[AISWorld] AMCIS 2023 CFP

[McLeod, Alexander J]

Security Analytics
Industry is relying more heavily on Information Systems and Analytics to discover security anomalies using Big Data and Machine Learning. The intersection of these technological and statistical tools provides opportunities for security researchers to advance Information Systems Security and Analytics knowledge. This mini-track seeks papers focusing on opportunities for research which informs, creates or analyzes large datasets using statistical techniques and tools to uncover unauthorized access, attempts to modify stored or in process information, use of malware and any measures needed to detect, document, or counter security threats. Papers analyzing or assessing audit trails and other security information to identify system events indicating violations of system security as well as adversarial statistical and machine learning applications will also be considered. Theoretical development, empirical findings, methodologies or case studies seeking to examine security analytics are various forms of acceptable research.

Alexander McLeod, Texas State University, a_m919 at txstate.edu Tahir Ekin, Texas State University, t_e18 at txstate.edu Barbara Hewitt, Texas State University, bh05 at txstate.edu

https://new.precisionconference.com/amcis23c

https://amcis2023.aisconferences.org/wp-content/uploads/2022/12/AMCIS_2023__Original_Template.doc

Full papers must describe completed research. Completed research papers will be submitted to a conference mini track where they will be peer-reviewed using a double-blind system and presented in a session format. Each session will consist of three or four competitive papers accepted through the review process. Sessions employ a standard format of presentation by an author and general audience discussion. Full papers must not exceed 10 pages (approx. 5,000 words) and must conform to the AMCIS 2023 submission template. Full papers that are accepted will be published in their entirety in the conference proceedings.