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The Locator/Identifier Separation Protocol (LISP) is an encapsulation protocol currently in development. It is based on the potential need to reorganize the routing architecture of the Internet in order to meet the still increasing size of this worldwide network. The key principle of this protocol is to split the current IP address space into an identifier address space and a locator one. In this paradigm, the identifier address serves the purpose of identifying a connection endpoint and is only routable in a stub network, a LISP site. The locator address, in turn, is used to locate this site in the core network. This address is thus globally routable. For nodes from different LISP sites to communicate between each other, a data tunnel has to be put in place between both sites.

Because of this separation principle, LISP needs a mechanism allowing it to translate an address from the identifier space to the locator space: the mapping system. Thanks to this, a LISP site is able to query a mapping, binding both address spaces, by the use of LISP control messages. LISP-DDT is a notable example of mapping system which draws inspiration, regarding its architecture, from the Domain Name System.

Both LISP and LISP-DDT current implementations may be prone to potential security vulnerabilities. In this regard, this work aims at getting a clear understanding of the security aspects of the studied protocols. This approach is done in order to find potential vulnerabilities in these protocols -- while not claiming to be exhaustive -- and take advantage of them in order to develop an attack. That way, a denial-of-service attack by amplification has been found out. This attack exploits the mapping lookup process between a LISP site and the mapping system. In particular, it relies on the fact that the mapping system is able to generate responses that are significantly larger than the queries causing them. This principle can hence be used to produce a lot of network traffic towards a predetermined victim node in order to consume its bandwidth.

As a proof-of-concept for the attack, a GNS3 emulated network topology has been set up and configured. This network therefore simulates an up and running LISP-DDT mapping system -- mimicking the one of the LISP Beta Network, a worldwide deployment of LISP on Internet -- in order to use it as an amplification vector for the attack. Results of the attack on this enclosed environment are analysed in this work. It proves the feasibility of the attack in the current implementations of LISP and LISP-DDT.

Finally, a brief discussion about possible mitigation techniques for the attack is provided. Among these mitigation techniques, one can cite the limitation of the reply size, the rate limitation or even anti-spoofing techniques. Either way, we hope to draw the LISP IETF Working Group's attention to the necessity of addressing this issue.

LISP --- LISP-DDT --- Mapping system --- DoS attack --- Amplification --- IP Spoofing --- GNS3 --- Security --- Networking --- Ingénierie, informatique & technologie > Sciences informatiques

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Remote sensing is being actively researched in the fields of environment, military and urban planning through technologies such as monitoring of natural climate phenomena on the earth, land cover classification, and object detection. Recently, satellites equipped with observation cameras of various resolutions were launched, and remote sensing images are acquired by various observation methods including cluster satellites. However, the atmospheric and environmental conditions present in the observed scene degrade the quality of images or interrupt the capture of the Earth's surface information. One method to overcome this is by generating synthetic images through image simulation. Synthetic images can be generated by using statistical or knowledge-based models or by using spectral and optic-based models to create a simulated image in place of the unobtained image at a required time. Various proposed methodologies will provide economical utility in the generation of image learning materials and time series data through image simulation. The 6 published articles cover various topics and applications central to Remote sensing image simulation. Although submission to this Special Issue is now closed, the need for further in-depth research and development related to image simulation of High-spatial and spectral resolution, sensor fusion and colorization remains.I would like to take this opportunity to express my most profound appreciation to the MDPI Book staff, the editorial team of Applied Sciences journal, especially Ms. Nimo Lang, the assistant editor of this Special Issue, talented authors, and professional reviewers.

image fusion --- random forest regression --- SAR image --- panchromatic image --- high-resolution --- multi-beam LiDAR --- in situ self-calibration --- mobile mapping system --- 3D point cloud --- backpack-based mapping --- aerial orthoimage --- Sentinel-2 --- super-resolution --- image simulation --- residual U-Net --- interferometry --- remote sensing --- computational simulation --- denoising --- detection --- SAR imagery --- fusing region proposals --- KOMPSAT-3A --- strip --- sensor modeling --- RPCs --- mosaic --- matching --- discrepancy --- n/a

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As climate-change- and human-induced floods inflict increasing costs upon the planet, both in terms of lives and environmental damage, flood monitoring tools derived from remote sensing platforms have undergone improvements in their performance and capabilities in terms of spectral, spatial and temporal extents and resolutions. Such improvements raise new challenges connected to data analysis and interpretation, in terms of, e.g., effectively discerning the presence of floodwaters in different land-cover types and environmental conditions or refining the accuracy of detection algorithms. In this sense, high expectations are placed on new methods that integrate information obtained from multiple techniques, platforms, sensors, bands and acquisition times. Moreover, the assessment of such techniques strongly benefits from collaboration with hydrological and/or hydraulic modeling of the evolution of flood events. The aim of this Special Issue is to provide an overview of recent advancements in the state of the art of flood monitoring methods and techniques derived from remotely sensed data.

mobile mapping system --- RRI model --- high-water marks --- inundation --- Northern Kyushu floods --- point clouds --- flood mapping --- temporary flooded vegetation (TFV) --- Sentinel-1 --- time series data --- Synthetic Aperture Radar (SAR) --- sentinel-1 --- SAR --- flood --- image classification --- clustering --- monsoon --- Philippines --- LiDAR --- geometric parameters --- levee stability --- overtopping --- Pearl River Delta --- CYGNSS --- flood detection --- Sistan and Baluchestan --- GNSS-R --- flood monitoring --- ALOS 2 --- multi-sensor integration --- multi-temporal inundation analysis --- Zambesi-Shire river basin --- image processing --- hydrology --- synthetic aperture radar --- n/a

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As climate-change- and human-induced floods inflict increasing costs upon the planet, both in terms of lives and environmental damage, flood monitoring tools derived from remote sensing platforms have undergone improvements in their performance and capabilities in terms of spectral, spatial and temporal extents and resolutions. Such improvements raise new challenges connected to data analysis and interpretation, in terms of, e.g., effectively discerning the presence of floodwaters in different land-cover types and environmental conditions or refining the accuracy of detection algorithms. In this sense, high expectations are placed on new methods that integrate information obtained from multiple techniques, platforms, sensors, bands and acquisition times. Moreover, the assessment of such techniques strongly benefits from collaboration with hydrological and/or hydraulic modeling of the evolution of flood events. The aim of this Special Issue is to provide an overview of recent advancements in the state of the art of flood monitoring methods and techniques derived from remotely sensed data.

Technology: general issues --- History of engineering & technology --- Environmental science, engineering & technology --- mobile mapping system --- RRI model --- high-water marks --- inundation --- Northern Kyushu floods --- point clouds --- flood mapping --- temporary flooded vegetation (TFV) --- Sentinel-1 --- time series data --- Synthetic Aperture Radar (SAR) --- sentinel-1 --- SAR --- flood --- image classification --- clustering --- monsoon --- Philippines --- LiDAR --- geometric parameters --- levee stability --- overtopping --- Pearl River Delta --- CYGNSS --- flood detection --- Sistan and Baluchestan --- GNSS-R --- flood monitoring --- ALOS 2 --- multi-sensor integration --- multi-temporal inundation analysis --- Zambesi-Shire river basin --- image processing --- hydrology --- synthetic aperture radar --- n/a

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This book includes 13 papers published in Special Issue ("Visual and Camera Sensors") of the journal Sensors. The goal of this Special Issue was to invite high-quality, state-of-the-art research papers dealing with challenging issues in visual and camera sensors.

self-assembly device --- 3D point clouds --- accuracy analysis --- VSLAM-photogrammetric algorithm --- portable mobile mapping system --- low-cost device --- BIM --- camera calibration --- DLT --- PnP --- weighted DLT --- uncertainty --- covariance --- robustness --- visual-inertial --- semi-direct SLAM --- multi-sensor fusion --- side-rear-view monitoring system --- automatic online calibration --- Hough-space --- unmanned aerial vehicle --- autonomous landing --- deep-learning-based motion deblurring and marker detection --- network slimming --- pruning model --- convolutional neural network --- convolutional filter --- classification --- multimodal human recognition --- blur image restoration --- DeblurGAN --- CNN --- facial expression recognition system --- computer vision --- multi-scale featured local binary pattern --- unsharp masking --- machine learning --- lens distortion --- DoF-dependent --- distortion partition --- vision measurement --- pathological site classification --- in vivo endoscopy --- computer-aided diagnosis --- artificial intelligence --- ensemble learning --- convolutional auto-encoders --- local image patch --- point pair feature --- plank recognition --- robotic grasping --- flying object detection --- drone --- image processing --- camera networks --- open-pit mine slope monitoring --- optimum deployment --- close range photogrammetry --- three-dimensional reconstruction --- OCD4M