posted by organizer: akageekgirl || 2470 views || tracked by 1 users: [display]

LASER 2017 : Learning from Authoritative Security Experiment Results (LASER) 2017

FacebookTwitterLinkedInGoogle

Link: http://2017.laser-workshop.org/
 
When Oct 18, 2017 - Oct 19, 2017
Where Arlington, VA
Submission Deadline Jul 15, 2017
Notification Due Sep 1, 2017
Final Version Due Nov 22, 2017
Categories    cybersecurity   experimentation   science   experiments
 

Call For Papers

The Learning from Authoritative Security Experiment Results (LASER) Workshop invites papers that seek to improve experimental methods in the field of cybersecurity. The goal of this workshop is to improve the rigor and quality of security experimentation by providing a venue where cybersecurity researchers can discuss experimental methods and present research that exemplifies sound scientific practice.

This year we particularly encourage papers in three areas:

* Well-designed security experiments, with positive or negative results.
* Experimental techniques that help address common sources of error.
* Replications (successful or failed) of previously published experiments.

Well-done security experiments, aside from the immediate value provided by the result of the experiment, can serve as methodological examples for future work. We therefore invite submissions reporting on the results of carefully designed and executed studies. Reviewers will be advised to judge the work of the quality of the design and how well that design was carried out rather than whether the result validates the original hypothesis. In other words, both positive and negative results will be accepted, provided the methodology is sound.

LASER also solicits papers that give new insights into common sources of error in security experiments. Awareness of common pitfalls allows researchers to avoid them, and to notice them in others' work during peer review. In machine learning, for example, it is well known that testing an algorithm on the same data that was used for training will result in overfitting and give an inflated view of the algorithm's performance. What sorts of mistakes in cybersecurity experimentation can lead us astray?

Finally, replications of prior work are an essential part of the scientific process: all experimentation has some natural level of error, and replication helps validate the soundness of existing work and provide a deeper understanding of the conditions under which published results hold. Replications of important security results are therefore a natural fit for LASER. In order to ensure fairness, we ask that submissions that fail to replicate prior work include a discussion of the authors' efforts to contact the authors of the original study and reconcile the differences.

Papers that include an analysis of a data set are encouraged to make said data available, as well as any analysis code. This helps ensure that work presented at LASER will can be meaningfully checked and reproduced by other researchers.

Well-written papers on these topics, as well as any others consistent with the workshop's goals of advancing the state of the art in cybersecurity experimentation, will be presented at the workshop and included in the proceedings.

Paper Format

Submissions may be 6-10 pages long including tables, figures, and references. Short papers of up 3-6 pages long are also welcome. Papers should be submitted via HotCRP. Submissions must be in PDF format using USENIX conference paper formatting guidelines. Reviewing will be double-blind, so authors should anonymize their papers and remove obvious self-references.

Authors are encouraged to use the “structured abstract” format (described below). Structured abstracts help make different submissions comparable, and allow readers to quickly understand the overall structure, methods, and conclusions of a study. A structured abstract should contain concise statements, presented in a consistent structure to help quickly facilitate an understanding of the study. Essential elements of structured abstracts are: background, aim, method, results, and conclusions:

Background. State the background and context of the work described in the paper.

Aim. State the research question, objective, or purpose of the work in the paper.

Method. Briefly summarize the method used to conduct the research, including subjects, procedures, data, and analytical methods.

Results. State the outcome of the research using measures appropriate for the study conducted.

Conclusions. State the surprises, lessons learned as a result of the study, and recommendations for future work.



Workshop Format

Because of the complex and open nature of the experimental methods, LASER is designed to be a workshop in the traditional sense. Presentations are expected to be interactive with the expectation that a substantial amount of this time may be given to questions and audience discussion, rather than pure presentation. Papers and presentations should be conducive to discussion, and the audience is encouraged to participate. To promote a high level of interaction, attendance is limited. First preference is given to participating authors. Additional seats are available on a first-come first-served basis.

Additionally, a pre-workshop version of the paper will be distributed to attendees. However, authors are encouraged to incorporate comments from the discussions at the workshop into final, camera-ready versions of their paper, to be published publicly by USENIX. Camera-ready paper versions are not due until approximately one month after the workshop.

Student Scholarships

LASER also seeks to foster learning in experimental methods for the next generation of computer security researchers. As such, LASER offers a limited number of student scholarships for participation.

Important Dates

Paper Submissions Due: July 15, 2017 (Firm date: there will be NO Extensions)

Paper Decisions to Authors: September 1, 2017

Pre-Workshop Papers Due: September 29, 2017

Final Papers Due: November 22, 2017

Related Resources

Intelligent Computing-Based Time Series 2025   Intelligent Computing: Special Issue: Intelligent Computing-Based Time Series Analysis for Cybersecurity
FLAIRS 2025   Florida Artificial Intelligence Research Society
From Data to Decision: Empowering Ecosys 2025   The International Society for Ecological Modelling Global Conference:
ACNS 2025   23rd International Conference on Applied Cryptography and Network Security - deadline 2
Insights 2024   Fifth Workshop on Insights from Negative Results in NLP
ASIACCS 2025   The 20th ACM ASIA Conference on Computer and Communications Security - deadline 2
Security 2025   Special Issue on Recent Advances in Security, Privacy, and Trust
Applied Sciences (MDPI) SI:Cybersecurity 2024   Applied Sciences (MDPI) Special Issue - Cybersecurity: Advances in Security and Privacy Enhancing Technology
IEEE-Ei/Scopus-ITCC 2025   2025 5th International Conference on Information Technology and Cloud Computing (ITCC 2025)-EI Compendex
ICSTTE 2025   2025 3rd International Conference on SmartRail, Traffic and Transportation Engineering (ICSTTE 2025)