Award Abstract # 1443019
CIF21 DIBBs: DIBBs for Intelligence and Security Informatics Research Community

NSF Org: OAC
Office of Advanced Cyberinfrastructure (OAC)
Recipient: UNIVERSITY OF ARIZONA
Initial Amendment Date: September 8, 2014
Latest Amendment Date: September 8, 2014
Award Number: 1443019
Award Instrument: Standard Grant
Program Manager: Amy Walton
awalton@nsf.gov
 (703)292-4538
OAC
 Office of Advanced Cyberinfrastructure (OAC)
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: October 15, 2014
End Date: September 30, 2019 (Estimated)
Total Intended Award Amount: $1,499,531.00
Total Awarded Amount to Date: $1,499,531.00
Funds Obligated to Date: FY 2014 = $1,499,531.00
History of Investigator:
  • Hsinchun Chen (Principal Investigator)
    hchen@eller.arizona.edu
  • Mark Patton (Co-Principal Investigator)
  • Catherine Larson (Co-Principal Investigator)
Recipient Sponsored Research Office: University of Arizona
845 N PARK AVE RM 538
TUCSON
AZ  US  85721
(520)626-6000
Sponsor Congressional District: 07
Primary Place of Performance: Univ. of Arizona MIS Dept.
1130 E. Helen St., Rm 430
Tucson
AZ  US  85721-0108
Primary Place of Performance
Congressional District:
07
Unique Entity Identifier (UEI): ED44Y3W6P7B9
Parent UEI:
NSF Program(s): Data Cyberinfrastructure,
Cybersecurity Innovation
Primary Program Source: 01001415DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 7433, 7434, 7726, 8027, 8048
Program Element Code(s): 772600, 802700
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

The growing number of cyber attacks on the Internet and other critical infrastructure has led to an increased sense of urgency in developing a better understanding of the motivation and methods behind such incursions. This project develops a research infrastructure for the Intelligence and Security Informatics (ISI) community comprised of experts across the computer, information, and social sciences.

The infrastructure consists of online archives and analysis tools. The archives contain a wide array of open source data including: discussions in online forums run by hackers, data from botnet command and control servers used to stage computer attacks, video streams and tweets and news summaries from economically and politically unstable states and regions. The analysis tools developed for this project support a range of research investigations. The social network analysis tool allows researchers to study how organizations form and how people interact with one another both virtually and in person. The data visualization tools are important for helping researchers pick out important patterns and trends in large sets of data of different types and from disparate sources. A new tool for adversarial data mining and deception detection allows researchers to deepen their enquiries and analysis of the intentions behind cyber-attacks.

Integrating these divergent data sources allows the security research community to more easily collaborate with other members of the community, rapidly test hypotheses, evaluate detection techniques, track down malicious actors, and identify weaknesses in a cyberinfrastructure network.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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(Showing: 1 - 10 of 16)
Abbasi, A., Zahedi, F. M., and Chen, Y. "Phishing Susceptibility: The Good, the Bad, and the Ugly" 14th IEEE International Conference on Intelligence and Security Informatics, Tucson, Arizona, Sept. 27-30 , 2016
Arnold, N., Ebrahimi, M., Zhang, N., Lazarine, B., Patton, M., Chen, H., & Samtani, S. "Dark-net ecosystem cyber-threat intelligence (CTI) Tool" IEEE International Conference on Intelligence and Security Informatics , 2019
Dobolyi, D., Abbasi, A., Zahedi, F. M., and Vance, T "The Phishing Funnel Model: A Design Artifact to Predict User Susceptibility to Phishing Websites" Information Systems Research , 2017
Dobolyi, D. and Abbasi, A. "PhishMonger: A Free and Open Source Public Archive of Real-World Phishing Websites" 14th IEEE International Conference on Intelligence and Security Informatics, Tucson, Arizona, Sept. 27-30 , 2016
D. Zimbra, A. Abbasi, D. Zeng, and H. Chen "The State-of-the-Art in Twitter Sentiment Analysis: A Review and Benchmark Evaluation" ACM Transactions on Management Information Systems , 2018
John Grisham, Calvin Barreras, Cyran Afarin, Mark Patton, Hsinchun Chen "Identifying Top Listers in Alphabay Using Latent Dirichlet Allocation" 14th IEEE International Conference on Intelligence and Security Informatics, Tucson, Arizona, Sept. 27-30. (NOTE: Development of this paper was supported by other federal grants, but the data collected will go to the DIBBs portal.) , 2016
Mohammadreza Ebrahimi, Mihai Surdeanu, Sagar Samtani, Hsinchun Chen "Detecting Cyber Threats in Non-English Dark Net Markets: A Cross-Lingual Transfer Learning Approach" 2018 IEEE International Conference on Intelligence and Security Informatics , 2018
P. Du et al., "Identifying, Collecting, and Presenting Hacker Community Data: Forums, IRC, Carding Shops, and DNMs" IEEE International Conference on Intelligence and Security Informatics , 2018
Po-Yi Du, Mohammadreza Ebrahimi, Ning Zhang, Hsinchun Chen "Identifying Key Opioid Sellers on Dark Net Marketplaces through High-Impact Products Prediction" 2018 IEEE International Conference on Intelligence and Security Informatics , 2018
Po-Yi Du, Ning Zhang, Mohammedreza Ebrahimi, Sagar Samtani, Ben Lazarine, Nolan Arnold, Rachael Dunn, Sandeep Suntwal, Guadalupe Angeles, Robert Schweitzer, Hsinchun Chen "Identifying, Collecting, and Presenting Hacker Community Data: Forums, IRC, Carding Shops, and DNMs" 2018 IEEE International Conference on Intelligence and Security Informatics , 2018
Ryan Williams, Sagar Samtani, Mark Patton, Hsinchun Chen "Incremental Hacker Forum Exploit Collection and Classification for Proactive Cyber Threat Intelligence: An Exploratory Study" 2018 IEEE International Conference on Intelligence and Security Informatics , 2018
(Showing: 1 - 10 of 16)

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

Shortly after the tragic events of 9/11, many Computer Information Science and Engineering (CISE) researchers began to develop interdisciplinary security-related research resulting in the community of Intelligence and Security Informatics (ISI) researchers. This interdisciplinary research field integrates advanced information technologies, computer science, computational social science, public policy, social/behavioral studies, and algorithms for security applications. Today, the international ISI community consists of 1,500+ scholars (70% in CISE disciplines; 30% in political and social sciences, international relations, criminal justice, etc.). Numerous law enforcement, intelligence experts, and IT practitioners actively participate in this community. The ISI community supports counterterrorism and homeland security?s missions of anticipation, prevention, preparedness, and response to security events, in physical, cyber, enterprise, and societal spaces by conducting high-impact research on emerging topics such as ?cybersecurity analytics? and ?terrorism informatics? using Big Data to predict, understand, and prevent events such as data breaches and terrorist attacks.

The broad scope, diversity of research topics, and longevity of ISI have resulted in the collection of hundreds of security related datasets. Unlike traditional CISE researchers who have access to publicly available data, however, the ISI community had no central data storage. In a domain where adversaries advance their skills at a staggering rate, this limitation severely hinders the development of transformative ISI research and ultimately, the security of modern society. This project aimed to address this critical gap by developing an ISI community infrastructure consisting of an opensource data repository and computational tools for data collection and analytics.

Each year of the project saw a steady rise in the number of published papers citing the available datasets, demonstrating broad dissemination of the resource. To our knowledge, from 2016-2019, a total of 47 papers have been published that cite data from the DIBBs portal. Users from over 100 different countries (as identified by IP) have downloaded just under 7 terabytes of data throughout the course of the project, through 94,000 file requests. Numerous U.S. and international academic institutions have downloaded data, and notable companies accessing the data include Amazon, Capital One, Cisco, Facebook, IBM, Paypal, and Yahoo.

The broader impacts of the project are exemplified by the numerous training and professional development opportunities for students involved in the project including hands-on infrastructure development, data collection and management, tool building, and engagement in a variety of community development events. Over thirty graduate students throughout our partner institutions were involved in this project in some capacity, many of whom contributed to or authored papers that used portal data.

An additional way that this project has made significant impacts is through the incorporation of datasets and tools from the portal into course curricula and other educational materials. Exposing students to real-world datasets gives them hands-on experience in ISI related research and prepares them for a career in the ISI domain. Over the past two years, the University of Arizona, the University of Georgia, and the University of South Florida have all developed new cybersecurity curricula using datasets provided by the portal.

 


Last Modified: 12/09/2019
Modified by: Hsinchun Chen

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