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Background Traffic We consider all traces collected in
2018 from the IP backbone from CAIDA (2018)’s monitors
for background traffic. Similar to Nagaraja et al. (2010), we
perform the aggregation for the traffic graph and conduct
experiments over the resulting subnet-level graph since netflow traces are aggregated into subnets for anonymity. We
select a random subset of nodes in the background traffic as
botnet nodes for embedding the botnet topology.


Botnet Traffic To investigate sensitivity of our techniques,
we embed the background traffic with particular overlaid P2P topologies we synthesize, including DE BRUIJN
(Kaashoek & Karger, 2003), KADEMLIA (Maymounkov &
Mazieres, 2002), CHORD (Stoica et al., 2001), and LEETCHORD (Jelasity & Bilicki, 2009). We also overlay two
real botnets from Garcia et al. (2014) in the manner as the
synthetic ones: a decentralized botnet P2P and a centralized
botnet C2 captured in 2011. As the two botnets are from
real malware, their traffic contains attack behaviors apart
from inner communication traffic.

This simulation experiment uses OPNET and STK simulation software to simulate
the information transmission network. From the Iridium constellation, we selected six
satellites and two ground stations to simulate the integrated information network of
heaven and earth. First, the data packets are routed through the satellite network to
find the best path, then transmitted to the relay node, and finally arrive at the ground
station


OPNET and STK (Systems Tool Kit) are both software tools used for simulating and analyzing networks. OPNET is primarily used for simulating and analyzing computer networks, while STK is used for simulating and analyzing satellite networks and other systems in a space or aerospace context. Both tools can be used for a wide range of applications, including network design, performance analysis, and troubleshooting. However, STK is geared more towards satellite system analysis and simulation, including satellite orbit prediction, coverage analysis and link budgeting . OPNET is more geared towards computer network analysis and simulation, including network protocol analysis, traffic analysis and network performance analysis.

https://www.youtube.com/watch?v=jo97pX_5DqY&list=PLvdhJ__UbhZ60sUxQFJu_a6Ck2dI_y0Ke

https://github.com/topics/iridium-satellites

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Satellite network và dataset

Dataset of satellite communication

https://www.kaggle.com/datasets/mahmoudreda55/satellite-image-classification

https://arxiv.org/abs/1706.06169

https://docs.google.com/document/d/10mkXBpZ9l10r2F4uvxPwPBl3Z-oIm36pV9YxeT8UlqE/edit#

Iridium constellation dataset github

https://ieee-dataport.org/open-access/mobile-communication-system-measurements-and-satellite-images

There are several datasets available for satellite network traffic analysis. Some examples include:

The GlobalSat dataset: This dataset was collected by the GlobalSat project, which aimed to study the performance of satellite networks in different parts of the world. The dataset contains a variety of satellite network traffic data, including TCP and UDP traffic, as well as data on network congestion and packet loss.

The GEO-SAT dataset: This dataset was collected by the European Space Agency and contains data on satellite network traffic in geostationary orbit (GEO). The dataset includes information on network congestion, packet loss, and other performance metrics.

The SatGen dataset: This dataset was generated by the SatGen tool, which is a tool for generating synthetic satellite network traffic. The dataset includes data on satellite network traffic patterns, including traffic volume and traffic distribution.

The NICT Satellite Traffic Dataset: This dataset was collected by the National Institute of Information and Communications Technology (NICT) in Japan and contains data on satellite network traffic in the Ka-band. The dataset includes information on traffic volume, packet loss, and other performance metrics.

The HST-3G dataset: This dataset was collected by the European Space Agency and contains data on satellite network traffic in the HST-3G (High-Speed Transmission 3rd Generation) satellite system. The dataset includes information on network congestion, packet loss, and other performance metrics.

These datasets can be used for research, benchmarking, and performance analysis of satellite network.

https://github.com/search?p=8&q=satellite+dataset&type=Repositories
https://data.mendeley.com/datasets/5pmnkshffm/3

https://github.com/chrieke/awesome-satellite-imagery-datasets

https://github.com/Seyed-Ali-Ahmadi/Awesome_Satellite_Benchmark_Datasets

https://github.com/dl4sits/BreizhCrops


HST-3G dataset
https://yzengal.github.io/files/ICDE21-HST-Full.pdf

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Satellite networks serve as conduits for a diverse range of data, catering to an array of applications and services. The following categories encompass the prevalent types of data transmitted over satellite networks:

+ Voice and Telephony [*7]: An essential function of satellite networks lies in facilitating voice communication, particularly in remote regions where terrestrial infrastructure may be limited or absent. By serving as intermediaries, satellites enable the transmission of voice signals between user devices or between user devices and landline networks, thus extending the reach of long-distance telephony.

+ Internet Data: Satellite networks assume a pivotal role in providing internet connectivity to areas where terrestrial networks are not readily accessible. By means of satellite links, a broad spectrum of internet data, encompassing web pages, emails, file downloads, and streaming media, can be effectively transmitted. Consequently, individuals, businesses, and organizations gain access to a vast realm of online resources and services, regardless of their geographical location. Notably, the network traffic data set published in reference [*25] represents a notable example within this domain.

+ Video and Television Broadcasting [*8]: The transmission of television signals constitutes a substantial aspect of satellite network functionality, affording broadcasters the means to disseminate television channels to a wide-ranging audience. Direct-to-Home (DTH) satellite television services exemplify this capability, as they deliver video and audio signals directly from satellites to user devices such as satellite TV receivers, thereby granting access to an extensive selection of TV channels.

+ Data Networks and Virtual Private Networks (VPNs) [*9]: Satellite networks offer robust data connectivity for a multitude of applications, including corporate networks, government networks, and remote site connectivity. Through their utilization, wide-area networks (WANs) and virtual private networks (VPNs) can be established, facilitating secure and private data communication between disparate locations.

+ Earth Observation Data [*10]: Satellites dedicated to Earth observation contribute significantly to the transmission of data pertaining to the Earth's surface, atmosphere, and environmental conditions. This encompasses a vast array of information, including high-resolution images, weather data, climate data, and other pertinent environmental parameters. Such data finds utility in diverse applications such as weather forecasting, disaster management, agriculture, urban planning, and environmental monitoring.

+ Global Navigation Satellite Systems (GNSS) Data [*11]: Noteworthy satellite networks, such as the Global Positioning System (GPS), Galileo, and GLONASS, are responsible for transmitting navigation data to user devices. This invaluable data serves as the foundation for precise positioning, navigation, and timing information, thereby enabling a plethora of applications, including navigation systems, geolocation services, and asset or vehicle tracking.

+ Sensor Data and Telemetry [*12]: Satellites, equipped with sensors or scientific instruments, fulfill a critical role in the collection and transmission of diverse data types for research purposes. This encompasses a wide range of scientific disciplines, including space exploration, astronomy, climate studies, oceanography, and related domains, thereby contributing to advancements in scientific knowledge.

+ Command and Control Data [*13]: In order to effectively manage and operate satellites, satellite networks necessitate the transmission of command and control data. This entails the exchange of commands to configure satellite functions, the monitoring of satellite health and performance, and the management of orbital parameters, all of which are essential for maintaining satellite operations at an optimal level.

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*7 Abdrakhmanova M. et al. Speakingfaces: A large-scale multimodal dataset of voice commands with visual and thermal video streams //Sensors. – 2021. – Т. 21. – №. 10. – С. 3465.

*8 Du B., Cai S., Wu C. Object tracking in satellite videos based on a multiframe optical flow tracker //IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. – 2019. – Т. 12. – №. 8. – С. 3043-3055.

*9 Naas M., Fesl J. A novel dataset for encrypted virtual private network traffic analysis //Data in Brief. – 2023. – Т. 47. – С. 108945.

*10 Gomes V. C. F., Queiroz G. R., Ferreira K. R. An overview of platforms for big earth observation data management and analysis //Remote Sensing. – 2020. – Т. 12. – №. 8. – С. 1253.

*11 Mendez-Astudillo J. et al. A new Global Navigation Satellite System (GNSS) based method for urban heat island intensity monitoring //International Journal of Applied Earth Observation and Geoinformation. – 2021. – Т. 94. – С. 102222.

*12 Halim D. K., Hutagalung S. Towards data sharing economy on Internet of Things: a semantic for telemetry data //Journal of Big Data. – 2022. – Т. 9. – №. 1. – С. 1-24.

*13 Hosseini N. et al. UAV command and control, navigation and surveillance: A review of potential 5G and satellite systems //2019 IEEE Aerospace Conference. – IEEE, 2019. – С. 1-10.

*25.	Labayen V., Magaña E., Morató D., Izal M. Online classification of user activities using machine learning on network traffic. Computer Networks. 2020;181:107557. DOI:10.1016/j.comnet.2020.107557