COL865 Special topic on Computer Applications

1. Class schedule: 1530-1700 on Tuesdays and Fridays (AD slot)
2. Please email {svs,suban}@iitd.ac.in with COL865 in the Subject if you are not registered in the course but are interested in attending.
3. All students interested in attending the course are requested to email a one page pdf indicating:
   1. the reason for your interest in the course
   2. any prior reading that you may have done on the topic and
   3. your views on the issues to be covered in the course.

• Sep 29 (pdf).
• Oct 6 (pdf). Refer to the section on general reading for reading material on the privacy judgment and the part 3 of the Constitution.
• Oct 9,10 (pdf). See The Digital Person: Technology and Privacy in the Information Age by Daniel J Solove.
• Oct 13 (Guest lecture on Data protection by Malavika Raghavan) (pdf). See Graham Greenleaf's Web Pages, GDPR, Personal data protection bill 2019.
• Oct 16 (Guest lecture on Personal Data protection bill by Malavika Raghavan) (pdf). Also see the marked-up draft bill.
• Oct 17. Privacy requirements. (pdf).
• Oct 17,20. On nature of computing. (pdf).
• Oct 20,27,31. Intro to modular arithmetic; symmetric and public-key cryptography (pdf). See A Course in Cryptography by Rafael Pass and Abhi Shelat.
• Nov 3,6. Crypto basics (pdf). See A Course in Cryptography by Rafael Pass and Abhi Shelat.
• Nov 6,13. Interactive and Zero-knowledge proofs (pdf). See A Course in Cryptography by Rafael Pass and Abhi Shelat.
• Nov 17. Transactional privacy and data minimization: linkable and unlinkable credentials, untraceability, virtual ids, anonymous credentials, blind signatures. (pdf). See A Course in Cryptography by Rafael Pass and Abhi Shelat; Security without Identification: Card Computers to make Big Brother Obsolete by David Chaum.
• Nov 20,24. Data minimization (pdf), Inferential privacy and anonymization, impossibility results (pdf). See Differential privacy by Cynthia Dwork (a copy accessible here only from within IITD; Robust De-anonymization of Large Sparse Datasets by Arvind Narayanan and Vitaly Shmatikov (also see the 2019 follow-up).
• Nov 24,27; Dec 15. Electronic voting (pdf). References linked in the slides. Also see Rivest, 2001a, Rivest, 2001b, Tufekci, 2019 and the 2018 report of the US National Academies of Sciences, Engineering and Medicine for arguments against internet voting.
• Dec 18. Public bulletin boards (pdf). Also see The append-only web bulletin board by James Heather and David Lundin.
• Dec 22. Blockchains (pdf)
• Dec 26,29. Elements of a privacy architecture: requirements and case studies (pdf)
• Dec 29, Jan 2. An architecture for privacy-by-design (pdf)

India is arguably the biggest deployer of digitization in public life with large public service applications (in-use or contemplated) like national identity, electronic voting, health registry, national population and voter registries, public credit registry, income and other tax registries, face recognition based access control to airports and other facilities, bluetooth based contact tracing and a national intelligence grid. However, the privacy issues in these are not well understood, and this has led to a constant tension between the state and the civil society and privacy activists resulting in several constitutional cases in the Supreme court and various High courts. The possibilities of inferential privacy violations with modern machine learning (whether deliberate or inadvertent), or unfair and discriminatory processing of data, compound the problem.

In this course we will unpack the privacy requirements in such applications from both legal and technical points of view. We will investigate the possibilities of early alignment of the two and examine if it is possible to outline the necessary and sufficient conditions for privacy protection. We will then review the privacy protection techniques in computer science ranging from encryption and applied cryptography, electronic voting, database and network security, trusted execution environments, blockchains, anonymization and other data minimisation techniques and evaluate their suitability for privacy protection. In the final part of the course we will investigate the architectural possibilities for privacy protection - from both legal and technical perspectives - that may help not only in design but also in assessing vulnerabilities and omissions.

The evaluations in this course will be based on scribing, reading and presentations, small implementations and a project cum term paper.

The course will not assume any background in cryptography and security, though familiarity will be useful. As such, the course will be accessible to all engineering students with 3rd year level maturity. The course however will assume familiarity with basic computing and probability. It will also assume some good common sense.