Sunday, October 1
Conference check-in: Lakeshore Ballroom, Conference Hotel, 2pm-6:30pm
Day 1, Monday, October 2 (Both parallel session rooms are in Lakeshore Ballroom)
|7:30am-5:30pm||Conference Check-in, Hallway outside the Lakeshore Ballroom|
|7:30am – 8:30am||Breakfast|
|8:30am – 8:45am||Welcome speech|
|8:45am – 9:45am||Keynote #1: Paths to Secure and Resilient Critical Infrastructure. Dr. Greg Shannon.|
|10:15am– 11:45am||Room 1||Room 2|
|Session 1A: Machine Learning and Cybersecurity||Session 1B: Social Media Analytics I|
Paper: Neuro-Logic Learning for Relation Reasoning over Event Knowledge Graph.
Paper: Vehicle Classification in Intelligent Transportation Systems Using Deep Learning and Seismic Data.
Paper: An Evolutionary Algorithm for Adversarial SQL Injection Attack Generation.
Paper: Dynamic Causal Modeling and Predictive Analysis for the COVID-19 Pandemic.
Paper: AI-based MultiModal to Identify State-linked Social Media Accounts in the Middle East: A Study on Twitter.
Paper: Controllable News Comment Generation based on Attribute Level Contrastive Learning.
|12pm – 1:30pm||Lunch break|
|1:30pm – 3:30pm||Room 1||Room 2|
|Session 2A: Cyber Threat Intelligence I||Session 2B: Artificial Intelligence for Cybersecurity|
Paper: Building the Future of Intelligence, Surveillance, and Reconnaissance (ISR) Collections: The Development and Evaluation of a Collaborative ISR Tool to Support Intel Analysts.
Paper: Mapping Exploit Code on Paste Sites to the MITRE ATT&CK Framework: A Multi-label Transformer Approach. [Candidate for the best paper award]
Paper: An Overview of Cybersecurity Knowledge Graphs Mapped to the MITRE ATT&CK Framework Domains.
Paper: Extracting Actionable Cyber Threat Intelligence from Twitter Stream. [Candidate for the best paper award]
Paper: Assessing the Vulnerabilities of the Open-Source Artificial Intelligence (AI) Landscape: A Large-Scale Analysis of the Hugging Face Platform.
Paper: Change Management using Generative Modeling on Digital Twins.
Paper: Learning to Listen and Listening to Learn: Spoofed Audio Detection through Linguistic Data Augmentation.
Paper: Named Entity Recognition for Epidemiological Investigation in COVID-19.
|3:30pm – 4:00pm||Coffee break|
|4:00pm – 5:30pm||Room 1||Room 2|
|Session 3A: Novel Defense||Session 3B: Human Behavior|
Paper: Disrupting Ransomware Actors on the Bitcoin Blockchain: A Graph Embedding Approach.
Paper: Deep Learning Based Behavior Anomaly Detection within the Context of Electronic Commerce. [Candidate for the best paper award]
Paper: Towards Low-Barrier Cybersecurity Research and Education for Industrial Control Systems.
Paper: Shoulder Surfing on Mobile Authentication: Perception vis-a-vis Performance from the Attacker’s Perspective.
Paper: SoK: Cybersecurity Regulations, Standards and Guidelines for the Healthcare Sector.
Paper: A Stage Model for Understanding Phishing Victimization Behavior in Embedded Training.
|6:30pm – 8:30pm||Banquet and Best Paper Awards (Lakeshore Ballroom)|
Day 2, Tuesday, October 3 (Both parallel session rooms are in Lakeshore Ballroom)
|8am – noon||Conference Check-in, Hallway outside the Lakeshore Ballroom|
|7:30am – 8:30am||Breakfast|
|8:30am – 9:30am||Keynote #2: Responsible AI: The Interplay between Algorithms, Data, People, and Policy. Dr. Heng Xu.|
|9:30am – 10:00am||Coffee break|
|10:00am – 11:30am||Room 1||Room 2|
|Session 4A: Social Media Analytics II||Session 4B: Cyber Threat Intelligence II|
Paper: Adversarial Topic-Aware Memory Network for Cross-Lingual Stance Detection.
Paper: A Continual Learning Framework for Event Prediction with Temporal Knowledge Graphs. [Candidate for the best paper award]
Paper: Style-Driven Multi-Perspective Relevance Mining Model for Hotspot Reprint Paragraph Prediction.
Paper: Context-Augmented Key Phrase Extraction from Short Texts for Cyber Threat Intelligence Tasks.
Paper: Boosting Domain-Specific Question Answering through Weakly Supervised Self-Training.
Paper: PCEN: Potential Correlation-Enhanced Network for Multimodal Named Entity Recognition. [Candidate for the best paper award]
|11:30am – 12:15pm||Session 5: Short Papers|
Paper: A Two-Stage Prompt Learning Method for Jointly Predicting Topic and Personality.
Paper: Building Human Digital Twins: Cases for Intelligence and Security Informatics.
Paper: MalwareDNA: Simultaneous Classification of Malware, Malware Families, and Novel Malware.
|12:15pm – 1:30pm||Lunch|
Paths to Secure and Resilient Critical Infrastructure
Greg Shannon, Ph.D.
Chief Cybersecurity Scientist and Directorate Fellow, Idaho National Laboratory
In this talk we consider emerging practical paths to ensuring secure and resilient critical infrastructure. Recall that our goal is to make it harder for adversaries to find and exploit vulnerabilities in our critical infrastructures and easier for us to build and operate secure and resilient critical infrastructure. For context, we’ll focus on research that was influenced/initiated in response to a request from the U.S. Congress in 2020 to develop a national strategy for cyber-informed engineering. That research includes developing and proliferating the use of cyber-informed engineering, new reference architectures, and new categories of cyber-physical weaknesses in critical infrastructure. Given recent advances in AI, we close by considering how advances in inductive and deductive AI accelerate and complicate practical paths to ensuring the security and resilience of critical infrastructure.
Greg Shannon is a Chief Cybersecurity Scientist at the Idaho National Laboratory (Battelle Energy Alliance, LLC) since 2021. He is also the Chief Science Officer for the Cybersecurity Manufacturing Innovation Institute at the University of Texas at San Antonio. Greg has a Ph.D. in Computer Sciences from Purdue University and a certificate in National and International Security Policy for Senior Executives from Harvard University. He has held various leadership roles, including Chief Scientist for the CERT Division at Carnegie Mellon University and Assistant Director for Cybersecurity Strategy at the White House Office of Science and Technology Policy. He is a founding board member of Women in CyberSecurity Inc. and serves on the U.S. Air Force Scientific Advisory Board. He has a strong background in research, policy development, and strategic planning in the cybersecurity domain.
Responsible AI: The Interplay between Algorithms, Data, People, and Policy
Heng Xu, Ph.D.
The complex tradeoffs and interrelations between algorithms, data, people, and policy in AI research are crucial considerations that impact the development, deployment, and societal impact of AI systems. Designing responsible AI systems requires careful consideration of these interrelations, as tradeoffs in one area can impact the others. In this talk, I will discuss the opportunities and challenges of converging knowledge and methods from multiple fields to address scientific and societal needs for Responsible AI. I will also explore some of the complex interrelations between algorithms, data, people and policy, grounded in our recent work on data privacy and fairness in machine learning. Finally, I will conclude with a reflection on how we could facilitate progress in this space, to navigate these complexities and develop AI technologies that are robust, fair, privacy-aware, secure, and aligned with societal values.
Dr. Heng Xu is a Professor of Management in the Warrington College of Business at the University of Florida. Her recent research focuses on privacy protection, data ethics, and fairness in machine learning. She has published over 100 research papers across different fields such as Business, Computer Science, and Psychology. Her research has been awarded multiple competitive grants from multiple federal funding agencies including Defense Advanced Research Projects Agency, National Institute of Health, and National Science Foundation. Dr. Xu’s work has received many awards, including the Management Information Systems Quarterly’s Impact Award (2021) for her interdisciplinary privacy research, Woman of Achievement Award in IEEE Big Data Security (2021) for her outstanding research contributions and mentoring women in the field, IEEE ITSS Leadership Award (2020) for her extensive scholarly and community-building efforts, the Operational Research Society’s Stafford Beer Medal (2018) for her work on healthcare privacy, National Science Foundation’s CAREER award (2010) for her work on digital privacy, and many best paper awards and nominations at various conferences.
Dr. Xu joined the University of Florida from the American University, where she served as a Professor and Director of Cybersecurity Governance Center in Kogod School of Business. She previously served as a faculty member at the Pennsylvania State University, as well as a program director at the National Science Foundation. She also served on a broad spectrum of national leadership committees including co-chairing the Federal Privacy R&D Inter-agency Working Group in 2016, and serving on the National Academies Committee on Open Science in 2017-2018.