PDF | Networked computers are ubiquitous, and are subject to attack, misuse, and ply, information visualization turns data into interactive graphical displays. Security data visualization also plays key role in emerging fields such as data science lesforgesdessalles.info Gather Raw Network. Data .  Greg Conti. Security Data Visualization: Graphical Techniques for Network Analysis.
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Network Security. Data Visualization . lesforgesdessalles.info~owen/ Research/Conference%20Publications/honeynet_IAWpdf. 0. Security Visualization. Past Ben Shneiderman, The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations. In Security Visualization and Enabler Books Emerge lesforgesdessalles.info . data visualization tools to your process. Greg Conti, in his groundbreaking gem, Security Data Visualization: Graphical. Techniques for Network Analysts, sums it .
If the goal is to improve security metrics before jumping to the step of setting up security visualization toolbox or gathering data. Nations Title Agency, Inc. We will see that none of these technologies are sufficient in our quest to defend our networks and information. There are tons of operational security metrics for optimizing operations and to highlight any operational issues related to vulnerability management. Shows the number of observations of a particular variable for given interval. Short papers describing practical applications of security visualization are solicited.
This is where all the current metrics is looked to understand the gaps. Below section highlights some techniques from Stephen Few for reference. Section 4. Security Data Visualization Data Preparation phase — 1 week.
The use cases might also take in to consideration the statistical methods for future trend predictions. Y to determine if they tend to move in the same or opposite directions. Security Data Visualization Deviation: Categorical subdivisions are compared again a reference.
A bar chart may be used for this comparison. A scatter plot is typically used for this message. Comparison between observations represented by two variables X. A cartogram is a typical graphic used. For example. Frequency distribution: Shows the number of observations of a particular variable for given interval.
Nominal comparison: Comparing categorical subdivisions in no particular order. Geographic or geospatial: Comparison of a variable across a map or layout.
A histogram. Security Data Visualization Few. Once the graph is determined it can be easily developed using tools like R which is covered in detail in Appendix C.
If the visualization requires additional tools section 6 explains setting up visualization toolbox. Management Laboratory. Another example of visualization is shown below with the Pareto plot.
Spear Phishing. Below example shows how visual timeline analysis helps explain the chronology of a spear phishing attack. Security Data Visualization In some cases the visualization can be simple flow chart representing incidents in cyber kill chain to identify which parts of the kill chain was successful so the organization can strengthen the controls. One of the key strengths of security teams is access to enterprise log data.
Security Data Visualization This step involves continuous improvement with feedback from the stakeholders and availability of new data. Human mind by evolution is trained to identify patterns and anomalies using visualization. As a simple example having darker colors Blue or Purple color in the graph instead of other light colors like Yellow helped in security part of the presentation since it was fitting well with the rest of the presentation.
Security tools provide lot of numeric data. The other aspect is to understand the different visualization methods which are available. Knowledge gathering phase Statistical knowledge — 1 week.
As long as the team understands the visualization lot of effort is not necessary for the aesthetics. The other key aspect is running large set of data through Gaussian distribution or Monte Carlo simulation models for predictions. This aspect is not as important in this project since the focus is on finding anomalies and not necessarily communicating to different sets of audience. There are good books on network security monitoring which might augment the domain knowledge along with work experience.
Security Data Visualization Information Security Domain Expertise — Ongoing In this case of finding anomalies understanding security log data is the foundational skills required for security data visualization.
The security monitoring experience will enable to team to baseline the activities and understand the anomalies. The team may require some brainstorming session to come up with goals and use cases for anomaly detection. Data Preparation phase — 1 week. This is ongoing activity where the team will keep updating their knowledge in this area.
For anomaly detection use cases the security monitoring domain knowledge is more important. The domain knowledge will enable the team to create as many hypotheses as possible. This is where all the current process for anomaly detection is looked to pingbalaji gmail. Retrieved November Security Data Visualization understand the gaps.
Once you have a set of hypotheses within the scope the team can start exploring the possibilities of creating graphs and visualizing.
For this use case of Firewall log data visualization to identify anomalies the below GIAC paper has examples using Afterglow.
It is important to start small on a particular type of log. For example the initial use case might be to identify anomalies in firewall log data using visualization. SSHD brute force attempts.
This iterative process will assist with finding anomalies. Below flowchart from Marty. As the team starts using Afterglow and other tools like R. Feedback and fine-tune — Ongoing Feedback is very vital in this process to share with the team.
Gobi and the other tools can be used to visualize. Security Data Visualization steps created false-positives will save a lot of time for the team. The team can slowly move in to correlating of all events and logs to find anomalies and keep iteratively improving the process.
There is lot of scope to continuously improve based on feedback and progress. Security Data Visualization 5. In this paper as one example. The good news is. If security practitioners are passionate and believe there can be new ways to analyze and visualize data.
I hope more security practitioners learn these data analysis and visualization techniques and by sharing these techniques. Security visualization can be used in many areas in information security. Another benefit. Security monitoring. Security data visualization also plays key role in emerging fields such as data science. November Retrieved September Visualization Is Power. Properties and best uses of visual encoding. Addison-Wesley Graphic Sociology.
The Sight and Sound of Cybercrime. How to get and show meaningful metrics for a scrum team. Piqua Leader-Dispatch Conway. The Office For Creative Research. August 1. Use Cases. Security Data Visualization Mondrian.
Discovery and Visual Analytics. Many Eyes. Graphics Press. Books and Other Resources. Edward R . Evidence and Narrative. Security Data Visualization Black Hat.
ISBN Edward R Open DNS presentation. Beautiful Evidence. The Visual Display of Quantitative Information 2nd ed.
Visual Explanations: Images and Quantities. ISBN 7. Visualising Data. Retrieved December 6. Selecting the Right Graph for Your Message. The 1s and 0s behind cyber warfare. Graph Selection Matrix. Retrieved December 8. Retrieved December 5. Tapping the Power of Visual Perception. The training was focused on how to use security visualization to help security analysts visualize security logs. The other inspirations are from many TED talks were many of the TED presenters use visualization to tell powerful stories.
Imagine if you can implement the same visualization to show how security incidents have risen over time. Motion Chart data visualization link: It was a learning moment when the R code was executed and the browser opened with the motion chart.
Another good example is gapminder. It can be accessed at http: There is a lot of guidance in the resources. Imagine a presentation for senior management with similar dynamic security metrics for your organization. Data analysis features on this web site serve as a good example on how security metrics can be extended to a dynamic format creatively.
By providing this dynamic content. There are a lot of books and leaders in this space who can be followed to keep up to date in security data visualization area. These are just few inspirations which enlighten us on the value of security data visualization. Security Data Visualization If you need additional information visit the data visualization reference network for wealth of information in this field which is visually catalogued: Some of the operational security metrics are good for technical audience and CISO for enhancing the services.
Depending on the organization. Information security metrics has to be customized to each and every organization.
There are tons of operational security metrics for optimizing operations and to highlight any operational issues related to vulnerability management. It contains dedicated chapters on security visualization.
The below materials and books are valuable resources for selecting and developing good information security metrics. Below are some of the books and publications that provide a methodology on creating a security metrics work program and candidate metrics which can be chosen to improve the current metrics or to create new metrics.
The security metrics program leader can be empowered with all the data and metrics which are already available. Security Scorecards Hoehl. Security metrics: Andrew Jaquith: Security Metrics Jaquith. NIST Rev 1 has candidate measures metrics which is a useful short list. Security Data Visualization It is beneficial to have a security metrics program within the security team with a process owner instead of generating different ad-hoc metrics from different sub-teams.
Once all the available information security metrics are reviewed. It is useful for the security metrics process owner to conduct a brainstorming session to update the information security metrics and use creative and innovative security visualization to display the data.
There are many other books and resources in the reference section like CIS metrics and Metricon metrics. This is certainly a valuable source of information for reference.
It also covers the relevant legislation and contracts that organizations must comply with. J This book focuses on security visualization which is the topic of the second part of this paper. Data Driven Security Jacobs. The idea was to highlight some important resources available on information security metrics.
It provides a lot of guidance. It provides clear examples. In this example. Date ID Severity Type: In this script. Security Data Visualization This script was adapted to meet incident metrics. View incidentpriority1 This displays the records. This sorts the data based on date. Creating a Basic Plot plot totalincidentsByDate. Building Security Data Visualization Toolbox There are many security data visualization tools available. This is just a short example to show how R can be used for effectively visualizing security incident trend metrics.
This creates the chart showing how many incidents are created per day. The website http: Security Data Visualization The plot is used to chart how many incidents are created per day. Barcharts and Mosaic Plots. This does not require any coding and very simple for security practitioner to generate interactive visualizations.
Applied security visualization also has lot of examples and guidance on developing security visualization using most of the tools in DAVIX. Mondrian Once you have the data. Some of the sophisticated ones are Tableau. It offers an easy-to-use API with several pingbalaji gmail. Security Data Visualization The book Marty. The below web page have numerous additional examples of information security data visualization for getting inspiration on use cases and applications of security data visualization: OpenDNS Data Visualization Framework OpenGraphiti is a free and open source 3D data visualization engine for data scientists to visualize semantic networks and to work with them.
The below white-paper explains in detail the OpenGraphiti framework https: References for R R. Appendix C. Security Data Visualization associated libraries to create custom-made datasets. It leverages the power of GPUs to process and explore the data and sits on a homemade 3D engine. Some examples include the analysis of security data. Getting Started. Sep Nov TXUS Oct NL Oct IN Nov AE Nov Oct GB Nov JP Nov COUS Oct DE Sep AU Nov VAUS Oct WAUS Oct GB Oct MDUS Sep GB Sep FLUS Nov Tysons Tysons.
AKUS Sep NVUS Sep IT Nov Dec I start by showing what big data looks like for security, how the history of using security for big data is tightly linked to the progress in big data itself. I talk about machine learning and artificial intelligence and show some of the limits and dangers of how we currently apply machine learning in security and how we can apply data visualization to help analysts better understand data.
I then go on to peek a little bit into my magic 8 ball to see how security big data environments might look in the future and finish the presentation with posing a few challenges to the community about security for big data problems. I have a questionnaire, for my thesis, aimed at people who have experience in Cyber Security, Visualization or HCI design or both. I would really appreciate if you can take some time out and fill out the questionnaire. Big data and security intelligence are the two very hot topics in security.
We are collecting more and more information from both the infrastructure, but increasingly also directly from our applications. This vast amount of data gets increasingly hard to understand. Terms like map reduce, hadoop, spark, elasticsearch, data science, etc.
But what are those technologies and techniques? We will see that none of these technologies are sufficient in our quest to defend our networks and information. Data visualization is the only approach that scales to the ever changing threat landscape and infrastructure configurations. Using big data visualization techniques, you uncover hidden patterns of data, identify emerging vulnerabilities and attacks, and respond decisively with countermeasures that are far more likely to succeed than conventional methods.
Something that is increasingly referred to as hunting. The attendees will learn about log analysis, big data, information visualization, data sources for IT security, and learn how to generate visual representations of IT data. The workshop is being heavily updated over the next months.
Check back here to see a list of new topics:. The section on big data is covering the following: Raffael Marty is vice president of security analytics at Sophos, and is responsible for all strategic efforts around security analytics for the company and its products. He is based in San Francisco, Calif. Marty is one of the world's most recognized authorities on security data analytics, big data and visualization.
His team at Sophos spans these domains to help build products that provide Internet security solutions to Sophos' vast global customer base. Previously, Marty launched pixlcloud, a visual analytics platform, and Loggly, a cloud-based log management solution.
With a track record at companies including IBM Research, ArcSight, and Splunk, he is thoroughly familiar with established practices and emerging trends in the big data and security analytics space. Marty is the author of Applied Security Visualization and a frequent speaker at academic and industry events. Zen meditation has become an important part of Raffy's life, sometimes leading to insights not in data but in life. We recently posted a case study of how a Fortune company is using Security Visualization as a front end to their various data collection systems.
The Security Visualization allows the company's analysts to look at 's of thousands of correlations each day and apply human pattern recognition to spot the "needles in the haystack". These are threats that are designed to avoid traditional intrusion and event management. Once the potential threat is identified and the log data is carved down to just the logs that are relevant, that subset of log data is then attached to a case study and delivered to case investigation for further evaluation.
In addition to identifying and carving down to just the relevant logs, the security visualization also makes it easier to communicate the findings to the extended team.
In this situation data is imported from several sources. Those sources include intrusion detection systems e. Symantec in addition to correlation systems e.
Security Visualization allows the analysts to hunt for unknown and unexpected threats. Threats such as time staged attacks, diagonal attacks, cluster attacks, octal jump attacks, embedded activity attacks, etc. This case study is recorded and can be viewed at http: I prepared an online survey as a part of my phd thesis. However, since this subject is relatively new I can not find anybody who may fill this survey around me in Turkey.
The survey is in Google Forms, at link https: It is not very short: It may take around 20 minutes but it is easy to fill, mostly composed of multi selection questions. Uncompleted survey results are not saved so the participants should complete the survey. Although we ask questions related to security systems and security visualization systems used to understand the visualization requirements. The survey, in general, does not include questions that give personal discomfort.
No tracking information such as email or organization name is asked during the survey. More descriptive information about how the survey results will be used exists in the starting page. So, please do not hesitate to fill, due to your privacy concerns. I hope experts of this forum may help me by filling the survey during a coffee break.
I need to take feedback soon, before my next thesis committee. I appreciate your help to a newbie security visualization researcher me: The 13th IEEE Symposium on Visualization for Cyber Security VizSec is a forum that brings together researchers and practitioners from academia, government, and industry to address the needs of the cybersecurity community through new and insightful visualization and analysis techniques.
VizSec provides an excellent venue for fostering greater exchange and new collaborations on a broad range of security- and privacy-related topics. The purpose of VizSec is to explore effective and scalable visual interfaces for security domains such as network security, computer forensics, reverse engineering, insider threat detection, cryptography, privacy, user assisted attacks prevention, compliance management, wireless security, secure coding, and penetration testing.
Full papers describing novel contributions in security visualization are solicited. Papers may present techniques, applications, practical experience, theory, analysis, experiments, or evaluations. We encourage the submission of papers on technologies and methods that promise to improve cyber security practices, including, but not limited to:. Short papers describing practical applications of security visualization are solicited.
We encourage the submission of papers discussing the introduction of cyber security visualizations into operational context, including, but not limited to:. Cyber security practitioners from industry, as well as the research community, are encouraged to submit case studies. Poster submissions may showcase late-breaking results, work in progress, preliminary results, or visual representations relevant to the VizSec community. The poster program will be a great opportunity for the authors to interact with the attendees and solicit feedback.