Data Science for Intrusion Detection and Digital Forensics

DSIDDF 2019


Data Mining & Analysis Databases & Information Systems



The goal of the DSIDDF workshop is to bring together researchers and engineers from all over the world to discuss their latest results in the practical application of applied data science tools, techniques, algorithms and solutions for solving problems in intrusion detection/prevention and digital forensics.
We invite original research contributions that advance the state-of-the-art as well as position papers, which pose a new direction or present a controversial point of view. Topics of interest include, but are not limited to:
• Artificial intelligence used in the field of safety and security
• Impact of detection and response measures on the investigation of cyber attacks
• Detection and response to cyber-physical attacks on critical infrastructure
• Cyberattack countermeasures, especially offensive responses
• Data security and privacy in critical systems
• Malware detection, modelling and analysis methods
• Situational awareness
• Machine learning for security
Submitted papers must be original contributions that are unpublished and are not currently under consideration for publication by other venues. Papers will be part of the CEUR proceedings (ceur-ws.org). Papers will undergo a blind peer review process, coordinated by the Scientific Committee. Papers must have 5-8 pages of two-columns A4 format, written in English, using LaTeX or MS Word (templates available at workshop website).
DSIDDF Workshop is organized as part of the Information Technologies – Application & Theory (ITAT) Conference 2019. Note, that each accepted paper requires at least a workshop registration.