Tuesday, May 11, 2021

Trusted CI webinar: Identifying Vulnerable GitHub Repositories and Users, Mon May 24th @11am Eastern

Indiana University's Sagar Samtani is presenting the talk, Identifying Vulnerable GitHub Repositories in Scientific Cyberinfrastructure: An Artificial Intelligence Approach, on Monday May 24th at 11am (Eastern).

Please register here. Be sure to check spam/junk folder for registration confirmation email.

The scientific cyberinfrastructure community heavily relies on public internet-based systems (e.g., GitHub) to share resources and collaborate. GitHub is one of the most powerful and popular systems for open source collaboration that allows users to share and work on projects in a public space for accelerated development and deployment. Monitoring GitHub for exposed vulnerabilities can save financial cost and prevent misuse and attacks of cyberinfrastructure. Vulnerability scanners that can interface with GitHub directly can be leveraged to conduct such monitoring. This research aims to proactively identify vulnerable communities within scientific cyberinfrastructure. We use social network analysis to construct graphs representing the relationships amongst users and repositories. We leverage prevailing unsupervised graph embedding algorithms to generate graph embeddings that capture the network attributes and nodal features of our repository and user graphs. This enables the clustering of public cyberinfrastructure repositories and users that have similar network attributes and vulnerabilities. Results of this research find that major scientific cyberinfrastructures have vulnerabilities pertaining to secret leakage and insecure coding practices for high-impact genomics research. These results can help organizations address their vulnerable repositories and users in a targeted manner.

Speaker Bio: Dr. Sagar Samtani is an Assistant Professor and Grant Thornton Scholar in the Department of Operations and Decision Technologies at the Kelley School of Business at Indiana University (2020 – Present). He is also a Fellow within the Center for Applied Cybersecurity Research (CACR) at IU. Samtani graduated with his Ph.D. in May 2018 from the Artificial Intelligence Lab in University of Arizona’s Management Information Systems (MIS) department from the University of Arizona (UArizona). He also earned his MS in MIS and BSBA in 2014 and 2013, respectively, from UArizona. From 2014 – 2017, Samtani served as a National Science Foundation (NSF) Scholarship-for-Service (SFS) Fellow.

Samtani’s research centers around Explainable Artificial Intelligence (XAI) for Cybersecurity and cyber threat intelligence (CTI). Selected recent topics include deep learning, network science, and text mining approaches for smart vulnerability assessment, scientific cyberinfrastructure security, and Dark Web analytics. Samtani has published over two dozen journal and conference papers on these topics in leading venues such as MIS Quarterly, JMIS, ACM TOPS, IEEE IS, Computers and Security, IEEE Security and Privacy, and others. His research has received nearly $1.8M (in PI and Co-PI roles) from the NSF CICI, CRII, and SaTC-EDU programs. 

He also serves as a Program Committee member or Program Chair of leading AI for cybersecurity and CTI conferences and workshops, including IEEE S&P Deep Learning Workshop, USENIX ScAINet, ACM CCS AISec, IEEE ISI, IEEE ICDM, and others. He has also served as a Guest Editor on topics pertaining to AI for Cybersecurity at IEEE TDSC and other leading journals. Samtani has won several awards for his research and teaching efforts, including the ACM SIGMIS Doctoral Dissertation award in 2019. Samtani has received media attention from outlets such as Miami Herald, Fox, Science Magazine, AAAS, and the Penny Hoarder. He is a member of AIS, ACM, IEEE, INFORMS, and INNS.

Join Trusted CI's announcements mailing list for information about upcoming events. To submit topics or requests to present, see our call for presentations. Archived presentations are available on our site under "Past Events."


Wednesday, April 28, 2021

Transition to practice success story: Pablo Moriano - technology readiness & understanding critical security issues in large-scale networked systems

Pablo Moriano is a research scientist in the Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL). He received Ph.D. and M.S. degrees in Informatics from Indiana University (IU). Previously, he received M.S. and B.S. degrees in Electrical Engineering from Pontificia Universidad Javeriana in Colombia.

Moriano’s research lies at the intersection of data science, network science, and cybersecurity. In particular, he develops data-driven and analytical methods to discover and understand critical security issues in large-scale networked systems. He relies on this approach to design and develop innovative solutions to address these. Applications of his research range across multiple disciplines, including the detection of exceptional events in social media, internet route hijacking, and insider threat behavior in version control systems. His research has been published in Computer Networks, Scientific Reports, Computers & Security, Europhysics Letters, and the Journal of Statistical Mechanics: Theory and Experiments as well as the ACM CCS International Workshop on Managing Insider Security Threats.

In the past, he interned at Cisco with the Advanced Security Group. He is a member of IEEE, ACM, and SIAM and has received funding from Cisco Research.

Trusted CI sat down with Moriano to discuss his transition to practice journey, what he has learned, and his experience with the Technology Readiness Level Assessment tool.

Trusted CI: Tell us about your background and your broader research interests.

My background is in electrical engineering.

I was born and grew up in Colombia. I attended Pontificia Universidad Javeriana to pursue a degree in electrical engineering. I remember enjoying so much math-related and physics classes, which are the foundations of electrical engineering. I did pretty well on those topics.

In my engineering classes, at the end of the semester, we had the same kinds of final projects as in the US, called capstones. The idea of these projects was to integrate the learnings from different subjects to solve a real engineering challenge. In these types of activities, you usually measure the impact a technology has on solving a real problem.

In general, I enjoyed going beyond what I learned in classes. I participated in math-related contests, which allowed me to sharpen my analytical skills. By the end of my undergraduate studies, I had a professor that always was encouraging me to try research and go to grad school. I worked under his supervision to complete my undergraduate thesis. In my undergraduate thesis, I developed real-time control algorithms for a non-linear laboratory plant that used magnetic levitation. That was a starting point to be involved with research and pursuing opportunities in that direction later during grad school.

Currently at Oak Ridge National Laboratory (ORNL), I am a researcher in the computer science and mathematics division. I develop data-driven and analytical models for understanding and identifying anomalies in large-scale networked systems such as cyber-physical systems, communication systems, and socio-technological systems like social media.

This is broad, but common to these systems, also known as complex systems, is that they are made of a large number of elements and that these elements interact in non-linear ways, often producing collective behavior. This collective behavior cannot be explained by analyzing the aggregated behavior of the individual parts. For example, on the internet, a large number of independent and autonomous networks, also known as Autonomous Systems (ASes), such as internet service providers, corporations, and universities are constantly interacting between each other to share reachability of information with respect to where to find destination IP addresses. To do so, ASes communicate using a protocol called Border Gateway Protocol (BGP). The details of the protocol and the interactions between Ases are complex and subject to engineering and economic constraints. However, their aggregated behavior allows users around the globe to navigate the web—and use many other services—by allowing them to find the resources they need every time they search online.

In these networked systems such as the internet, their emergent behavior may sometimes be anomalous or substantially different. This idea in the cybersecurity space is really important because it may be an indication of a problem or in the worst case scenario an indication of an upcoming attack. A similar approach as described in the case of the internet may be used to study other real-world networked systems.

Trusted CI: Tell us about your experience using the Technology Readiness Level (TRL) assessment.

When I was finishing my studies at IU, I had the chance to participate in a Trusted CI workshop in Chicago. At that time Florence [Hudson] was leading that effort.

In addition to getting to interact with other researchers, the intention of the workshop was to provide an opportunity to share the latest research efforts in the cybersecurity space. The emphasis was also to showcase previous academic research that was subsequently translated to practice, delivering a solution to a practical need. That event was very fruitful and allowed me to interact with other peers, have a fresh perspective into transition to practice, and grow my network.

Later, I was invited to participate in the [Trusted CI] cohort. The intention of the cohort is to bring together researchers interested in solving real-world problems in cybersecurity and help them do so. During the process, you get mentorship through the process of transition to practice. In addition, the experience allows you to foster interactions with external stakeholders to receive feedback and support during the process.

The cohort, under the leadership of Ryan [Kiser] has been developing different useful tools like the TRL assessment and canvas proposition.

The TRL assessment idea is not new. In fact, it came from NASA in the 70s. However, it has not been widely used as a resource for transition to practice by cybersecurity researchers. In particular, the TRL assessment provides a tool—similar to a decision tree—to help classify the level of maturity of a technology. Originally, it was conceived using a nine-level scale (from one to nine) with nine being the most mature technology. The TRL assessment is super helpful, for example, to identify the next steps in the transition to practice journey. The fundamental assumption of the tool is that by recognizing where you are at the moment, you will have a clearer picture on how to proceed next.

For instance, when searching for funding opportunities, having a clear picture of where you are (with respect to the maturation of the technology) will allow you to better target specific sources of funding, enabling next steps in the transition to practice journey. In my experience at ORNL, it is an important decision element when deciding which funding steps to pursue in the overall R&D pipeline across several federal agencies.

Trusted CI: Talk about your experience with the funding you were pursuing.

Here at ORNL, there are different opportunities for funding, including specific ones for transitioning to practice your research. One of the fundamental advantages of working in a national laboratory is that it is an environment that bridges academia and industry. In that sense, the work we do is mission-driven and has real-world impact—often with some component of transition to practice as a measure of impact. That means that both research and development are tied together and highly appreciated.

I already applied to an internal funding opportunity for transition to practice. The main purpose of the solicitation was to look for technologies at a minimum of TRL 5 (requiring a working high-fidelity prototype which is beyond basic research) to support the necessary steps for technology maturation. The final goal was to help convert the prototype into an actual usable system that may open the door to commercialization opportunities.

By the time I applied, my technology was not at TRL 5 and of course that was the basis of the feedback that I received. I, however, enjoyed and learned during the process and realized that there are other solicitations that may be more adequate to help me to increase the TRL of my technology (from proof-of-concept to prototype). Throughout the process, I had the chance to talk with practitioners out there and learn about the practical challenges they faced with current deployed systems. I also learned about other federal agencies such as DOE, DHS, and DARPA (and people there) looking for proposals with the focus on transition to practice. That was encouraging.

Trusted CI: Tell us more about your technology.

It's a technology that aims to detect and inform network operators in near real-time about routing incidents (of different severity) by leveraging update messages transmitted in BGP. The fundamental characteristic of the intended system is that it is somehow automatic (leveraging AI/ML methods), detects incidents as soon as possible (allowing quick turnaround), and is able to detect subtle attacks in which only a small fraction of IP prefixes are affected (usually the ones performed through man-in-the-middle).

Trusted CI: Describe where you’d say you are in your transition to practice.

Through the Trusted CI cohort, I had the opportunity to use that TRL tool to evaluate the current state of my technology. By using the tool and the decision criteria behind it, I am pretty confident that the technology at this stage is on what is called Level 3 or proof-of-concept.

The next step will be to mature the technology to build a high-fidelity working prototype that can be used to detect routing incidents using real-time data.

This particular BGP project came from my dissertation research. I recently published a paper about it. However, beyond this project, I see that tools like the TRL assessment are essential to guide my next steps. For that reason, this experience easily translates to other ongoing research projects that go through the whole R&D pipeline.

Trusted CI: Where do you see your research heading down the road?

I'm pursuing the idea of maturing the BGP technology. The problem of BGP incident detection has been in the community for many years. BGP anomaly detection is a difficult space with little room for improvement. For that reason, you need to be very precise about the added value the technology is offering. I also started new projects in the cybersecurity space where I see a clear path between research and development. Currently, these are in earlier stages but may benefit from early consideration through the use of tools like the TRL assessment and the Trusted CI cohort experience.

Monday, April 12, 2021

Trusted CI webinar: Arizona State's Science DMZ, Mon April 26th @11am Eastern

Members of Arizona State University are presenting on their Science DMZ on Monday April 26th at 11am (Eastern).

Please register here. Be sure to check spam/junk folder for registration confirmation email.

Drawing upon its mission to enable access to discovery and scholarship, Arizona State University is deploying an advanced research network employing the Science DMZ architecture. While advancing knowledge of managing 21st-century cyberinfrastructure in a large public research university, this project also advances how network cyberinfrastructure supports research and education in science, engineering, and health.

Replacing existing edge network equipment and installing an optimized, tuned Data Transfer Node provides a friction-free wide area network path and streamlined research data movement. A strict router access control list and intrusion detection system provide security within the Science DMZ, and end-to-end network performance measurement via perfSONAR guards against issues such as packet loss.

Recognizing that the operation of the Science DMZ must not compromise the university’s network security profile, while at the same time avoiding the performance penalty associated with perimeter firewall devices, data access and transfer services will be protected by access control lists on the Science DMZ border router as well as host-level security measures. Additionally, the system architecture employs the anti-IP spoofing tool Spoofer, the Intrusion Detection System (IDS) Zeek, data-sharing honeypot tool STINGAR, traditional honeypot/darknet/tarpit tools, as well as other open-source software.

Finally, Science data flows are supported by a process incorporating user engagement, iterative technical improvements, training, documentation, and follow-up.

Speaker Bios:

Douglas Jennewein is Senior Director for Research Computing in the Research Technology Office at Arizona State University. He has supported computational and data-enabled science since 2003 when he built his first supercomputer from a collection of surplus-bound PCs. He currently architects, funds, and deploys research cyberinfrastructure including advanced networks, supercomputers, and big data archives. He has also served on the NSF XSEDE Campus Champions Leadership Team since 2016 and has chaired that group since 2020. Jennewein is a certified Software Carpentry instructor and has successfully directed cyberinfrastructure projects funded by the National Science Foundation, the National Institutes of Health, and the US Department of Agriculture totaling over $4M.

Chris Kurtz is the Senior Systems Architect for the Research Technology Office in the Office of Knowledge Enterprise at Arizona State University. Previously Chris was the Director of Public Cloud Engineering as well as the Splunk System Architect (and Evangelist) at ASU. He has been appointed as Splunk Trust Community MVP since its inception. Chris is a regular speaker on Splunk and Higher Education, including multiple presentations at Educause, Educause Security Professionals,  and Splunk’s yearly “.conf" Conference. Prior to architecting Splunk, he was the Systems Manager of the Mars Space Flight Facility at ASU, a NASA/JPL funded research group, where he supported numerous Mars Missions including TES, THEMIS, and the Spirit and Opportunity Rovers. Chris lives in Mesa, Arizona along with his wife, rescue dogs, and cat.

Join Trusted CI's announcements mailing list for information about upcoming events. To submit topics or requests to present, see our call for presentations. Archived presentations are available on our site under "Past Events."


Wednesday, April 7, 2021

Michigan State University Engages with Trusted CI to Raise Awareness of Cybersecurity Threats in the Research Community

Cybersecurity exploits are on the rise across university communities, costing valuable resources, and loss of productivity, research data, and personally identifiable information. In a DXC report, it was estimated that an average ransomware attack can take critical systems down for 16 days, and the overall worldwide cost of ransomware in 2020 was predicted to cost $170 billion.   Additional reputational impacts of cybersecurity attacks, although hard to measure, regularly weigh in the minds of scientists and researchers.

An event of this nature occurred at Michigan State University (MSU), which experienced a ransomware attack in May 2020. While many organizations attempt to keep the public from finding out about cyberattacks for fear of loss of reputation or follow-up attacks, MSU has decided to make elements of its attack public in the interests of transparency, to encourage disclosure of similar types of attacks, and perhaps more importantly, to educate the open-science community about the threat of ransomware and other destructive types of cyberattacks. The overarching goal is to raise awareness about rising cybersecurity threats to higher education in hopes of driving safe cyberinfrastructure practices across university communities. 

To achieve this, the CIO’s office at MSU has engaged with Trusted CI, the NSF Cybersecurity Center of Excellence, in a collaborative review and analysis of the ransomware attack suffered by MSU last year.  The culmination of the engagement will be a report focusing on lessons learned during the analysis; these ‘Lessons Learned’ would then be disseminated to the research community.  We expect the published report to be a clear guide for researchers and their colleagues who are security professionals to help identify, manage, and mitigate the risk of ransomware and other types of attacks.

Thursday, April 1, 2021

Trusted CI Engagement Application Deadline Extended


Trusted CI Engagement Application Deadline

 Extended till April 9, 2021


Apply for a one-in-one engagement with Trusted CI for early 2021


Trusted CI is accepting applications for one-on-one engagements to be executed in July-Dec 2021. Applications are due April 9, 2021

To learn more about the process and criteria, and to complete the application form, visit our site: 


During Trusted CI’s first 5 years, we’ve conducted
 more than 24 one-on-one engagements with NSF-funded projects, Large Facilities, and major science service providers representing the full range of NSF science missions.  We support a variety of engagement types including: assistance in developing, improving, or evaluating an information security program; software assurance-focused efforts; identity management; technology or architectural evaluation; training for staff; and more.   

As the NSF Cybersecurity Center of Excellence, Trusted CI’s mission is to provide the NSF community a coherent understanding of cybersecurity’s role in producing trustworthy science and the information and know-how required to achieve and maintain effective cybersecurity programs.

Tuesday, March 30, 2021

Announcing the 2021 Trusted CI Annual Challenge on Software Assurance

The Trusted CI “Annual Challenge” is a year-long project focusing on a particular topic of importance to cybersecurity in scientific computing environments.  In its first year, the Trusted CI Annual Challenge focused on issues in trustworthy data.  Now, in its second year, the Annual Challenge is focusing on software assurance in scientific computing.

The scientific computing community develops large amounts of software.  At the largest scale, projects can have millions of lines of code.  And indeed, the software used in scientific computing and the vulnerabilities present in scientific computing can be similar to that used in other domains.  At the same time, the software developers have usually come from traditional scientific focused domains rather than traditional software engineering backgrounds.  And, in comparison to other domains, there's often less emphasis on software assurance.

Trusted CI has a long history in addressing the software assurance of scientific software, both through engagements with individual scientific software teams, as well as through courses and tutorials frequently taught at conferences and workshops by Elisa Heyman and Barton Miller, from University of Wisconsin-Madison.  This year’s Annual Challenge seeks to complement those existing efforts in a focused way, and leveraging a larger team.  Specifically, this year’s Annual Challenge seeks to broadly improve the robustness of software used in scientific computing with respect to security.  It will do this by spending the March–June  2021 timeframe engaging with developers of scientific software to understand the range of software development practices being used and identifying opportunities to improve practices and code implementation to minimize the risk of vulnerabilities.  In the second half of 2021, we will leverage our insights to develop a guide specifically aimed at the scientific software community that covers software assurance in a way most appropriate to that community,.  

We seek to optimize the impact of our efforts in 2021 by focusing our effort on software that is widely used, is situated in vulnerable locations, and is developed mostly by individuals who do not have traditional software engineering backgrounds and training.

This year’s Annual Challenge is supported by a stellar team of Trusted CI staff, including Andrew Adams (Pittsburgh Supercomputing Center), Kay Avila (National Center for Supercomputing Applications), Ritvik Bhawnani (University of Wisconsin-Madison), Elisa Heyman (University of Wisconsin-Madison), Mark Krenz (Indiana University), Jason Lee (Berkeley Lab/ NERSC), Barton Miller (University of Wisconsin-Madison), and Sean Peisert (Berkeley Lab; 2021 Annual Challenge Project Lead).

Monday, March 29, 2021

Trusted CI and the CI CoE Pilot Complete Identity Management Engagement with GAGE


The Geodetic Facility for the Advancement of Geoscience (GAGE), is operated by UNAVCO and funded by the NSF and NASA. The GAGE project’s mission is to provide support to the larger NSF investigator community for geodesy, earth sciences research, education, and workforce development. During the second half of 2020, GAGE and the Trusted CI/CI CoE Identity Management working group collaborated on an engagement to design a working proof of concept for integrating federated identity into GAGE’s researcher data portal.

The Cyberinfrastructure Center of Excellence Pilot (CI CoE) is a Trusted CI partner, specializing in providing expertise and active support to CI practitioners at the NSF major facilities in order to accelerate the data lifecycle and ensure the integrity and effectiveness of the CI upon which research and discovery depends. The Identity Management working group is a joint effort between the CI CoE and Trusted CI to provide subject matter expertise and advice to major facilities on trust and identity issues, best practices and implementation. The working group's target audience is NSF funded major facilities, but participation in the working group is open to anyone in higher education and IAM.

The engagement began in July 2020 with a month long series of interviews between working group members and GAGE department leadership. GAGE came into the engagement with a series of needs that had arisen from practice and with a request from NSF to collect information on how their research data was being used. The working group used the interviews to identify key systems and areas of impact in order to present GAGE with a design for integrating federated identity into their data portal using elements of InCommon’s Trusted Access Platform.

Over the next three months, the engagement team met with members of GAGE’s software development team, CILogon, and COmanage to finalize and implement the proof of concept design. This design used CILogon to consume federated identities from other InCommon member institutions and then used COmanage registry to store GAGE specific attributes for those identities to grant permission for accessing various data groups, membership in research projects, and home institutions. Identities and attributes stored in COmanage could then be passed to the GAGE data portal using OIDC claim tokens; granting permissions appropriately at the time of access and allowing GAGE to track which identities were requesting what permissions for their data.

The engagement culminated with a 15-page report delivered to GAGE in February 2021 containing detailed observations from interviews, alternate design configurations and tools for the proof of concept, lessons learned through the implementation process, and identification of future opportunities for investment and collaboration in IAM. Additionally, findings from this engagement will be included in an IAM cookbook that the working group plans to release in 2022. The Identity Management working group meets monthly on the second Monday at 2pm Eastern time. For more information about the Identity Management working group, please see the Trusted CI IAM page, the CI CoE working group directory, or join our mailing list to receive updates on working group meetings and products.

GAGE is funded by an NSF award managed by the Division of Earth Sciences (Award #1724794) and is operated by UNAVCO. The CI CoE Pilot is supported by a grant managed by the NSF Office of Advanced Cyberinfrastructure (Award #1842042) and is a collaboration between the University of Southern California, University of North Carolina at Chapel Hill, University of Notre Dame, University of Utah, and Indiana University. The working group would like to thank the following institutions and organizations for the collaboration and contributions to the engagement: Internet2 and InCommon, the CILogon team, the COmanage team, and the Globus team.