Workshop Overview

The irreversible dependence on computing technology has paved the way for cybersecurity’s rapid emergence as one of modern society’s grand challenges. To combat the ever-evolving, highly-dynamic threat landscape numerous academics and industry professionals are systematically searching through billions of log files, social media platforms (e.g., Dark Web), malware files, and other data sources to preemptively identify, mitigate, and remediate emerging threats and key threat actors. Artificial Intelligence (AI)-enabled analytics has started to play a pivotal role in sifting through large quantities of these heterogeneous cybersecurity data to execute fundamental cybersecurity tasks such as asset management, vulnerability prioritization, threat forecasting, and controls allocations. However, the volume, variety, veracity, and variety of cybersecurity data sharply contrasts with conventional data sources. Moreover, industry and academic AI-enabled cybersecurity analytics are often siloed. To this end, this workshop aims to being to gather academic and practitioners to share, disseminate, and communicate completed research papers, work in progress, and review articles pertaining to AI-enabled cybersecurity analytics.

Submission Guidelines

All submissions must be in PDF format and formatted according to the new Standard ACM Conference Proceedings Template. Submissions are limited to a 4-page initial submission, excluding references or supplementary materials. Upon acceptance, the authors are allowed to include an additional page (5-page total) for that camera ready version that accounts for reviewer comments. Authors should use supplementary material only for minor details that do not fit in the 4 pages, but enhance the scientific reproducibility of the work (e.g., model parameters). Since all reviews are double-blind, and author names and affiliations should NOT be listed. For accepted papers, at least one author must attend the workshop to present the work. Based on the reviews received, accepted papers will be designated as a contributed talk (four total, 15 minutes each), or as a poster. All accepted papers will be posted on the workshop website. The final date for submission is May 10, 2021. 

List of Topics

This workshop aims to being to gather academic and practitioners to share, disseminate, and communicate completed research papers, work in progress, and review articles pertaining to AI-enabled cybersecurity analytics. Areas of interest include, but are not limited to:

• Static and/or dynamic malware analysis and evasion
• IP reputation services (e.g., blacklisting)
• Anomaly and outlier detection
• Phishing detection (e.g., email, website, etc.)
• Dark Web analytics (e.g., multi-lingual threat detection, key threat actor identification)
• Spam detection
• Large-scale and smart vulnerability assessment
• Real-time threat detection and categorization
• Real-time alert correlation for usable security
• Weakly supervised and continual learning for intrusion detection
• Adversarial attacks to automated cyber defense
• Automated vulnerability remediation
• Internet of Things (IoT) analysis (e.g., fingerprinting, measurements, network telescopes)
• Misinformation and disinformation
• Deep packet inspection
• Automated mapping of threats to cybersecurity risk management framework

Each manuscript must clearly articulate their data (e.g., key metadata, statistical properties, etc.), analytical procedures (e.g., representations, algorithm details, etc.), and evaluation set up and results (e.g., performance metrics, statistical tests, case studies, etc.). Providing these details will help reviewers better assess the novelty, technical quality, and potential impact. Making data, code, and processes publicly available to facilitate scientific reproducibility is not required. However, it is strongly encouraged, as it can help facilitate a culture of data/code sharing in this quickly developing discipline.

Committees

Program Committee (Listed Alphabetically Based on Last Name)

• Benjamin Ampel, University of Arizona
• Dr. Hyrum Anderson, Microsoft
• Dr. Victor Benjamin, Arizona State University
• Dr. Elias Bou-Harb, University of Texas, San Antonio
• Dr. Yidong Chai, Tsinghua University
• Dr. Sriram Chelleppan, University of South Florida
• Dr. Sven Krasser, CrowdStrike
• Dr. Weifeng Li, University of Georgia
• Dr. Yunji Liang, Northwestern Polytechnical University
• Dr. Xiaojing Liao, Indiana University Bloomington
• Dr. Sudip Mittal, University of North Carolina, Wilmington
• Dr. Edward Raff, Booz Allen HamiltonDr. Ethan Rudd, FireEye
• Dr. Ankit Shah, University of South Florida
• Steven Ullman, University of Arizona
• Dr. Ziming Zhao, University of Buffalo
• Dr. Lina Zhou, University of North Carolina, Charlotte
• Dr. Hongyi Zhu, University of Texas, San Antonio

Organizing committee

• Dr. Sagar Samtani, Indiana University
• Dr. Jay Yang, Rochester Institute of Technology
• Dr. Hsinchun Chen, University of Arizona

Publication

Accepted AI4Cyber-KDD papers will be listed on the Workshop Webpage (https://ai4cyber-kdd.com/). 

Contact

All questions about submissions should be emailed to Dr. Sagar Samtani at ssamtani@iu.edu.