Corporate Talk


CORPORATE TALK SERIES


Nishanth Chandran

(Principal Researcher, Microsoft Research)

Bio: Nishanth Chandran is a Principal Researcher at Microsoft Research, India. His research interests are in problems related to cryptography, cloud security, confidential computing and secure computation. Prior to joining MSRI, Nishanth was a Researcher at AT&T Labs, and before that he was a Post-doctoral Researcher at MSR Redmond.

Nishanth is a recipient of the 2010 Chorafas Award for exceptional achievements in research and his research has received coverage in science journals and in the media at venues such as Nature and MIT Technology Review. He has published several papers in top computer science conferences and journals such as ACM CCS, Crypto, Eurocrypt, IEEE S&P, and so on. His work on position-based cryptography was selected as one of the top 3 works and invited to QIP 2011 as a plenary talk. Nishanth has served on the technical program committee of all the top cryptography conferences on several occasions and he also holds 6 US Patents. Nishanth received his Ph.D. and M.S. in Computer Science, both from UCLA, and B.E. in Computer Science and Engineering from Anna University (Hindustan College of Engineering), Chennai.

Nishanth is also a top ranking (A grade) All India Radio South Indian Classical (Carnatic) Violinist and has performed at international venues such as the Hollywood Bowl, Los Angeles (as part of legendary sitarist Late Pandit Ravi Shankar’s ensemble) and the Madras Music Academy, Chennai.

Title of the Talk: Privacy-Preserving Machine Learning

Abstract: Can multiple entities compute joint functions on their private data without revealing it in the clear with any other entity? Cryptography provides an answer to this intriguing question through the primitive of secure multi-party computation (MPC). A fascinating use-case of MPC is the task of privacy preserving machine learning. A patient can obtain a diagnosis of his/her disease from the owner of an ML model for the disease without revealing his/her private medical information to the model owner nor learning anything else about the ML model. Such a technology could be invaluable towards realizing the full potential of Machine Learning as a Service.

In this talk, I will provide an overview of the area of privacy preserving machine learning. I will also describe a system CrypTFlow, developed at Microsoft Research India, that for the first time, enables such privacy preserving machine learning at the scale of the ImageNet dataset.


Matthew Krieger

(VP of Technology at Cober, Inc.)

Bio: Matthew Krieger is a technologist and executive with experience in IT, manufacturing and publishing. He is VP of Technology for Cober, Inc. and previously held senior IT leadership positions at Time, Inc. and the Reader’s Digest Association. Matt is Chief Technology Officer and sits on the Operating Committee of the SCORE Fairfield County Connecticut chapter, provides CTO guidance for TeenSmart International, and is on the Southern Connecticut State University Computer Science Technical Advisory Committee. Matt is also President of the Reader’s Digest Partners for Sight Foundation non-profit, is on the advisory board of Cyber-Seniors and until recently served on the Advisory Board for the Baruch College Computer Center for Visually Impaired People, having been part of a team that successfully transitioned the Center to a new home. Matt is a frequent presenter on topics of business and technology. Matt is also creator of Whysper, a platform allowing the consumption of web content as text-to-speech podcasts.

Title of the Talk: IoT Security – Even More Complex Than It Seems

Abstract: IoT security is a complex topic with broad scope. Beyond basic physical device security and protection of communications from prying eyes are considerations around device authentication, ensuring message integrity, ongoing patch management, standardizing protocols, securing the massive surface area of the rapidly growing footprint of IoT sensors, secure-from-the-start development practices, the mismatch between IT and industrial networks and more. This talk will explore the definition of security in the context of IoT, cover threats to the IoT devices and networks, touch on the current state of IoT security from a regulatory perspective and explore options for securing the IoT ecosystem.


 

Important Deadlines

Full Paper Submission:28th September 2020
Acceptance Notification: 9th October 2020
Final Paper Submission:27th October 2020
Early Bird Registration: 22nd October 2020
Presentation Submission: 28th October 2020
Conference: 4 - 7 November 2020

Previous Conferences

IEEE IEMCON 2019

IEEE IEMCON 2018

IEEE IEMCON 2017

Search

 

Generic selectors
Exact matches only
Search in title
Search in content
Search in posts
Search in pages
Filter by Categories
Uncategorized

 

Announcements

• Conference Proceedings will be submitted for publication at IEEE Xplore® digital library .

• Best Paper Award will be given for each track.

• Conference Record No