In today’s interconnected digital world, where data plays a pivotal role in shaping various aspects of our lives, the need to safeguard individual privacy has never been more critical. This course is designed to provide you with a deep understanding of the evolving landscape of privacy concerns and equip you with cutting-edge privacy-enabling-techniques (PETs) to protect sensitive information. The course starts with situating the word privacy in the world of security and explains its distinct importance vis-a-vis its more popular counterpart, namely security. We subsequently deal with various privacy-enabling technique (PET) methods. The course starts with methods based on statistical techniques, like differential privacy. Subsequently, we deal with a plethora of cryptographic techniques. We emphasize Fully Homomorphic Encryption, which is the holy grail in modern-day computing, promising users the ability of arbitrary computation on encrypted data. We follow with another notion of encryption, namely searchable encryption, which allows users to offload and search data on encrypted data on the cloud. Finally, we deal with another fundamental PETs method, namely secure multi-party computation, which allows users to distribute and perform computations without divulging more than needed information on the private data of the users.
Another interesting and practical direction of achieving privacy is through systems approach, wherein the trust is in-built in computing systems. In this part of the course, we delve into modern-day computer architectures which are built on enforcing trust by isolating the trusted world, where sensitive information is processed, from the real world. These isolations intend to provide privacy guarantees against powerful adversary models.
Finally, the course puts forward several case studies where the studied methods are applied. These applications encompass Machine learning inference, cyber-physical systems, and even genome sequencing. All these and many more crucial applications, once again show the elegance and importance of the studied PETs techniques.
Lecture 1: Introduction to PETS
Lecture 2-3: Homomorphic Encryption
Leccture 4-7: Fully Homomorphic Encryption
Lecture 8-9: Searchable Encryption
Lecture 10-13: Searchable Symmetric Encryption
Lecture 14-15: Functional Encryption
Lecture 16: Attribute-based Encryption
Lecture 17-19: Differential Privacy
Lecture 20-21: Information-theoretic measures of Differential Privacy
Lecture 22: Application of Differential Privacy in practical use-cases
Lecture 23-25: Secure multi-party computation
Lecture 26: Sequestered Encryption
Lecture 27-29: Trusted Architecture
Lecture 30-32: Intel SGX, TDX, etc
Lecture 33: ARM Trustzone architecture
Lecture 34-35: Use case 1: Privacy Enabling machine Learning Inference
Lecture 36-37: Use case 2: Privacy enabling Cyber Physical Systems: Smart metering in smart grids
Total number of hours 37
1. Cynthia Dwork, Aaron Roth. “The Algorithmic Foundations of Differential Privacy Foundations and Trends in Theoretical Computer Science, Volume 9, Issue 3–4 August
2014pp 211–407, https://doi.org/10.1561/0400000042
2. Xun Yi, Russell Paulet, Elisa Bertino, Homomorphic Encryption and Applications (SpringerBriefs in Computer Science) 2014th Edition by Xun Yi (Author), Russell Paulet
Elisa Bertino
3. Ronald Cramer, Ivan Bjerre Damgård, Jesper Buus Nielsen, Aarhus Universitet, Secure Multiparty Computation and Secret Sharing, Cambridge University Press
Some of the other important references are:
• Cynthia Dwork and Aaron Roth (2014), "The Algorithmic Foundations of Differential Privacy", Foundations and Trends® in Theoretical Computer Science: Vol. 9: No. 3–4, pp
211-407. http://dx.doi.org/10.1561/0400000042
• Rashmi Agrawal, Ajay Joshi, On Architecting Fully Homomorphic Encryption-based Computing Systems, Springer.
• David Evans, Vladimir Kolesnikov and Mike Rosulek, A Pragmatic Introduction to Secure Multi-Party Computation, https://securecomputation.org/
• Resources on Fully Homomorphic Encryption, https://fPETs team link: CS60212: Privacy Enabling Technologies (Spring 2025) | General | Microsoft Teamshe.org/resources/
We will use with the channels on Microsoft teams for sharing of course materials, have announcements, etc. The teams link is as follows: Link
. Please check that channel regularly.