Institution
Edinburgh Napier University
Education•Edinburgh, United Kingdom•
About: Edinburgh Napier University is a education organization based out in Edinburgh, United Kingdom. It is known for research contribution in the topics: Population & Context (language use). The organization has 2665 authors who have published 6859 publications receiving 175272 citations.
Papers published on a yearly basis
Papers
More filters
••
TL;DR: The model estimation results show that a wide range of accident, vehicle, driver, trip and location characteristics have varying impacts on injury severities when different weather and lighting conditions are jointly considered.
68 citations
••
TL;DR: This article proposes a novel ensemble deep learning based web attack detection system (EDL-WADS) to alleviate the serious issues that IoT networks faces and shows that the proposed system can detect web attacks accurately with low false positive and negative rates.
Abstract: Internet of Things (IoT) has become one of the fastest-growing technologies and has been broadly applied in various fields. IoT networks contain millions of devices with the capability of interacting with each other and providing functionalities that were never available to us before. These IoT networks are designed to provide friendly and intelligent operations through big data analysis of information generated or collected from an abundance of devices in real time. However, the diversity of IoT devices makes the IoT networks’ environments more complex and more vulnerable to various web attacks compared to traditional computer networks. In this article, we propose a novel ensemble deep learning based web attack detection system (EDL-WADS) to alleviate the serious issues that IoT networks faces. Specifically, we have designed three deep learning models to first detect web attacks separately. We then use an ensemble classifier to make the final decision according to the results obtained from the three deep learning models. In order to evaluate the proposed WADS, we have performed experiments on a public dataset as well as a real-word dataset running in a distributed environment. Experimental results show that the proposed system can detect web attacks accurately with low false positive and negative rates.
68 citations
••
TL;DR: It is suggested that in order to verify this, it is necessary for smart cities to first baseline the social-demographic structure of retrofit proposals, to assess whether the regional innovation creates the wealth needed to under-grid the sustainability of city-districts.
68 citations
••
TL;DR: A novel analytical model is proposed for holistic handover (HO) cost evaluation, that integrates signaling overhead, latency, call dropping, and radio resource wastage, and a novel application of a recurrent deep learning architecture, specifically, a stacked long-short-term memory model.
68 citations
••
Hampshire Hospitals NHS Foundation Trust1, Aberdeen Royal Infirmary2, University of Salerno3, University of Southampton4, Erciyes University5, NHS Ayrshire and Arran6, University of Udine7, Tan Tock Seng Hospital8, Murdoch University9, Edinburgh Napier University10, University of Pennsylvania11, Ross University School of Veterinary Medicine12, Humboldt University of Berlin13, University of Aberdeen14, Charité15, Royal Prince Alfred Hospital16, Statens Serum Institut17, University of Rennes18, Erasmus University Rotterdam19, Radboud University Nijmegen20
TL;DR: Panton–Valentine leukocidin (PVL), a pore-forming cytotoxic secreted toxin, has been associated with severe Staphylococcus aureus pneumonia and prototypical skin lesions and suffers from a selective reporting bias towards community-associated methicillin-resistant S. a Aureus.
68 citations
Authors
Showing all 2727 results
Name | H-index | Papers | Citations |
---|---|---|---|
William MacNee | 123 | 472 | 58989 |
Richard J. Simpson | 113 | 850 | 59378 |
Ken Donaldson | 109 | 385 | 47072 |
John Campbell | 107 | 1150 | 56067 |
Muhammad Imran | 94 | 3053 | 51728 |
Barbara Rothen-Rutishauser | 70 | 339 | 17348 |
Vicki Stone | 69 | 204 | 25002 |
Sharon K. Parker | 68 | 238 | 21089 |
Matt Nicholl | 66 | 224 | 15208 |
John H. Adams | 66 | 354 | 16169 |
Darren J. Kelly | 65 | 252 | 13007 |
Neil B. McKeown | 65 | 281 | 19371 |
Jane K. Hill | 62 | 147 | 20733 |
Min Du | 61 | 326 | 11328 |
Xiaodong Liu | 60 | 474 | 14980 |