List of Sample Research and Education Projects

Together with the team I have been principal investigator or co-principal investigator for numerous Research and Education projects, each that has resulted due to a grant or a contract. This section provides an overview of a sample of the high impact projects, many of them are over $1M and some around $4M. I was instrumental in getting all of the projects listed below even though I am not the principal investigator for some of the projects). The funding is discussed under the section on Research and Education Funding. I have been part of around 60 research and education projects over the years.

Sample Research Projects

1. A Semantic Framework for Policy Specification and Enforcement in a Need to Share Environment (2007-2010)

   Funded by NSF and IARPA, this approx. 600K project developed a conceptual framework for computational policies to support information sharing in a need to share environment. Our framework integrated and extended our work on access control (RBAC), usage control (UCON) and deontic policies (REI), grounding them in ontologies expressed in the Semantic Web language OWL. We used it to design a policy specification language and enumerate required software artifacts and tools. Finally, we studied the framework applicability to realistic applications such as the management of healthcare records and homeland security related data.

2. Assured Information Sharing Lifecycle (2008 – 2013)

   This $1M project is a MURI (Multi-University Research Initiative) funded by the Air Force Office of Scientific Research (AFOSR) (part of a $7.5M initiative). The main objective of our project is: define, design, and develop an Assured Information Sharing Lifecycle (AISL) that realizes the DoD's information sharing value chain. In this paper we describe the problem faced by the Department of Defense and our solution to developing an AISL System. As part of this project we developed the following: (i) A framework for policy-based Assured Information Sharing, (ii) Incentives for Assured Information Sharing, and (iii) the Risks involved in information sharing. Subsequently we designed and developed a system for multiple organizations sharing information securely. (It should be noted we utilized the research of our prior project (2005-2007) funded by AFOSR to prepare a one page for a MURI, which was subsequently include in the MURI call for proposals in 2007).

3. Securing the Cloud (2008-2012)

   Funded by AFOSR, this approx. $2.4M project developed a secure cloud framework and demonstrated assured information sharing in the cloud. The framework included Secure Virtual Network Monitor, Secure Virtual Machine Monitor, Secure Hadoop, Secure MapReduce, and Secure Wery Processing in the Cloud. We them utilized the secure cloud to demonstrate assured information sharing applications. AFOSR did a press release on our work. Part of the effort was collaborative between UT Dallas, Kings Collee, U of London, and U of Insubria Italy. Our one page was also included in the 2010 STTR call for proposals. It should also be nod that we received funding from NSF to develop course modules in Secure Cloud Computing in 2011 and have also written a book on this topic.

4. Secure Complex Networks (2009 – 2014)

   Funded by AFOSR, this $1.6M project was on developing secure complex networks including sensor networks, semantic web, and social networks. The secure social network component was based on semantic web technologies and demonstrate access control for social networks. In addition, we also developed technologies for privacy enhanced social networks. We also explored several other aspects' such as secure geospatial systems and inference control. Security techniques for schema/ontology integration and matching was also developed.

5. Secure Data Provenance (2011 – 2017)

   Funded by NSF, this approx. $1M project developed a comprehensive technical and scientific framework to address the security and privacy challenges of provenance data, and the attendant tradeoffs, so that our society can gain maximum benefit from applications of provenance data. Detailed foundational research was performed on security enhanced data models, access control and usage models, privacy including anonymization and sanitization, integrity, accountability, and risk management techniques for provenance data. This foundational research was complemented by data provenance case studies in scientific and cyber security information sharing, and construction of prototype data provenance systems at the operating systems and data layers.

6. Malware Analysis (2012 – 2017)

   Funded by AFOSR, this approx.. $1M project developed several tools for malware analysis. In particular, our tools included those for malware analysis in Andrin phones, insider threat detection, botnet detection, and detecting malware that changes patterns. We also deceived tools for stream analytics applied to malware detection. The set of tools were made open source. We also published two books based on this research.

7. TraCR (2023 – 2028) – Transportation Cybersecurity and Resiliency

   Funded by USDOT, this $1.75M project (with 100% cost share for a total of $3.5M) is part of a $20M National UTC led by Clemson University. UTD's focus is on (i) securing USDOT service packages such as Transit Security, as well as conducting fundamental research on applying AI for transportation systems security including Data Privacy, Data Security, as well as applying GenAO techniques for analyzing large volumes of documents containing regulations. UTD started the research in January 2024 and our work is expected to end in December 2028.

8. FARML (2024 – 2029)

   Funded by the ARL, this $3.5M project is on developing techniques for handle adversarial machine learning that handle adversarial attacks We plan to developed several adversarial machine learning algorithms that handle various attacks including denial of service and attacks to IoT systems. We also plan to test our algorithms with real world data and develop demonstration systems.

Sample Education Projects

9. NSF Scholarship for Service (SFS) (2010 – Present)

   Since 2010, we have been part of the NSF SFS program and have received two renewals in 2014 and 2019 for a total of around $10M. We have graduated 70+ MS students under this program and have focused on different thrusts such as AI+Security, Policy and Technology, and Software defended networks, among others. Students have been placed in federal government jobs. We have organized a variety of activities for the students including capture the flag events and our annual TexSAW (Texas Security Awareness Week) since 2011. Students participate from around the world.

10. Big Data Security and Privacy (2017-2023)

    This NSF funded 500K project has focused on capacity building for Big Data Security and Privat. We were motivated by the fact that data owners may need to protect their data, and require cryptographic guarantees about data security and integrity of computational output from these third-party services. The project addressed this need by developing an experimental education program for Big Data Security and Privacy (BDSP). The project developed a set of laboratory exercises and course modules in BDSP that has been shared with academia, government, and industry. More details about this project will be discussed under the section on "High Profile Education Projects".

11. Blockchain Technologies (2019 – 2025)

    This NSF funded 600K project has resulted in developing experiments and course work in Blockchain technologies. We introduced our first Blockchain course in Spring 2024. Students familiarized themselves with a variety of Blockchain concepts including mining algorithms, smart contracts, and various consensus algorithms such as Proof-of-Work, Proof-of-Stake, etc. used on Bitcoin and Ethereum Blockchains. Furthermore, the course also addressed security concerns such as smart contract protection through code rewriting and vulnerability detection using machine learning.

12. Trustworthy AI (AI, Security and Privacy) (2020-2024)

    This approx. 250K NF funded EAGER project team is developing five modular courses for graduate students: (1) Scalable Advanced Analytics, (2) AI including Explainable Machine Learning (ML), (3) ML for Cybersecurity, (4) Cybersecurity for ML (e.g., Adversarial ML), and (5) Secure Blockchain Technologies. The design of these modular and hybrid courses will incorporate research-based pedagogies and innovative technologies. Courses will be offered in both instructor-led and student-directed learning formats to study the differences in learning outcome, if any, between these two different approaches. We have offered variations of the courses (e.g., Trustworthy Machine Learning at U of Dschang in Africa) and will offer a course on Trustworthy AI in Fall 2025 at UT Dallas. It should be noted that we have also received additional funds from NSA to develop complementary courses such as in Data Science. We have published a book on Secure Data Science and writing a second book on Trustworthy Machine Learning.