scholarly journals Cloud-Based User Behavior Emulation Approach for Space-Ground Integrated Networks

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 44
Author(s):  
Leiting Tao ◽  
Xiaofeng Wang ◽  
Yuan Liu ◽  
Jie Wu
Keyword(s):  
Large Scale ◽  
User Behavior ◽  
Security Evaluation ◽  
Security Strategy ◽  
Integrated Networks ◽  
Computational Overhead ◽  
Concurrent Communication ◽  
Test Platform ◽  
Scale Characteristics ◽  
Dynamic Emulation

Cyber-physical systems (CPSs) based on space-ground integrated networks (SGINs) enable CPSs to break through geographical restrictions in space. Therefore, providing a test platform is necessary for new technical verification and network security strategy evaluations of SGINs. User behavior emulation technology can effectively support the construction of a test platform. Given the inherent dynamic changes, diverse behaviors, and large-scale characteristics of SGIN users, we propose user behavior emulation technology based on a cloud platform. First, the dynamic emulation architecture for user behavior for SGINs is designed. Then, normal user behavior emulation strategy driven by the group user behavior model in real time is proposed, which can improve the fidelity of emulation. Moreover, rogue user behavior emulation technology is adopted, based on traffic replay, to perform the security evaluation. Specifically, virtual Internet Protocol (IP) technology and the epoll model are effectively integrated in this investigation to resolve the contradiction between large-scale emulation and computational overhead. The experimental results demonstrate that the strategy meets the requirement of a diverse and high-fidelity dynamic user behavior emulation and reaches the emulation scale of 100,000-level concurrent communication for normal users and 100,000-level concurrent attacks for rogue users.

scholarly journals A lightweight cryptographic algorithm for the transmission of images from road environments in self-driving

Cybersecurity ◽  
2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Runchen Gao ◽  
Shen Li ◽  
Yuqi Gao ◽  
Rui Guo
Keyword(s):  
Large Scale ◽  
Edge Computing ◽  
Sensitive Information ◽  
Security Strategy ◽  
Privacy Leakage ◽  
Computational Overhead ◽  
Cryptographic Algorithm ◽  
Comparable Encryption ◽  
Iot Devices ◽  
The Internet Of Things

AbstractWith the large-scale application of 5G in industrial production, the Internet of Things has become an important technology for various industries to achieve efficiency improvement and digital transformation with the help of the mobile edge computing. In the modern industry, the user often stores data collected by IoT devices in the cloud, but the data at the edge of the network involves a large of the sensitive information, which increases the risk of privacy leakage. In order to address these two challenges, we propose a security strategy in the edge computing. Our security strategy combines the Feistel architecture and short comparable encryption based on sliding window (SCESW). Compared to existing security strategies, our proposed security strategy guarantees its security while significantly reducing the computational overhead. And our GRC algorithm can be successfully deployed on a hardware platform.

A Scalable Redefined Stochastic Blockmodel

2021 ◽  
Vol 15 (3) ◽  
pp. 1-28
Author(s):  
Xueyan Liu ◽  
Bo Yang ◽  
Hechang Chen ◽  
Katarzyna Musial ◽  
Hongxu Chen ◽  
...  
Keyword(s):  
Large Scale ◽  
Network Science ◽  
Learning Algorithm ◽  
State Of The Art ◽  
Real World Data ◽  
Computational Overhead ◽  
Stochastic Blockmodel ◽  
Np Hard Problem ◽  
Large Scale Networks ◽  
The Cost

Stochastic blockmodel (SBM) is a widely used statistical network representation model, with good interpretability, expressiveness, generalization, and flexibility, which has become prevalent and important in the field of network science over the last years. However, learning an optimal SBM for a given network is an NP-hard problem. This results in significant limitations when it comes to applications of SBMs in large-scale networks, because of the significant computational overhead of existing SBM models, as well as their learning methods. Reducing the cost of SBM learning and making it scalable for handling large-scale networks, while maintaining the good theoretical properties of SBM, remains an unresolved problem. In this work, we address this challenging task from a novel perspective of model redefinition. We propose a novel redefined SBM with Poisson distribution and its block-wise learning algorithm that can efficiently analyse large-scale networks. Extensive validation conducted on both artificial and real-world data shows that our proposed method significantly outperforms the state-of-the-art methods in terms of a reasonable trade-off between accuracy and scalability. 1

A Novel Stable Algorithm of Getting User’s Account Based on Telnet Protocol

2013 ◽  
Vol 299 ◽  
pp. 130-134
Author(s):  
Li Wei ◽  
Da Zhi Deng
Keyword(s):  
Network Security ◽  
Network Management ◽  
Large Scale ◽  
Computer Network ◽  
User Behavior ◽  
Political Stability ◽  
Future Internet ◽  
Stable Algorithm ◽  
Internet User Behavior ◽  
Security Incidents

In recent years,china input in the construction of the network management is constantly increasing;information technology has improved continuously,but,making a variety of network security incidents occur frequently,due to the vulnerability of the computer network system inherent,a direct impact on national security and social and political stability. Because of the popularity of computers and large-scale development of the Internet, network security has been increasing as the theme. Reasonable safeguards against violations of resources; regular Internet user behavior and so on has been the public's expectations of future Internet. This paper described a stable method of getting telnet user’s account in development of network management based on telnet protocol.

scholarly journals Small-scale characteristics of extremely high latitude aurora

2009 ◽  
Vol 27 (9) ◽  
pp. 3335-3347 ◽  
Author(s):  
J. A. Cumnock ◽  
L. G. Blomberg ◽  
A. Kullen ◽  
T. Karlsson ◽  
Keyword(s):  
High Latitude ◽  
Large Scale ◽  
Small Scale ◽  
Strong Correlations ◽  
Polar Cap ◽  
Plasma Flows ◽  
Ionospheric Convection ◽  
Local Closure ◽  
Scale Characteristics

Abstract. We examine 14 cases of an interesting type of extremely high latitude aurora as identified in the precipitating particles measured by the DMSP F13 satellite. In particular we investigate structures within large-scale arcs for which the particle signatures are made up of a group of multiple distinct thin arcs. These cases are chosen without regard to IMF orientation and are part of a group of 87 events where DMSP F13 SSJ/4 measures emissions which occur near the noon-midnight meridian and are spatially separated from both the dawnside and duskside auroral ovals by wide regions with precipitating particles typical of the polar cap. For 73 of these events the high-latitude aurora consists of a continuous region of precipitating particles. We focus on the remaining 14 of these events where the particle signatures show multiple distinct thin arcs. These events occur during northward or weakly southward IMF conditions and follow a change in IMF By. Correlations are seen between the field-aligned currents and plasma flows associated with the arcs, implying local closure of the FACs. Strong correlations are seen only in the sunlit hemisphere. The convection associated with the multiple thin arcs is localized and has little influence on the large-scale convection. This also implies that the sunward flow along the arcs is unrelated to the overall ionospheric convection.

scholarly journals Container Networking Performance Analysis for Large-Scale User Behavior Simulation

2019 ◽  
Vol 07 (10) ◽  
pp. 136-146
Author(s):  
Yifang Ji ◽  
Guomin Zhang ◽  
Shengxu Xie ◽  
Xiulei Wang
Keyword(s):  
Performance Analysis ◽  
Large Scale ◽  
User Behavior ◽  
Behavior Simulation

scholarly journals Convectively Coupled Kelvin Waves: From Linear Theory to Global Models

2015 ◽  
Vol 73 (1) ◽  
pp. 407-428 ◽  
Author(s):  
Michael J. Herman ◽  
Zeljka Fuchs ◽  
David J. Raymond ◽  
Peter Bechtold
Keyword(s):  
Composite Structures ◽  
Large Scale ◽  
Kelvin Waves ◽  
Radiosonde Data ◽  
3D Analysis ◽  
Kelvin Wave ◽  
Scale Characteristics ◽  
Precipitation Anomalies ◽  
Convective Inhibition ◽  
Ecmwf Model

Abstract The authors analyze composite structures of tropical convectively coupled Kelvin waves (CCKWs) in terms of the theory of Raymond and Fuchs using radiosonde data, 3D analysis and reanalysis model output, and annual integrations with the ECMWF model on the full planet and on an aquaplanet. Precipitation anomalies are estimated using the NOAA interpolated OLR and TRMM 3B42 datasets, as well as using model OLR and rainfall diagnostics. Derived variables from these datasets are used to examine assumptions of the theory. Large-scale characteristics of wave phenomena are robust in all datasets and models where Kelvin wave variance is large. Indices from the theory representing column moisture and convective inhibition are also robust. The results suggest that the CCKW is highly dependent on convective inhibition, while column moisture does not play an important role.

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