A Multi-Disciplinary Perspective for Conducting Artificial Intelligence-enabled Privacy Analytics: Connecting Data, Algorithms, and Systems
Speaker
Sagar Samtani
Indiana University
Host
Srinivas Devadas
CSAIL
Abstract:
Privacy concerns have rapidly emerged as a significant societal issue. Events such as
Facebook-Cambridge Analytica scandal and data aggregation efforts by technology providers have
illustrated how fragile modern society is to privacy violations. Internationally recognized entities such as
the National Science Foundation (NSF) have indicated that Artificial Intelligence (AI)-enabled models,
artifacts, and systems can efficiently and effectively sift through large quantities of data from legal
documents, social media, Dark Web sites, and other sources to curb privacy violations. Yet considerable
efforts are still required for understanding prevailing data sources, systematically developing AI-enabled
privacy analytics to tackle emerging challenges, and deploying systems to address critical privacy needs.
To this end, I provide an overview of prevailing data sources that can support AI-enabled privacy
analytics; a multi-disciplinary research framework that connects data, algorithms, and systems to tackle
emerging AI-enabled privacy analytics challenges such as entity resolution, privacy assistance systems,
privacy risk modeling, and more; a summary of selected funding sources to support high-impact privacy
analytics research; and an overview of prevailing conference and journal venues that can be leveraged to
share and archive privacy analytics research. I will also provide some recent examples of how deep
learning-based algorithms can be developed to support privacy applications, such as identifying how
companies adjust their privacy policies in light of emerging regulations (e.g., GDPR).
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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 (IU). He
is also a Fellow within the Center for Applied Cybersecurity Research at IU. Samtani graduated with his
Ph.D. in May 2018 from the Artificial Intelligence (AI) Lab in University of Arizona’s Management
Information Systems (MIS) department. From 2014 – 2017, Samtani served as a National Science
Foundation (NSF) CyberCorps Scholarship-for-Service (SFS) Fellow. Samtani’s research centers around
Artificial Intelligence for Cybersecurity and Cyber Threat Intelligence (CTI). Recent topics include deep
learning, network science, and text mining approaches for open source software security, scientific
cyberinfrastructure security, AI risk management, and Dark Web analytics. Samtani has published over
forty journal and conference papers on these topics in leading Information Systems (IS) venues such
as MIS Quarterly, Journal of MIS, cybersecurity venues such as ACM Transactions on Privacy and
Security, IEEE S&P, and Computers and Security, and machine learning venues such as ACM KDD,
IEEE ICDM, IEEE Intelligent Systems, and others. His research has received over $2M in funding from
NSF’s cybersecurity programs, including Secure and Trustworthy Cyberspace (SaTC) for cybersecurity
research and education, Cybersecurity Innovation for Cyberinfrsatructure (CICI) for operational
cybersecurity research, and CyberCorps SFS for cybersecurity workforce development. One of these
awards was under the CISE Research Initiation Initiative (CRII), also commonly known as the “Pre-
CAREER” Award. Dr. Samtani has co-founded workshops on AI for Cybersecurity topics at ACM KDD
and IEEE ICDM. He has also served as a Guest Editor on topics pertaining to AI for Cybersecurity
at IEEE Transactions on Dependable and Secure Computing (TDSC) and ACM Transactions on MIS. 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, CAMLIS, and others. He currently serves as an Associate Editor for ACM TMIS
and Information and Management. He is deeply engaged with industry, serving on the CompTIA ISAO
Executive Advisory Council and Board of Directors for the DEFCON AI Village. Similarly, he regularly
presents at industry venues and conferences, including DEFCON, JPMorgan Chase, IT Nation, and
others. Samtani has won several awards, including the ACM SIGMIS Doctoral Dissertation award in
2019, Runner-Up for the INFORMS Nunamaker-Chen Dissertation Award in 2018, and multiple teaching
awards for courses on AI for cybersecurity, CTI, and business analytics. Samtani has received media
attention from outlets such as Miami Herald, Fox, Science Magazine, AAAS, Associated Press, and
the Penny Hoarder. He is a member of INFORMS, AIS, ACM, IEEE, and INNS.
Privacy concerns have rapidly emerged as a significant societal issue. Events such as
Facebook-Cambridge Analytica scandal and data aggregation efforts by technology providers have
illustrated how fragile modern society is to privacy violations. Internationally recognized entities such as
the National Science Foundation (NSF) have indicated that Artificial Intelligence (AI)-enabled models,
artifacts, and systems can efficiently and effectively sift through large quantities of data from legal
documents, social media, Dark Web sites, and other sources to curb privacy violations. Yet considerable
efforts are still required for understanding prevailing data sources, systematically developing AI-enabled
privacy analytics to tackle emerging challenges, and deploying systems to address critical privacy needs.
To this end, I provide an overview of prevailing data sources that can support AI-enabled privacy
analytics; a multi-disciplinary research framework that connects data, algorithms, and systems to tackle
emerging AI-enabled privacy analytics challenges such as entity resolution, privacy assistance systems,
privacy risk modeling, and more; a summary of selected funding sources to support high-impact privacy
analytics research; and an overview of prevailing conference and journal venues that can be leveraged to
share and archive privacy analytics research. I will also provide some recent examples of how deep
learning-based algorithms can be developed to support privacy applications, such as identifying how
companies adjust their privacy policies in light of emerging regulations (e.g., GDPR).
Zoom Info:
Join Zoom Meeting
https://mit.zoom.us/j/97527284254
Password: <3security
One tap mobile
+16465588656,,97527284254# US (New York)
+16699006833,,97527284254# US (San Jose)
Meeting ID: 975 2728 4254
US : +1 646 558 8656 or +1 669 900 6833
International Numbers: https://mit.zoom.us/u/auBvg4NEV
Join by SIP
97527284254@zoomcrc.com
Join by Skype for Business
https://mit.zoom.us/skype/97527284254
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 (IU). He
is also a Fellow within the Center for Applied Cybersecurity Research at IU. Samtani graduated with his
Ph.D. in May 2018 from the Artificial Intelligence (AI) Lab in University of Arizona’s Management
Information Systems (MIS) department. From 2014 – 2017, Samtani served as a National Science
Foundation (NSF) CyberCorps Scholarship-for-Service (SFS) Fellow. Samtani’s research centers around
Artificial Intelligence for Cybersecurity and Cyber Threat Intelligence (CTI). Recent topics include deep
learning, network science, and text mining approaches for open source software security, scientific
cyberinfrastructure security, AI risk management, and Dark Web analytics. Samtani has published over
forty journal and conference papers on these topics in leading Information Systems (IS) venues such
as MIS Quarterly, Journal of MIS, cybersecurity venues such as ACM Transactions on Privacy and
Security, IEEE S&P, and Computers and Security, and machine learning venues such as ACM KDD,
IEEE ICDM, IEEE Intelligent Systems, and others. His research has received over $2M in funding from
NSF’s cybersecurity programs, including Secure and Trustworthy Cyberspace (SaTC) for cybersecurity
research and education, Cybersecurity Innovation for Cyberinfrsatructure (CICI) for operational
cybersecurity research, and CyberCorps SFS for cybersecurity workforce development. One of these
awards was under the CISE Research Initiation Initiative (CRII), also commonly known as the “Pre-
CAREER” Award. Dr. Samtani has co-founded workshops on AI for Cybersecurity topics at ACM KDD
and IEEE ICDM. He has also served as a Guest Editor on topics pertaining to AI for Cybersecurity
at IEEE Transactions on Dependable and Secure Computing (TDSC) and ACM Transactions on MIS. 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, CAMLIS, and others. He currently serves as an Associate Editor for ACM TMIS
and Information and Management. He is deeply engaged with industry, serving on the CompTIA ISAO
Executive Advisory Council and Board of Directors for the DEFCON AI Village. Similarly, he regularly
presents at industry venues and conferences, including DEFCON, JPMorgan Chase, IT Nation, and
others. Samtani has won several awards, including the ACM SIGMIS Doctoral Dissertation award in
2019, Runner-Up for the INFORMS Nunamaker-Chen Dissertation Award in 2018, and multiple teaching
awards for courses on AI for cybersecurity, CTI, and business analytics. Samtani has received media
attention from outlets such as Miami Herald, Fox, Science Magazine, AAAS, Associated Press, and
the Penny Hoarder. He is a member of INFORMS, AIS, ACM, IEEE, and INNS.