CCNI Workshop

GTA³ 2018: Workshop on Graph Techniques for Adversarial Activity Analytics

February 9th, 2018 | The Ritz-Carlton Hotel - Marina Del Rey, CA

Theme & Purpose

Networks are natural analytic tools in modeling adversarial activities (e.g., human trafficking, illicit drug production, terrorist financial transaction) using different intelligence data sources. However, such activities are often covert and embedded across multiple domains and contexts. They are generally not detectable and recognizable from the perspective of an isolated network, and only become apparent when multiple networks are analyzed in a joint manner. Thus, one of the main research topics in modeling adversarial activities is to develop effective techniques to align and fuse information from different networks into a unified representation for global analysis. Based on the combined network representation, an equally important research topic is on detecting and matching indicating patterns to recognize the underlining adversarial activities in the integrated network.

Two key challenge problems involved in the modeling process include:

  • Network alignment and merging: develop accurate and scalable methods for mapping of nodes across heterogeneous networks based on different associational and causal dependencies.
  • Sub-graph detection and matching: develop robust and efficient algorithms for richly attributed networks to support recognition of complex query patterns for networks.

The focus of this workshop is to gather together the researchers from all relevant fields to share their experience and opinions on graph mining techniques in the era of big data, with emphasis on two fundamental problems – “Connecting the dots” and “finding a needle in a haystack”, in the context of graph-based adversarial activity analytics. A best paper will be selected and announced in our workshop based on the collective feedback from our reviewers.

This workshop (co-located with the 11th ACM Conference on Web Search and Data Mining) aims to bring together a cross-disciplinary audience of researchers from both academia and industry to share experience with techniques, resources and best practices, and to exchange perspectives and future directions. We expect the workshop to develop a community of interested researchers and facilitate their future collaborations.

Topics of Interest

Including but not limited to:

  • Data integration and alignment from multiple heterogeneous networks
  • Novel algorithms for sub-graph detection and matching in large networks
  • Graph construction and modeling for different domains (e.g., financial fraud, human trafficking, DDoS attack)
  • Complex anomaly (e.g., group anomaly) detection and interpretation
  • Atypical behavior and rare event detection
  • Limits of detectability and identifiability
  • Evolution analysis and forecasting 
  • Game theoretic approach on anticipating opponent intent and actions
  • Identification of novel network datasets and/or evaluation metrics
  • Multilayer and multiplex network analytics
  • Clustering and ranking methods for composite networks
  • Large-scaled link prediction and recommendation algorithms
  • Community detection in big networks
  • Information diffusion and influence maximization
  • Interactive visualization for big graphs
  • New methods and frontiers in spectral graph theory
  • Analysis of network topologies (e.g., centrality and network motif analysis)
  • Semi-supervised learning, Transductive inference, Active learning, and Transfer learning

Submission Instructions

Submissions to the workshop will be subject to a single-blind peer review process, with each submission reviewed by at least two program committee members in addition to an organizer. Accepted papers will be given either an oral or poster presentation slot, and made available in the workshop’s website.

Papers must be submitted in PDF format according to ACM guidelines and style files to fit within 8 pages (long papers), 4 pages (short papers) or 2 pages (demo papers) including any diagrams, references and appendices. PDF files must have all non-standard fonts embedded. Submissions must be self-contained and in English. After uploading your submission, please check the copy stored on the site. Submissions that do not follow these guidelines, or do not view or print properly, may be rejected without review.

ACM style files (LaTeX and Word) are available from:

Submissions should be made using the EasyChair submission system.

Important Dates

  • All deadlines end at 11:59pm PST
  • + Submission Deadline November 24, 2017
  • + Notification to AuthorsDecember 20, 2017
  • + Camera-ready PDFs dueJanuary 12, 2018
  • + Workshop DateFebrurary 9, 2018

Keynote Speakers

Accepted Papers

Metrics for Evaluating Network Alignment

Joel Douglas, Ben Zimmerman, Alexei Kopylov, Jiejun Xu, Daniel Sussman, and Vince Lyzinski

Matched Filters for Noisy Induced Subgraph Detection

Daniel Sussman, Vince Lyzinski, Carey Priebe, and Youngser Park

Cyber Persona Identification via Indirect Feature Analysis

Suzanne Stathatos, Asitang Mishra, and Chris Mattmann

Efficient Routing with Partial Information

Xiaoran Yan, Andrea Avena-Koenigsberger, and Olaf Sprons

Ensemble Sentiment Analysis to Identify Human Trafficking in Web Data

Anastasia Mensikova, and Chris Mattmann


8:25am | Opening Remarks
8:30am - 9:20am | Keynote: Local Graph Analytics: Beyond Characterizing Community Structure
9:20am - 10:10am | Keynote: Mathematical Issues Derived from Modeling Adversarial Activity (MAA)
10:10am - 10:20am | Coffee Break
10:20am - 11:10am | Keynote: Detecting Significant Network Processes
11:10am - 12:00pm | Keynote: Multilayer Networks
12:00pm - 12:15pm | Contributed talk: Metrics for Evaluating Network Alignment
12:15pm - 12:30pm | Contributed talk: Matched Filters for Noisy Induced Subgraph Detection
12:30pm - 12:45pm | Contributed talk: Cyber Persona Identification via Indirect Feature Analysis
12:45pm - 12:55pm | Contributed talk: Efficient routing with partial information
12:55pm - 1:05pm | Contributed talk: Ensemble Sentiment Analysis to Identify Human Trafficking in Web Data
1:05pm | Closing Remarks

Program Committee

  • Connie Ni (HRL, USA)
  • Dave Huber (HRL, USA)
  • Nicola Perra (U. Greenwich, UK)
  • Feng Chen (SUNY, Albany, USA)
  • Hasan Davulcu (ASU, USA)
  • Yu-Ru Lin (U. Pittsburgh, USA)
  • Meng Jiang (Notre Dame, USA)
  • Xiaoran Yan (Indiana University, USA)

Workshop Organizers