In 2019, the majority of companies used at least one cloud computing service and it is expected that by the end of 2021, cloud data centres will process 94% of workloads. The financial and operational advantages of moving IT infrastructure to specialised cloud providers are clearly compelling. However, with such volumes of private and personal data being stored in cloud computing infrastructures, security concerns have risen. Motivated to monitor and analyze adversarial activities, we deploy multiple honeypots on the popular cloud providers, namely Amazon Web Services (AWS), Google Cloud Platform (GCP) and Microsoft Azure, and operate them in multiple regions. Logs were collected over a period of three weeks in May 2020 and then comparatively analysed, evaluated and visualised. Our work revealed heterogeneous attackers' activity on each cloud provider, both when one considers the volume and origin of attacks, as well as the targeted services and vulnerabilities. Our results highlight the attempt of threat actors to abuse popular services, which were widely used during the COVID-19 pandemic for remote working, such as remote desktop sharing. Furthermore, the attacks seem to exit not only from countries that are commonly found to be the source of attacks, such as China, Russia and the United States, but also from uncommon ones such as Vietnam, India and Venezuela. Our results provide insights on the adversarial activity during our experiments, which can be used to inform the Situational Awareness operations of an organisation.
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http://dx.doi.org/10.3390/s21072433 | DOI Listing |
J Colloid Interface Sci
January 2025
Institute of Advanced Chemistry of Catalonia (IQAC), Consejo Superior de Investigaciones Científicas (CSIC), Jordi Girona, 18-26, 08034 Barcelona, Spain; Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN, ISCIII), Jordi Girona, 18-26, 08034 Barcelona, Spain. Electronic address:
Hypothesis: Water-in-water (W/W) emulsions can be obtained when two water-soluble components are mutually immiscible. The scientific literature on W/W emulsions focuses on polymer-polymer mixtures, with only a few reports on polymer-salt systems, and no documented cases involving polymer-surfactant mixtures. Our hypothesis was that by lowering the cloud temperature of a surfactant through the addition of a polymer, phase segregation into two immiscible aqueous solutions could enable the formation of W/W emulsions.
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January 2025
Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China.
Accurate 6D object pose estimation is critical for autonomous docking. To address the inefficiencies and inaccuracies associated with maximal cliques-based pose estimation methods, we propose a fast 6D pose estimation algorithm that integrates feature space and space compatibility constraints. The algorithm reduces the graph size by employing Laplacian filtering to resample high-frequency signal nodes.
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January 2025
College of Electronics and Information Engineering, South-Central Minzu University, Wuhan 430074, China.
Drones are extensively utilized in both military and social development processes. Eliminating the reliance of drone positioning systems on GNSS and enhancing the accuracy of the positioning systems is of significant research value. This paper presents a novel approach that employs a real-scene 3D model and image point cloud reconstruction technology for the autonomous positioning of drones and attains high positioning accuracy.
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January 2025
School of Geosciences, Yangtze University, Wuhan 430100, China.
Roadside tree segmentation and parameter extraction play an essential role in completing the virtual simulation of road scenes. Point cloud data of roadside trees collected by LiDAR provide important data support for achieving assisted autonomous driving. Due to the interference from trees and other ground objects in street scenes caused by mobile laser scanning, there may be a small number of missing points in the roadside tree point cloud, which makes it familiar for under-segmentation and over-segmentation phenomena to occur in the roadside tree segmentation process.
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December 2024
College of Cryptography Engineering, Engineering University of PAP, Xi'an 710086, China.
With the rapid development of the Internet of Things (IoT), the scope of personal data sharing has significantly increased, enhancing convenience in daily life and optimizing resource management. However, this also poses challenges related to data privacy breaches and holdership threats. Typically, blockchain technology and cloud storage provide effective solutions.
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