Maritime transports play a critical role in international trade and commerce.Massive vessels sailing around the world continuously generate vessel trajectory data that contain rich spatial–temporal patterns of vessel...Maritime transports play a critical role in international trade and commerce.Massive vessels sailing around the world continuously generate vessel trajectory data that contain rich spatial–temporal patterns of vessel navigations.Analyzing and understanding these patterns are valuable for maritime traffic surveillance and management.As essential techniques in complex data analysis and understanding,visualization and visual analysis have been widely used in vessel trajectory data analysis.This paper presents a literature review on the visualization and visual analysis of vessel trajectory data.First,we introduce commonly used vessel trajectory data sets and summarize main operations in vessel trajectory data preprocessing.Then,we provide a taxonomy of visualization and visual analysis of vessel trajectory data based on existing approaches and introduce representative works in details.Finally,we expound on the prospects of the remaining challenges and directions for future research.展开更多
Mitigating increasing cyberattack incidents may require strategies such as reinforcing organizations’ networks with Honeypots and effectively analyzing attack traffic for detection of zero-day attacks and vulnerabili...Mitigating increasing cyberattack incidents may require strategies such as reinforcing organizations’ networks with Honeypots and effectively analyzing attack traffic for detection of zero-day attacks and vulnerabilities. To effectively detect and mitigate cyberattacks, both computerized and visual analyses are typically required. However, most security analysts are not adequately trained in visualization principles and/or methods, which is required for effective visual perception of useful attack information hidden in attack data. Additionally, Honeypot has proven useful in cyberattack research, but no studies have comprehensively investigated visualization practices in the field. In this paper, we reviewed visualization practices and methods commonly used in the discovery and communication of attack patterns based on Honeypot network traffic data. Using the PRISMA methodology, we identified and screened 218 papers and evaluated only 37 papers having a high impact. Most Honeypot papers conducted summary statistics of Honeypot data based on static data metrics such as IP address, port, and packet size. They visually analyzed Honeypot attack data using simple graphical methods (such as line, bar, and pie charts) that tend to hide useful attack information. Furthermore, only a few papers conducted extended attack analysis, and commonly visualized attack data using scatter and linear plots. Papers rarely included simple yet sophisticated graphical methods, such as box plots and histograms, which allow for critical evaluation of analysis results. While a significant number of automated visualization tools have incorporated visualization standards by default, the construction of effective and expressive graphical methods for easy pattern discovery and explainable insights still requires applied knowledge and skill of visualization principles and tools, and occasionally, an interdisciplinary collaboration with peers. We, therefore, suggest the need, going forward, for non-classical graphical methods for visualizing attack patterns and communicating analysis results. We also recommend training investigators in visualization principles and standards for effective visual perception and presentation.展开更多
基金supported in part by the National Natural Science Foundation of China(No.41801313,41901397,and 61872388).
文摘Maritime transports play a critical role in international trade and commerce.Massive vessels sailing around the world continuously generate vessel trajectory data that contain rich spatial–temporal patterns of vessel navigations.Analyzing and understanding these patterns are valuable for maritime traffic surveillance and management.As essential techniques in complex data analysis and understanding,visualization and visual analysis have been widely used in vessel trajectory data analysis.This paper presents a literature review on the visualization and visual analysis of vessel trajectory data.First,we introduce commonly used vessel trajectory data sets and summarize main operations in vessel trajectory data preprocessing.Then,we provide a taxonomy of visualization and visual analysis of vessel trajectory data based on existing approaches and introduce representative works in details.Finally,we expound on the prospects of the remaining challenges and directions for future research.
文摘Mitigating increasing cyberattack incidents may require strategies such as reinforcing organizations’ networks with Honeypots and effectively analyzing attack traffic for detection of zero-day attacks and vulnerabilities. To effectively detect and mitigate cyberattacks, both computerized and visual analyses are typically required. However, most security analysts are not adequately trained in visualization principles and/or methods, which is required for effective visual perception of useful attack information hidden in attack data. Additionally, Honeypot has proven useful in cyberattack research, but no studies have comprehensively investigated visualization practices in the field. In this paper, we reviewed visualization practices and methods commonly used in the discovery and communication of attack patterns based on Honeypot network traffic data. Using the PRISMA methodology, we identified and screened 218 papers and evaluated only 37 papers having a high impact. Most Honeypot papers conducted summary statistics of Honeypot data based on static data metrics such as IP address, port, and packet size. They visually analyzed Honeypot attack data using simple graphical methods (such as line, bar, and pie charts) that tend to hide useful attack information. Furthermore, only a few papers conducted extended attack analysis, and commonly visualized attack data using scatter and linear plots. Papers rarely included simple yet sophisticated graphical methods, such as box plots and histograms, which allow for critical evaluation of analysis results. While a significant number of automated visualization tools have incorporated visualization standards by default, the construction of effective and expressive graphical methods for easy pattern discovery and explainable insights still requires applied knowledge and skill of visualization principles and tools, and occasionally, an interdisciplinary collaboration with peers. We, therefore, suggest the need, going forward, for non-classical graphical methods for visualizing attack patterns and communicating analysis results. We also recommend training investigators in visualization principles and standards for effective visual perception and presentation.
