Authors may submit long papers (up to 8 pages) or short papers (up to 4 pages) for presentation. Exceptions to page limits can be made on a case-by-case basis.
Submission should follow the IEEE double-column format: for information and insturctions see the IEEE publications page at http://www.ieee.org/conferences_events/conferences/publishing/templates.html
(link opens in new window). Submission format is PDF.
SYMPOSIUM OBJECTIVE
The Symposium will include paper presentations and a panel discussion.
The Symposium will be part of HICSS-53 at the Grand Wailea on Maui.
KEYNOTE SPEAKER DR. ANDREW B. WHINSTON
This Symposium enables practitioners and academics to present emerging cybersecurity big data research and challenges in domains such as data collection and processing, data analytics, data handling, machine learning, deep learning, and visualization; as well as to present and discuss potential cybersecurity big data research topics and methodologies of interest to the cybersecurity community.
Machine Learning and Analytics cover all forms that leverage or require Big Data for support, including defensive measures, potential threat identification applications, or deep learning opportunities. They also include, but are not limited to, methodologies, techniques, and impacts of real-time processing for incident detection and/or prevention, data review for incident and anomaly detection, post incident response analytics, and IT audit related analytics. Data handling covers research and case studies into process and procedures. Visualization will look at all aspects of research related to visualizing the data, such as temporal, geographical, threat, actor, event based, and other data types. Topics related to data include areas such as logs, network traffic data (PCAP), system process data, system memory data, and even complete virtualized system snapshots.
REVIEW PROCESS
SYMPOSIUM FORMAT
Dr. Andrew B. Whinston, the Hugh Roy Cullen Centennial Chair in Business Administration and the Director of the Center for Research in Electronic Commerce at The University of Texas at Austin, will be giving a keynote address at this symposium titled “A unique perspective on connecting security, bitcoin, and the need for the attackers to build a reputation of honest dealing, with additional discussion on Bandit Models.”.
Submission deadline EXTENDED: November 18, 2019
Papers should be emailed to AZSecure-HICSS@list.arizona.edu. Authors of accepted papers will present their work during the Symposium. Due to the limited time available, short papers will have 15 minutes to present and long papers 20 minutes. Because we are seeking the latest in current ongoing research, authors retain the copyright to their work, although they may cite it as a peer reviewed conference paper. We do ask permission to host accepted papers on the Symposia website.
CALL FOR PAPERS
Presented by Dr. Hsinchun Chen, Regents' Professor and Thomas R. Brown Chair of MIS, Director, Artificial Intelligence Laboratory, University of Arizona
Dr. Mark Patton, Senior Lecturer in MIS, Program Administrator, AZSecure Cybersecurity Fellowship Program, University of Arizona
E. Choma, & R. Frank. "Geographic distribution and content analysis of targets on five hacking-focused online discussion forums." HICSS Symposium on Cybersecurity Big Data Analytics, 2019.
C. Joslyn, S. Aksoy, D. Arendt, L. Jenkins, B. Praggastis, E. Purvine, M. Zalewski. "High Performance Hypergraph Analytics of Domain Name System Relationships." HICSS Symposium on Cybersecurity Big Data Analytics, 2019.
N. Munaiah, J. Pelletier, S. Su, S. Jay Yang, A. Meneely. "A Cybersecurity Dataset Derived from the National Collegiate Penetration Testing Competition." HICSS Symposium on Cybersecurity Big Data Analytics, 2019.
J. Acosta, M. Akbar, & A. Fielder. "Comprehensive Data Analytics for Threat Detection." HICSS Symposium on Cybersecurity Big Data Analytics, 2018.
C. Gardner, A. Waliga, D. Thaw, S. Churchman. "Using Camouflaged Cyber Simulations as a Model to Ensure Validity in Cybersecurity Experimentation." HICSS Symposium on Cybersecurity Big Data Analytics, 2018.
N. Mogire, R.K. Minas, & M.E. Crosby. "Automatically Unaware: Using Data Analytics to Detect Physiological Markers of Cybercrime." HICSS Symposium on Cybersecurity Big Data Analytics, 2018.
M. DeYoung, R. Marchany, & J. Tront. "Network Security Data Analytics for Logged Events." HICSS Symposium on Cybersecurity Big Data Analytics, 2017.
C. Hicks, & N. Beebe. "Labeling the National Collegiate Cyber Defense Competition Dataset for Cybersecurity Research." HICSS Symposium on Cybersecurity Big Data Analytics, 2017.
L. Kaati, T. Isbister, & K. Cohen. "Gender Classification with Data Independent Features in Multiple Languages." HICSS Symposium on Cybersecurity Big Data Analytics, 2017.
M. Salman, B. Welch, J. Tront, D. Raymond, R. Marchany. "Designing PhelkStat: Big Data Analytics for System Event Logs." HICSS Symposium on Cybersecurity Big Data Analytics, 2017.
B. Walls. "A Look at Data Feature Extraction and Classification Techniques for Predicting Botnet Assaults." HICSS Symposium on Cybersecurity Big Data Analytics, 2017.