Visual Analytics for Electromagnetic Situation Awareness in Radio Monitoring and Management

Zhao, Ying; Luo, Xiaobo; Lin, Xiaoru; Wang, Hairong; Kui, Xiaoyan; Zhou, Fangfang; Wang, Jinsong; Chen, Yi; Chen, Wei

doi:10.1109/tvcg.2019.2934655

Cited by 52 publications

(16 citation statements)

References 71 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This paper uses the SIR [ 31 ] model to obtain the propagation impacts of network nodes in order to verify the correctness of the ranking method. In the simulation process [ 32 ], at the beginning of this paper, node

is initialized as the infected state, and other nodes are set to vulnerable states. In each iteration, the infected node tries to infect all the neighboring nodes in its vulnerable state with probability β .…”

Section: Methodsmentioning

confidence: 99%

A Novel Method to Rank Influential Nodes in Complex Networks Based on Tsallis Entropy

Xue-gong

Zhou

Liao

et al. 2020

Entropy

View full text Add to dashboard Cite

With the rapid development of social networks, it has become extremely important to evaluate the propagation capabilities of the nodes in a network. Related research has wide applications, such as in network monitoring and rumor control. However, the current research on the propagation ability of network nodes is mostly based on the analysis of the degree of nodes. The method is simple, but the effectiveness needs to be improved. Based on this problem, this paper proposes a method that is based on Tsallis entropy to detect the propagation ability of network nodes. This method comprehensively considers the relationship between a node’s Tsallis entropy and its neighbors, employs the Tsallis entropy method to construct the TsallisRank algorithm, and uses the SIR (Susceptible, Infectious, Recovered) model for verifying the correctness of the algorithm. The experimental results show that, in a real network, this method can effectively and accurately evaluate the propagation ability of network nodes.

show abstract

Section: Methodsmentioning

confidence: 99%

A Novel Method to Rank Influential Nodes in Complex Networks Based on Tsallis Entropy

Xue-gong

Zhou

Liao

et al. 2020

Entropy

View full text Add to dashboard Cite

show abstract

“…Visualization has become an increasingly important research area due to its wide range of applications in many disciplines [19,23,25,26,31,38,41,[53][54][55][56][57][58][59][60]62]. Recently, the visualization and visual analytics community is eliciting considerable interests in blockchain data presentation and analysis, leading to several pioneering studies [45].…”

Section: Blockchain Data Visualizationmentioning

confidence: 99%

SilkViser: A Visual Explorer of Blockchain-based Cryptocurrency Transaction Data

Zhao¹

2020

Preprint

Self Cite

View full text Add to dashboard Cite

<p>Many blockchain-based cryptocurrencies provide users with online blockchain explorers for viewing online transaction data. However, traditional blockchain explorers mostly present transaction information in textual and tabular forms. Such forms make understanding cryptocurrency transaction mechanisms difficult for novice users (NUsers). They are also insufficiently informative for experienced users (EUsers) to recognize advanced transaction information. This study introduces a new online cryptocurrency transaction data viewing tool called SilkViser. Guided by detailed scenario and requirement analyses, we create a series of appreciating visualization designs, such as paper ledger-inspired block and blockchain visualizations and ancient copper coin-inspired transaction visualizations, to help users understand cryptocurrency transaction mechanisms and recognize advanced transaction information. We also provide a set of lightweight interactions to facilitate easy and free data exploration. Moreover, a controlled user study is conducted to quantitatively evaluate the usability and effectiveness of SilkViser. Results indicate that SilkViser can satisfy the requirements of NUsers and EUsers. Our visualization designs can compensate for the inexperience of NUsers in data viewing and attract potential users to participate in cryptocurrency transactions.</p>

show abstract

“…In summary, whether implemented by visually or other analytical methods, proper definition and comparison in behavior patterns are of paramount importance [36].…”

Section: Visualization On Behavior Patternsmentioning

confidence: 99%

Owleyes: A Visual Analytics System for Functions and Connection Patterns of IPv4 Addresses in Networks

Yan

He²,

Liu

et al. 2020

IEEE Access

View full text Add to dashboard Cite

Netflow log files commonly contain massive transfer records in tiny time interval, making analytical works complex and burdensome. By combining human cognition abilities with computerized techniques, visual analytics systems have become efficient tools for showing network states and locating abnormal behaviors. However, traditional visual analytics systems tend to be designed for solving certain problems and unable to synthesize various types of data sources. Despite recent advances in network security visualization, academia still starves for a proper solution to visualize IPv4 address behavior modes and IPv4 connection patterns within limited drawing space. Thus, we propose a visual analytics system called 'Owleyes' which reprocesses Netflow log data with simple statistical operations in basic dimensions and fulfills the aforementioned requirements with proper novel graphs such as 'sunburst-hive-plot graph' (SHG) and link-wheel graph (LW). The SHG provides a stable and comparable means of visualizing connection patterns efficiently in a limited drawing space. The LW represents the hourly connection counts of main ports in a specific IPv4 connection during one day. With the use case dealing with the ChinaVis 2016 Challenge I data, the efficiency and practicability of Owleyes are demonstrated. INDEX TERMS Visual analytics, network security, sunburst-hiveplot graph, link wheel graph, user-centric interaction. HAIBO HU received the master's degree in software engineering and the Ph.D. degree in computer science from Chongqing University, China, in 2004 and 2012, respectively. He is currently an Associate Professor with the School of Big Data and Software Engineering, Chongqing University. He is also a Research Associate with the Key Laboratory for Dependable Service Computing in Cyber Physical Society of the Ministry of Education, China. His current research interests include software engineering, pattern recognition, semantic web, and visual analytics.

show abstract

Visual Analytics for Electromagnetic Situation Awareness in Radio Monitoring and Management

Cited by 52 publications

References 71 publications

A Novel Method to Rank Influential Nodes in Complex Networks Based on Tsallis Entropy

A Novel Method to Rank Influential Nodes in Complex Networks Based on Tsallis Entropy

SilkViser: A Visual Explorer of Blockchain-based Cryptocurrency Transaction Data

Owleyes: A Visual Analytics System for Functions and Connection Patterns of IPv4 Addresses in Networks

Contact Info

Product

Resources

About