Author Guidelines

Author Guidelines
Contribution Link
Safety and Security of Software Using Machine Learning in Cyber-physics System

Submission instructions

Q: What types of contributions are accepted?
This workshop accepts regular research papers within 6 pages, short papers within 4 pages and position papers within 2 pages.
Submitted papers must conform to the two-column IEEE conference publication format. Templates for LaTeX and Microsoft Word are available from http://www.ieee.org/conferences_events/conferences/publishing/templates.html: please use the letter format template and conference option.
Papers should be submitted in the PDF format: they must not exceed page limit. Submissions will be handled via EasyChair. Papers must neither have been previously accepted for publication nor be under submission in another conference or journal. For your paper to be published in the proceedings, at least one of the authors of the paper must register for the conference and confirm that she/he will present the paper in person.
Describe the review and evaluation process to decide which submissions to accept: All papers will be evaluated in terms of the following criteria:

  • Originality or potential for impact: The submission presents a particularly novel collation of historical work, insight or approach towards new/future work, and/or is potentially disruptive of current practice or common knowledge.
  • Soundness: The submission makes a coherent argument, substantiated by historical analysis, cogent analytical argument, or appropriately-scoped initial empirical results.
  • Relevance: The submission appropriately considers and puts itself in context with respect to the relevant literature.
  • Topics of interest include development, analysis methods, technologies, and machine learning models to enhance the reliability, safety, and security of software in CPS, and are not limited to:
    1. Reliability, Security, and Safety of Software in CPS
    2. Anomaly Detection Using Log
    3. Deep Learning for Program Synthesis
    4. Inroads in Testing Access Control Using Deep Learning
    5. Vulnerability Management
    6. Modern Software Quality Assurance
    7. Secure Development Life Cycle
    8. Security Architecture and Design
    9. Software Security Using Deep Learning
    10. Privacy-preserving Machine Learning and Data Analytics
    11. Intrusion Detection Using Machine Learning
    12. Testing, Verification, and Validation Using Deep Learning
    13. Software Quality, Metrics and Measurements, Estimation and Prediction of Quality/Reliability
    14. Dependability, Survivability, and Resilience Study
    15. Supporting Tools and Automation in CPS
    16. Empirical Study in CPS
    17. Novel Interdisciplinary Research in CPS