration with companies EMERGYA and SECMOTIC with contracts #8.06/5.47.4997 and #8.06/5.47.4996. It has also been funded by the Spanish Ministry of Science and Innovation and /Junta de Andalucı́a/FEDER under contracts TIN2014-57341-R and TIN2017-88213-R, the network of smart cities CI-RTI (TIN2016-81766-REDT

    Collaborative perception architecture in smart cities

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    Autonomous Driving Systems have become a reality in our society. Everyday, progress is made to increase vehicles' autonomy to drive without restrictions in roads and cities. To achieve that, researchers are always seeking for new methods to ensure the safety of the vehicles. A promising strategy is to improve the quality of the collected perception data as it directly influences the overall performance of the autonomous system. However, despite the advances achieved in detection methods and algorithms, perception is currently physically restricted by the available on-board sensors and their line-of-sight. To overcome this limitation, the autonomous system should not only capture on-board perception data, but also enhance it with data exchanged with other agents in the environment. This is known in research as Collaborative Perception, where mobile and stationary agents share object detection and sensor data inside an Intelligent Transport Systems network. This master's thesis brings together a collection of ETSI standards with the goal of developing a well-defined architecture for future implementation of a Secure Collaborative Perception Network in the context of Smart Cities. The architecture has been designed using the open-source software Capella Arcadia following a Model Based Software Engineering methodology
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