Cybersecurity Student Demo Day Finale and Mixer
Due to COVID-19, IISP is postponing the Cybersecurity Demo Day event.
New Fall Date - August 27, 2020
Student research with the best chance of commercialization or demonstrating the most impact can win from a funding pool of almost $100,000
• Network with faculty, students, investors, and industry professionals
• Engage with Georgia Tech's robust entrepreneurial ecosystem
• Cast your vote for the Peoples' Choice Award
Demo Day Finale & Mixer
3:00 – 3:30 p.m. Mixer & Poster Session
3:30 – 4:30 p.m. Panel of Experts Discuss Cyber Challenges
4:45 – 6:15 p.m. Finale & Prizes Awarded
Here is a Recap of Last Year's Demo Day Finale
The Institute for Information Security & Privacy (IISP), presented the Demo Day Finale on April 16th, a signature event that brings together faculty, students, and industry leaders to explore emerging cybersecurity innovation at Georgia Tech. The Finale was the culmination of the Demo Day Program which spanned six months and was designed to help students consider the commercialization aspects of their research.
The program began with a Mixer & Poster Session from 4:00 – 4:30 p.m., followed by the Finale. Dr. Michael Farrell & Dr. Wenke Lee, Co-Executive Directors for the Institute for Information Security & Privacy welcomed the audience and introduced the judges.
About the Judges
- Blake Patton, Tech Square Ventures
Blake Patton is the founder and managing partner of Tech Square Ventures, a seed- and early-stage venture fund in Atlanta that invests in innovative startups with potential to transform their markets. Patton represents Tech Square Ventures on the boards of Cypress.io, Pointivo, PreTel Health, Sequr, and UserIQ, and is a board observer of Haste and Salesfusion. He also serves as Tech Square Venture’s fund manager for Engage, an innovative accelerator and venture fund in partnership with 10 leading corporations and Georgia Tech.
- Richard Telljohann, IBM Security
Rich Telljohann is Director for Business and Corporate Development for IBM Security. In this role, he leads the Technology Alliances and Ecosystem strategy and organization, and is also a core member of the M&A team.
- John Schanz, TDF Ventures
John Schanz has built high-performance teams that have navigated the industry through profound change. He has been recognized as a key contributor to the massive scaling and advancement of Internet infrastructure. John helped scale the global Internet core at Sprint, and his team enabled Aol to grow into the predominant Internet Service Provider of its era.Currently, John is a Senior Advisor at BBH Capital Partners, Graham Partners and TDF Ventures. John is on the Board of Congruex LiquidSky. He has held senior leadership positions at Comcast, Aol, Transaction Network Services, MediaCenters, Sprint and GE. He serves as chairman of the Board of Cabrini University.
About the Winners
Student Competition Prizes
Finalists will compete for over $100,000 in funding and prizes, as they move research from the lab to the marketplace. The National Science Foundation I-Corps Grants are available to the participating students.
The following Demo Day Finale prizes were awarded.
The following Demo Day Finale prizes were awarded
- $7,000 cash prize for Commercialization Track, courtesy of the Institute for Information Security and Privacy
Commercialization Track Winner: MLsploit
Evan Downing, Shang-Tse Chen, Nilaksh Das, Jinho Jung, Carter Yagemann, Polo Chau, Taesoo Kim, Le Song, Advisor - Wenke Lee
Machine learning is at risk of being attacked. As companies continue to depend on machine learning to solve their problems, more sophisticated attacks are being created to undermine and take advantage of machine learning algorithms. Worse, these machine learning attacks can have adverse effects on our physical world, like forcing a self-driving car to run a stop sign. MLsploit is a framework designed to solve this problem by allowing operators to evaluate their trained machine learning models against a variety of attacks in order to strengthen them. MLsploit focuses not just on image, video, and audio data, but also contains information security datasets used to detect malware and defend against network intrusions. Using MLsploit, a company can evaluate machine learning models trained on a number of different datasets which provide valuable services to themselves and to their customers.
Presenter: Evan Downing is a Ph.D. student studying the intersection between malware/ intrusion detection, machine learning, and adversarial machine learning. He works under Dr. Wenke Lee in the Institute for Information Security & Privacy (IISP). His current projects study how well machine learning and deep learning algorithms perform in the presence of classical security attacks as well as explaining what these algorithms have learned after training them on large datasets.
- $4,000 cash prize for Research Track, courtesy of the Institute for Information Security and Privacy.
Tie between Needlestack – Elizabeth Krizay & Home IoT – Omar Alrawi
($4,000 – split between 2,000/ $2 ,000)
Research Track Winner: Home-based IoT Security Evaluations
Omar Alrawi, Chaz Lever, , Fabian Monrose, Advisor - Manos Antonakakis
Home-based Internet-of-Thing (IoT) devices are often released with cyber vulnerabilities due to pressures related to time-to-market and production costs which may take priority over prudent security practices.
The team presents an objective approach to evaluating a home-based IoT deployment and uncovering latent vulnerabilities across all components. The approach includes:
Home-based Internet-of-Thing (IoT) devices are often released with cyber vulnerabilities due to pressures related to time-to-market and production costs which may take priority over prudent security practices.
The team presents an objective approach to evaluating a home-based IoT deployment and uncovering latent vulnerabilities across all components. The approach includes:
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Empirically quantifying security metrics for smart-home devices
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Comprehensively covering all aspects of smart home deployment (device, mobile application, cloud, and communication)
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Temporally measuring the security posture of home-based IoT devices and tracking their improvement through historical data
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Providing an open and transparent approach
Research Track Winner: Needlestack: An Obfuscation Framework for Protecting Browsing Privacy
Elizbeth J. Krizay, Advisor - Rachel Cummings
In response to a March 28, 2017, congressional resolution to repeal an earlier regulation, Internet Service Providers (ISPs) are allowed to collect and store private information such as every search, website visited, article read, and location of their subscribers.
In response to a March 28, 2017, congressional resolution to repeal an earlier regulation, Internet Service Providers (ISPs) are allowed to collect and store private information such as every search, website visited, article read, and location of their subscribers.
In response to this repeal, this research aims to create a technology (likely an internet plugin) that does not conceal a user’s data from an ISP as a VPN would, but rather with noise that is unidentifiable from his or her own browsing patterns. This noise will consist of randomly generated website requests that simulate human browsing behavior. The user’s own browsing history will still be available to the ISP, but it will be masked in a sea of similar, humanistic requests. The end result of this noise is that an ISP, or any other company with access to the user’s data, won’t be able to differentiate the real user data from that randomly generated by Needlestack, thus leaving the ISP unable to figure out sensitive information about the user. Rather than searching for a needle in a proverbial haystack, ISPs would be left searching for a needle in a stack of other needles.
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$2,000 cash prize for People's Choice Award, courtesy of the Institute for Information Security and Privacy.
CREATE-X Winner: RFDIDS – Tohid Shekari
Christian Bayens, Morris Cohen, Lukas Graber, Advisor - Raheem Beyah
Recent events affecting power grids (such as the Ukrainian blackout in 2015) have highlighted the vulnerabilities in modern power systems, especially power substations which form the backbone of electricity networks. There have been significant efforts among researchers to develop effective intrusion detection systems (IDS) in order to prevent such attacks or reduce their damaging consequences. However, all of the existing techniques require some level of trust from components on the SCADA network; hence, they are still vulnerable to sophisticated attacks that would compromise the SCADA system completely. This research presents a radio frequency-based distributed IDS which remains reliable even when the entire SCADA system is considered untrusted. The developed air-gapped sensor is also robust against replay/ spoofing attacks, meaning that the attacker is not able to feed it fake data.
Presenter: Tohid Shekari is currently a double major student (PhD in ECE and MSc in Cybersecurity) with the Department of Electrical and Computer Engineering, Georgia Institute of Technology. He is doing research on the security of power grids under the supervision of Dr. Raheem Beyah. Specifically, his current research interests include cybersecurity in power systems, power system resilience, and application of optimization methods in power system operation. Mr. Shekari has won several research awards including the Best Paper Award in the Hawaii International Conference on System Sciences (HICSS), 2018.
Recent events affecting power grids (such as the Ukrainian blackout in 2015) have highlighted the vulnerabilities in modern power systems, especially power substations which form the backbone of electricity networks. There have been significant efforts among researchers to develop effective intrusion detection systems (IDS) in order to prevent such attacks or reduce their damaging consequences. However, all of the existing techniques require some level of trust from components on the SCADA network; hence, they are still vulnerable to sophisticated attacks that would compromise the SCADA system completely. This research presents a radio frequency-based distributed IDS which remains reliable even when the entire SCADA system is considered untrusted. The developed air-gapped sensor is also robust against replay/ spoofing attacks, meaning that the attacker is not able to feed it fake data.
Presenter: Tohid Shekari is currently a double major student (PhD in ECE and MSc in Cybersecurity) with the Department of Electrical and Computer Engineering, Georgia Institute of Technology. He is doing research on the security of power grids under the supervision of Dr. Raheem Beyah. Specifically, his current research interests include cybersecurity in power systems, power system resilience, and application of optimization methods in power system operation. Mr. Shekari has won several research awards including the Best Paper Award in the Hawaii International Conference on System Sciences (HICSS), 2018.
- CREATE-X Launch program seat worth $4,000 in grant funding and $30,000 of value in services including legal services, space, mentorship, IP protection, and visibility)
The Cybersecurity Demo Day Finale at Georgia Tech brings together graduate students, faculty and industry thought leaders to explore emerging cybersecurity research. Attendees have the opportunity to engage with Georgia Tech's robust entrepreneurial ecosystem, including VentureLab, ATDC, and CREATE-X.
