-------- Forwarded Message -------- Subject: [AISWorld] HICSS 2021 "Machine Learning and Cyber Threat Intelligence and Analytics Minitrack" Date: Sat, 11 Jul 2020 11:07:20 -0500 From: Raymond Choo raymond.choo@fulbrightmail.org To: aisworld@lists.aisnet.org, aisworld-request@lists.aisnet.org

https://hicss.hawaii.edu/tracks-54/software-technology/#machine-learning-and...

*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 Only theoretical and technical papers describing previously unpublished, original, state-of-the-art research, and not currently under review by a conference or a journal will be considered.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