623 research outputs found

    Security Implications of Fog Computing on the Internet of Things

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    Recently, the use of IoT devices and sensors has been rapidly increased which also caused data generation (information and logs), bandwidth usage, and related phenomena to be increased. To our best knowledge, a standard definition for the integration of fog computing with IoT is emerging now. This integration will bring many opportunities for the researchers, especially while building cyber-security related solutions. In this study, we surveyed about the integration of fog computing with IoT and its implications. Our goal was to find out and emphasize problems, specifically security related problems that arise with the employment of fog computing by IoT. According to our findings, although this integration seems to be non-trivial and complicated, it has more benefits than the implications.Comment: 5 pages, conference paper, to appear in Proceedings of the ICCE 2019, IEEE 37th International Conference on Consumer Electronics (ICCE), Jan 11- 13, 2019, Las Vegas, NV, US

    Solar-blind AlxGa1-xN-based avalanche photodiodes

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    Cataloged from PDF version of article.We report the Metalorganic Chemical Vapor Deposition (MOCVD) growth, fabrication, and characterization of solar blind AlxGa1-xN/GaN-based avalanche photodiodes. The photocurrent voltage characteristics indicate a reproducible avalanche gain higher than 25 at a 72 V applied reverse bias. Under a 25 V reverse bias voltage, the 100 mu m diameter devices had a maximum quantum efficiency of 55% and a peak responsivity of 0.11 A/W at 254 nm, and a NEP of 1.89x10(-16) W/Hz(1/2). (c) 2005 American Institute of Physics

    A qualitative systematic review of the reasons for parental attendance at the emergency department with children presenting with minor illness

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    Introduction: Over 5 million children attend the Emergency Department (ED) annually in England with an ever-increasing paediatric emergency caseload echoed globally. Approximately 60% of children present with illness and the majority have non-urgent illness creating burgeoning pressures on children’s ED and this crisis resonates globally. To date no qualitative systematic review exists that focuses on the parental reasons for childhood attendance at the ED in this subgroup. Aim: To identify parental reasons for attending ED for their children presenting with minor illness. Method: A qualitative systematic review was conducted against inclusion/exclusion 10 criteria. Five electronic databases and key journals were searched in June 2015. Findings: 471 studies were identified and following study selection, 4 qualitative studies 12 were included. Nine themes were identified e.g. dissatisfaction with family medical services, perceived advantages of ED and ‘child suffering’ with novel and insightful sub-themes of ‘hereditary anxiety’, ‘taking it off our hands’, ED as a ‘magical place’. Conclusion: This novel qualitative systematic review examined parental attendance presenting with childhood minor illness of interest to emergency care reformers and clinicians. ED attendance is complex and multifactorial but parents provide vital insight to ED reformers on parental reasons for ED attendance in this sub group

    Leakage current by Frenkel-Poole emission in Ni/Au Schottky contacts on Al0.83In0.17N/AlN/GaN heterostructures

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    Cataloged from PDF version of article.In order to determine the reverse-bias leakage current mechanisms in Schottky diodes on Al0.83In0.17N/AlN/GaN heterostructures, the temperature-dependent current-voltage measurements were performed in the temperature range of 250-375 K. In this temperature range, the leakage current was found to be in agreement with the predicted characteristics, which is based on the Frenkel-Poole emission model. The analysis of the reverse current-voltage characteristics dictates that the main process in leakage current flow is the emission of electrons from a trapped state near the metal-semiconductor interface into a continuum of states which associated with each conductive dislocation

    How Image Degradations Affect Deep CNN-based Face Recognition?

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    Face recognition approaches that are based on deep convolutional neural networks (CNN) have been dominating the field. The performance improvements they have provided in the so called in-the-wild datasets are significant, however, their performance under image quality degradations have not been assessed, yet. This is particularly important, since in real-world face recognition applications, images may contain various kinds of degradations due to motion blur, noise, compression artifacts, color distortions, and occlusion. In this work, we have addressed this problem and analyzed the influence of these image degradations on the performance of deep CNN-based face recognition approaches using the standard LFW closed-set identification protocol. We have evaluated three popular deep CNN models, namely, the AlexNet, VGG-Face, and GoogLeNet. Results have indicated that blur, noise, and occlusion cause a significant decrease in performance, while deep CNN models are found to be robust to distortions, such as color distortions and change in color balance.Comment: 8 pages, 3 figure

    Industrial networks and IIoT: Now and future trends

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    Connectivity is the one word summary for Industry 4.0 revolution. The importance of Internet of Things (IoT) and Industrial IoT (IIoT) have been increased dramatically with the rise of industrialization and industry 4.0. As new opportunities bring their own challenges, with the massive interconnected devices of the IIoT, cyber security of those networks and privacy of their users have become an important aspect. Specifically, intrusion detection for industrial networks (IIoT) has great importance. For instance, it is a key factor in improving the safe operation of the smart grid systems yet protecting the privacy of the consumers at the same time. In the same manner, data streaming is a valid option when the analysis is to be pushed from the cloud to the fog for industrial networks to provide agile response, since it brings the advantage of fast action on intrusion detection and also can buy time for intrusion mitigation. In order to dive deep in industrial networks, basic ground needs to be settled. Hence, this chapter serves in this manner, by presenting basic and emerging technologies along with ideas and discussions: First, an introduction of semiconductor evolution is provided along with the up-to-date hi-tech wired/wireless communication solutions for industrial networks. This is followed by a thorough representation of future trends in industrial environments. More importantly, enabling technologies for industrial networks is also presented. Finally, the chapter is concluded with a summary of the presentations along with future projections of IIoT networks

    Security of the Internet of Things: Vulnerabilities, Attacks and Countermeasures

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    Wireless Sensor Networks (WSNs) constitute one of the most promising third-millennium technologies and have wide range of applications in our surrounding environment. The reason behind the vast adoption of WSNs in various applications is that they have tremendously appealing features, e.g., low production cost, low installation cost, unattended network operation, autonomous and longtime operation. WSNs have started to merge with the Internet of Things (IoT) through the introduction of Internet access capability in sensor nodes and sensing ability in Internet-connected devices. Thereby, the IoT is providing access to huge amount of data, collected by the WSNs, over the Internet. Hence, the security of IoT should start with foremost securing WSNs ahead of the other components. However, owing to the absence of a physical line-of-defense, i.e., there is no dedicated infrastructure such as gateways to watch and observe the flowing information in the network, security of WSNs along with IoT is of a big concern to the scientific community. More specifically, for the application areas in which CIA (confidentiality, integrity, availability) has prime importance, WSNs and emerging IoT technology might constitute an open avenue for the attackers. Besides, recent integration and collaboration of WSNs with IoT will open new challenges and problems in terms of security. Hence, this would be a nightmare for the individuals using these systems as well as the security administrators who are managing those networks. Therefore, a detailed review of security attacks towards WSNs and IoT, along with the techniques for prevention, detection, and mitigation of those attacks are provided in this paper. In this text, attacks are categorized and treated into mainly two parts, most or all types of attacks towards WSNs and IoT are investigated under that umbrella: “Passive Attacks” and “Active Attacks”. Understanding these attacks and their associated defense mechanisms will help paving a secure path towards the proliferation and public acceptance of IoT technology

    Nanoantenna coupled UV subwavelength photodtectors based on GaN

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    Cataloged from PDF version of article.The integration of nano structures with opto-electronic devices has many potential applications. It allows the coupling of more light into or out of the device while decreasing the size of the device itself. Such devices are reported in the VIS and NIR regions. However, making plasmonic structures for the UV region is still a challenge. Here, we report on a UV nano-antenna integrated metal semiconductor metal (MSM) photodetector based on GaN. We designed and fabricated Al grating structures. Well defined plasmonic resonances were measured in the reflectance spectra. Optimized grating structure integrated photodetectors exhibited more than sevenfold photocurrent enhancement. Finite difference time domain simulations revealed that both geometrical and plasmonic effects played role in photocurrent enhancement. (C) 2012 Optical Society of Americ
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