##ATTENTION## The Workshop will be held VIRTUALLY and the papers will normally be PUBLISHED in IEEE XPLORE.

The IEEE International Workshop on Big Data Analytics for Cyber Threat Hunting (CyberHunt 2020) is organized by the Digital Security Research Group of the University of Oslo (Norway) in conjunction with the 2020 IEEE International Conference on Big Data (IEEE BigData 2020). The workshop will be held VIRTUALLY during Dec 10-13, 2020.

CyberHunt 2020 Website: http://cyberhunt2020.cyberhunt.no/
IEEE BigData Website: http://bigdataieee.org/BigData2020/

Cyber-crimes against critical infrastructure, operational technology, IoT, and large organizations have become more sophisticated and are executed at machine speed. In response to that, cyber defenders transition from manual and reactive approaches to more automated and proactive. A key element for building a robust security posture against adversarial attacks is Cyber threat intelligence (CTI). CTI allows security teams to benefit from increased situational awareness and thus minimize their organizations' attack surfaces. Based on the detection maturity of an organization, such intelligence can update cyber defense components in an automated manner based on the established trust between the entity sharing the intelligence and the entity consuming it, or in more proactive approaches such as threat hunting and risk assessment. For example, TTPs used in adversarial activities can support threat hunting efforts where the objective is to detect unidentified malicious activity that evaded existing security solutions. The CyberHunt workshop aims to present (potentially AI-focused) new research in the areas of cyber-threat hunting, cyber-threat intelligence, and security orchestration, automation, and response.

#Research Topics#
Any novel research related to cyber threat intelligence, incident and threat response, threat hunting, and security automation and orchestration is welcome.

Some suggested topics are:

Cyber Threat Intelligence (strategic, operational, tactical, technical)
Models for forecasting cyber-attacks and measuring impact
Threat actor groups & techniques
Semantic modeling, data representation, and fusion for CTI
Models that take into consideration Deception and Uncertainty in cyber-attack attribution
Indicators of compromise and how to detect/mitigate
Visualization techniques for intelligence analysis and investigation
Legal, privacy and ethical factors in intelligence analysis
Data analytics for security
Threat Hunting
Intrusion and anomaly detection and prevention
Incident Response
Monetization of cybercrime
Open Source tools
Relevant geopolitical cybersecurity research
Security Automation
Security Orchestration

#The Organizing Committee#
Vasileios Mavroeidis – University of Oslo, Norway (vasileim@ifi.uio.no) - Co-chair
Audun Jøsang – University of Oslo, Norway (audun.josang@mn.uio.no) - Co-chair
Nils Gruschka - University of Oslo, Norway (nilsgrus@ifi.uio.no) - PC-chair
Mateusz Zych - University of Oslo, Norway (mateusdz@ifi.uio.no) - PC-chair assistant
Tamas Bisztray - University of Oslo, Norway (tamasbi@ifi.uio.no) - Publicity chair

#Program Committee#

* Andrii Shalaginov - Center for Cyber- and Information Security, Norwegian University of Science and Technology
* Audun Joøsang - University Of Oslo
* Blerim Rexha - University of Prishtina
* Fabio Massimo Zannaro - University Of Oslo
* Fatbardh Veseli - Goethe University Frankfurt / Capgemini Germany
* Jassim Happa - Department of Computer Science, University of Oxford
* Mateusz Zych - University of Oslo
* Nils Gruschka - University Of Oslo
* Panagiotis Karampelas - Hellenic Air Force Academy
* Siri Bromander - Mnemonic AS
* Tamas Bisztray - University Of Oslo
* Vasileios Mavroeidis - University Of Oslo

#Paper Guidelines#
The authors are invited to submit a full-length paper (up to 10 pages) or short papers (up to 6 pages).
Papers should be formatted to the IEEE Computer Society Proceedings Manuscript Formatting Guidelines. You can find more information at the official IEEE BigData Webpage - http://bigdataieee.org/BigData2020/CallPapers.html