-------- Forwarded Message --------
https://hicss.hawaii.edu/tracks-54/software-technology/#machine-learning-and-cyber-threat-intelligence-and-analytics-minitrack
*HICSS 2021 "Machine Learning and Cyber Threat Intelligence and
Analytics
Minitrack"*
With the digitalization of things, a significant amount of data is
collected from different security monitoring solutions as well as
systems
that were compromised or have been used to facilitate an attack
(e.g. a
cloud server). Thus, advanced cyber threat intelligence and
analytical
techniques (e.g. threat intelligence, big data and machine
learning
techniques) are key to real-time detection and mitigation of cyber
security
incidents, and to the collection and analysis of cyber security
incident
related information.
This minitrack will focus on cutting-edge research from both
academia and
industry, with a particular emphasis on novel techniques and tools
to
perceive, reason, learn and act on a wide range of data collected
from
different attack (or attempts), sophisticated advanced persistent
threat
campaigns, etc. Only theoretical and technical papers describing
previously
unpublished, original, state-of-the-art research, and not
currently under
review by a conference or a journal will be considered.
Topics of interest include, but are not limited to:
- Blockchain and its application in cyber security
- Detection and analysis of advanced threat actors tactics,
techniques
and procedures
- Application of machine learning tools and techniques in cyber
threat
intelligence
- Theories and models for detection and analysis of advanced
persistent
threats
- Automated and smart tools for collection, preservation and
analysis of
digital evidences
- Threat intelligence techniques for constructing, detecting, and
reacting to advanced intrusion campaigns
- Applying machines learning tools and techniques for malware
analysis
and fighting against cyber crimes
- Intelligent incident response tools, techniques and procedures
for
contemporary technologies, such as cloud and cyber-physical
systems
- Intelligent analysis of different types of data collected from
different layers of network security solutions
- Threat intelligence in cyber security domain utilising big data
solutions such as Hadoop
- Intelligent methods to manage, share, and receive logs and data
relevant to variety of adversary groups
- Interpretation of cyber threat and forensic data utilising
intelligent
data analysis techniques
- Infer intelligence of existing cyber security data generated by
different monitoring and defence solutions
- Automated and intelligent methods for adversary profiling
- Automated integration of analysed data within incident response
and
cyber forensics capabilities
Important Dates for Paper Submission
July 15 — Papers due
August 15 — Reviews due
August 22 — Minitrack Chairs’ decisions due
August 23 — Notifications to authors
September 4 — Revision due for papers accepted with mandatory
changes
September 10 — Minitrack Chairs’ final decisions due for papers
with
mandatory changes
September 11 — Notifications to authors of revised papers
September 22 — Final manuscripts due
January 4 — Publications of full conference proceedings
Minitrack Co-Chairs:
*Kim-Kwang Raymond Choo* (Primary Contact)
University of Texas at San Antonio
raymond.choo@utsa.edu
*Ali Dehghantanha*
University of Guelph
adehghan@uoguelph.ca
*Glenn Dietrich*
University of Texas at San Antonio
Glenn.Dietrich@utsa.edu
_______________________________________________
AISWorld mailing list
AISWorld@lists.aisnet.org