BigCyber – 2023

To be held in conjunction with the 2023 IEEE International Conference on Big Data (Big Data 2023), Dec 15-18, 2023

Security analysts must process high velocity and veracious data for early, ideally left of an exploit, detection of cybersecurity events, such as attacks, data-theft, etc. The problem is challenging, given the constantly evolving threat landscape. Even with advanced monitoring, sophisticated persistent attackers can spend as many as 146 days in a system before being detected. Existing systems’ lack of unified organizational view causes information flooding and overwhelms a security analyst with false alarms. We need techniques that reduce an analyst’s cognitive load.

Even in mid-sized environments, big data crossing the organizational boundary need to be mined, examined, and analyzed to create ‘Analyst Augmentation Systems’, which will aid security analysts in their day-to-day operations.

This workshop aims to bring together researchers from Cybersecurity and Big Data to help further homeland security’s missions of anticipation, interdiction, prevention, preparedness, and response. We invite submissions in areas (but not limited to) related to knowledge extraction from cybersecurity intelligence big datasets, fast analysis of security datasets for relevant information, and using this knowledge for various cybersecurity activities like early attack detection, mitigation, remediation, and forensics.

Workshop Schedule

Bigcyber 2023 Workshop Schedule

Important dates

  • Oct 22, 2023: Due date for full workshop papers submission
  • Nov 1, 2023: Notification of paper acceptance to authors
  • Nov 20, 2023: Camera-ready of accepted papers
  • Dec 15-18, 2023: Workshops

Formatting details: 

1. We accept the standard IEEE format.
2. Page limit is up to 10 pages.
3. All workshop papers are included in IEEE Big Data conference proceedings.

Paper Submission:

Please submit a full-length paper (up to 10 pages in IEEE 2-column format, with reference pages counted in the 10 pages ) through the online submission system.