Discussions

This is where you can start discussions around security visualization topics.

NOTE: If you want to submit an image, post it in the graph exchange library!

You might also want to consider posting your question or comment on the SecViz Mailinglist!

Discussion Entries

Money Mule, Phishing and AFF SPAMclouds

Mainly as a bit of fun, I thought it would be interesting to sort some of our SPAM into distinct groups and make some wordclouds, or more specifically SPAMclouds from the content of the spam.
Attached is the cloud for SPAM attempting to recruit Money Mules.

You can see the Phishing and Advance Fee Fraud (AFF) clouds and the full story here http://honeynet.org.au/?q=spamclouds

ben

Money Mule SPAMcloud

CISSE Working Group Outcomes - Security Visualization Challenges

At the CISSE 2009 conference, we held a workshop on Security Visualization, during which we identified a number of research problems associated with security visualization. You can find them listed below. Tomorrow, we will identify use-cases for security visualization. If you have any use-cases that you want us to consider, comment on here!

Security Visualization Research Problems


Important Realization: Visualization is generally an add-on to a specific problem or task. This dilutes the research community, since there are data visualizations of many different areas of interest.

Data Acquisition

  • Data normalization: aggregation, filter, and augmentation. Common formats are needed that span the requirements.

  • Accessing data (transport problems)

  • Data security issues (confidentiality, integrity)

  • Context collection

  • Real-time processing (collection and visualization)

  • Data disposal / destruction

  • What to do with missing data / gaps?

  • “Cleaning” data

Visual Representations

  • Time series representations instead of snap-shots

  • Are three-dimensional / interactive visualizations more intuitive / easier to use than, for example, a set of two dimensional representations?
  • Education of Expert Witnesses: how to present scientific data and explain visualizations in terms that are understandable by juries, prosecutors, and judges

  • The challenge of transitioning data into evidence is an on-going problem. The starting point is raw data, which is then transformed into a visual representation, which is then contextually interpreted as information. There are many issues with this process, including appropriate representation of actual or relational time sequence and the provability of the linkage between the raw data and the interpreted information.

  • Photo classification: A challenge is the emerging area of photo-realistic cartoons or imagined figures, which are getting so life-like that they are crossing the boundary from good to evil when used inappropriately.

  • Extremely large data set analyses, focusing on making them faster while maintaining accuracy

  • Integration of many variables into a useful visualization, where many means 4 or more variables.

Visual Interpretations

  • “Bridging the Gap”: creating visualizations that are intuitively interpretable by non-trained people. This implies needed integration of knowledge from the fields of sociology, cultural anthropology, learning theory, neuroscience, psychology, disability amelioration, etc.

  • Understanding visual representations: interpreting actual meaning from the visualization can be challenging. Research into how to make this more intuitive is needed, as is research in how to best educate analysts. Additionally, better human-interpretable visualizations are needed.

  • Visualization as an accelerator of identification of anomaly judgment (OK versus Not OK)

  • Interpretative visualization tools

  • Enable a better interpretation of complexities in relationships and interactions in data sets.

Overall Problems

  • Scientific validation of tools (Type 1 and Type 2 error rates; perhaps tool certification as being built with “pure” software, perhaps Common Criteria type certification)

  • Need to create an inter-disciplinary community of visualization researchers that talk to each other and share methods so that the wheel does not need to re-invented between communities

help debugging tcpdump2csv.pl?

I'm trying to use afterglow 1.5 on a gentoo system and running into an issue that I hope you can help me figure out.
When I read a dump file into tcpdump2csv.pl, using the switches documented, I get absolutely no output. If I turn on debug, I get my tcpdump lines, preceded by "ERROR:" as below:
ERROR: 2009-05-04 18:37:28.332949 In ethertype IPv4 (0x0800), length 93: (tos 0x0, ttl 61, id 0, offset 0, flags [DF], proto UDP (17), length 77)
ERROR: 74.63.208.3.53 > 216.245.196.14.56383: 14710 1/0/0 mail.lab.spb.ru. A 77.234.201.82 (49)
If I run with tcpdump -ttnnlr, I get a little closer to the lines in your documentation, in that the timestamp is on the same line as the capture info:
ERROR: 1241462458.413252 In ethertype IPv4 (0x0800), length 93: 74.63.208.3.53 > 216.245.196.14.43954: 7712 1/0/0 A 195.128.50.36 (49)

There is no description of what the error is, and still no CSV output is appearing.
If it makes a difference, I am running with tcpdump 4.0. If I can add an ebuild for afterglow 2.0 for the gentoo world, I will give that a try and see if I get a little further.

VizSec 2009 - submission deadline approaching

The 6th International Workshop on Visualization for Cyber Security (VizSec) will be held October 11, 2009 in Atlantic City, NJ, USA in conjunction with VisWeek 2009.

The deadline for full papers (12 pages) is May 8, 2009. The deadline for short papers (6 pages) is May 22, 2009.

Please see the web site for formatting instructions, templates and information on how to submit your paper.

http://vizsec.org/vizsec2009/

Best,
-john

Sphere Of Influence

Take a look at my site www.manntechcomputersinc.com We have developed a visualization tool for pix/asa and snort. It maps ip to geographical locations countries (source or destination), anonymous proxies , sat providers, regions etc. We repsent countries by flags and provide users to add their own icons. I'd be interested to hear what people think....

Screen Shot Sphere of Influence

Conficker.C UDP P2P Traffic

The chart represent several hours of conficker's P2P Udp activity, it relates destination address with dest UDP used.

Conficker.C UDP P2P Traffic

conficker.c - ccTLD attractor

This is my smart analysis about the first 20days of April 2009 ccTLD (country code top level domain) generated by the algorithm used by worm for pseudo random domain name generation.
The following chart show the frequency for each ccTLD. As you can see there is a sort of attractor for some ccTLD such as AG, BO, LC, HN, PE, and TW. A singular point is for DJ ccTLD domain. For more information http://extraexploit.blogspot.com. This kind of analysis I think that is usefull for get evidence as indicator of conficker.c activities inside your corporate network.

Feedback are well come.

Regards

conficker.c - ccTLD attractor

SecViz Mailinglist - Subscribe Today!

SecViz has a mailinglist!

The charter for the list is the same as for the SecViz Web site: share, discuss, challenge, and learn about security visualization. The mailinglist should help to have more in-depth discussions and get quicker responses on specific topics. I am looking forward to some good discussions around visualization applications, visualization methods, use-cases, etc. Fire away!

Note that the list keeps a public archive!

VizSec 2009 Call For Participation

VizSec 2009
Workshop on Visualization for Cyber Security
October 11, 2009 / Atlantic City, NJ USA
http://vizsec.org/vizsec2009/

The 6th International Workshop on Visualization for Cyber Security is a forum that brings together researchers and practitioners in information visualization and security to address the specific needs of the cyber security community through new and insightful visualization techniques. Co-located this year with IEEE InfoVis/Vis/VAST, VizSec will continue to provide opportunities for the two communities to collaborate and share insights into providing solutions for security needs through visualization approaches. Accepted papers will be published by the IEEE and archived in the IEEE Digital Library. The authors of the best papers will be invited to extend and revise their paper for journal publication in a special issue of Information Visualization.

This year our focus is on advancing Visualization for Cyber Security as a scientific discipline. While art, engineering, and intuitions regarding the human element will always remain important if we are to obtain useful cyber security visualizations, advances in the scientific practice of research are needed. The scientific aspects of visualization for cyber security draw both on empirical observation (similar to many natural and social sciences) and formal science (such as the formal derivations in mathematics). Barriers confronting current researchers include concerns about available data, lack of a common agreement about what constitutes sound experimental design, the difficulties of measuring the relative effectiveness of security visualizations in practice, and the lack of a common understanding of user requirements. While many researchers are making progress in these and other critical areas, much work yet remains.

What To Submit

Papers offering novel contributions in security visualization are solicited. Papers may present technique, applications, practical experience, theory, or experiments and evaluations. Papers are encouraged on technologies and methods that have been demonstrated to be useful for improving information systems security and that address lessons from actual application. We encourage papers that report results on visualization techniques and systems in solving all aspects of cyber security problems, including how visualization applies to:
*Different aspects of security: software, networks and log files (e.g., Internet routing, packet traces and network flows, intrusion detection alerts, attack graphs, application security, etc.)
*Application of visualization techniques in formalizing, defining and analyzing security policies
*Forensic analysis, correlating events, cyber-defense task analysis
*Computer network defense training and offensive information operations
*Building rules, feature selection, and detecting anomalous activity
*Software, software security, and viruses
*Deployment and field testing of VizSec systems
*Evaluation and user testing of VizSec systems
*User and design requirements for VizSec systems
*Lessons learned from development and deployment of VizSec systems
*“Field Research” Best Practices
*Interaction with domain experts – best practices, lessons learned
*Differentiating the needs of different domains and time frames
*Best practices for obtaining and sharing potentially sensitive data for purposes of visualization and assessment, including how to approach personal privacy, regulatory, and organizational issues
*Metrics and measurements (e.g., criteria for the relative effectiveness of cyber visualizations)
*Handling large datasets, scalability issues, and providing real time or near-real time visualizations
Accepted papers will be published by the IEEE and made available through the IEEE Digital Library.

Paper Format:

Submitted papers must not substantially overlap papers that have been published or that are simultaneously submitted to a journal or a conference with proceedings. All submissions should be appropriately anonymized (i.e., papers should not contain author names or affiliations, or obvious citations). Submissions are to be made to the submission web site at http://www.vizsec.org/vizsec2009/submit. Only pdf files will be accepted. Papers should be formatted using the IEEE templates (see http://www.vizsec.org/vizsec2009/ for instructions).
*Full papers should be at most 12 pages, including the bibliography and appendices.
*Short papers should be at most 6 pages, including the bibliography and appendices.
Committee members are not required to read the appendices, and so the paper should be intelligible without them. Submissions not meeting these guidelines risk rejection without consideration of their merits. Authors of accepted papers must guarantee that their papers will be presented at the conference.

Papers must be received by the deadline of April 24, 2009, for long papers and May 22, 2009, for short papers.

Journal Special Issue

The authors of the best papers from the accepted program will be invited to extend and revise their paper for a special issue of Information Visualization (IVS), an international, peer-reviewed journal publishing articles on fundamental research and applications of information visualization. These papers will be chosen by the program committee.

Paper Award

There will be an award for the best paper from the accepted program. The best paper award will be given to the paper judged to have the highest overall quality. A key element of the best paper selection process will be whether the results are believed to be repeatable by other scientists based on the algorithms and data provided in the paper. This award will be chosen by the program committee.

Scholarships

A limited number of scholarships will be available for students and first-year faculty who have had papers accepted to VizSec.

Organizing Committee

General Chair Deborah Frincke, Pacific Northwest National Laboratory and University of Washington
Program Co-Chair: Carrie Gates, CA Labs
Program Co-Chair: John Goodall, Secure Decisions Division of Applied Visions
Papers Chair: Robert Erbacher, Utah State University

Program Committee

Richard Beijtich, General Electric, USA
Greg Conti, United States Military Academy, USA
Marc Dacier, Symantec Research Labs, France
Anita D’Amico, Secure Decisions div. of Applied Visions, USA
Ron Dilley, Information Security Professional, USA
Dave Ebert, Purdue University, USA
Glenn Fink, Pacific Northwest National Lab, USA
John Gerth, Stanford University, USA
Warren Harrop, Swinburne Univ. of Technology, Australia
Mark Haselkorn, University of Washington, USA
Richard Johnson, Microsoft, USA
Richard Kemmerer, UC Santa Barbara, USA
Toby Kohlenberg, Intel, USA
Florian Mansmann, University of Konstanz, Germany
Raffael Marty, Splunk, USA
Doug Maughan, Department of Homeland Security, USA
John McHugh, Dalhousie Univ., Canada, and Univ. NC, USA
Jan P. Monsch, Dublin City University, Ireland
Chris North, Virginia Tech, USA
Stephen North, AT&T Research, USA
Sean Peisert, UC Davis, USA
Greg Schmidt, SPADAC, USA
George Tadda, Air Force Research Lab, USA
Ed Talbot, Sandia National Laboratories, USA
Joanne Treurniet, Defence R&D Canada, Canada
Grant Vandenberghe, Defence R&D Canada, Canada
Kirsten Whitley, Department of Defense, USA
Pak Chung Wong, Pacific Northwest National Lab, USA
Tamara Yu, Massachusetts Institute of Technology, USA

http://vizsec.org/vizsec2009/

DNS tunnel detection

I've been frustrated with large-scale traffic analysis tools for a long time. I recently did some DNS traffic analysis to study possibilities for detecting DNS tunnels.

I wrote up my traffic analysis thoughts in a study of dns. The result of that paper was thresholds of typical DNS hostname request lengths, at least for my traffic. Not satisfied with a static threshold, I built a visualization for the traffic using processing. The writeup of the visualization is available in part ii.

A picture is attached of dns hostname requests when ssh'ing over dns using dns2tcp. The code is available as well; you can visualize your own captures or live traffic off the wire.

enjoy.
tranq

Visualization of DNS tunnel traffic