Data Science

General Objectives Ensuring the privacy of personal data, and securing the computing infrastructures, are key concerns when collecting and analyzing sensitive data sets. Example of these data sets include medical data, personal communication, personal and company-wide financial information. The course is meant to cover an overview of modern techniques aimed at protecting data privacy and security in such applications. Specific Objectives The students will learn the basic cryptographic techniques and their application to obtaining privacy of data in several applications, including cloud computing, statistical databases, distributed computation, and cryptocurrencies. Knowledge and Understanding -) Modern cryptographic techniques and their limitations. -) Techniques for achieving privacy in statistical databases. -) Techniques for designing cryptographic currencies and distributed ledgers. -) Techniques for secure distributed multiparty computation. Applying knowledge and understanding: -) How to select the right cryptographic scheme for a particular application. -) How to design a differentially private mechanism. -) How to program a secure cryptosystem, or a secure smart contract, or a secure cryptographic protocol. Autonomy of Judgment The students will be able to judge the security of the main cryptographic applications. Communication Skills How to describe the security of cryptographic standards, privacy-preserving statistical databases, and blockchains. Next Study Abilities The students interested in research will learn what are the main open challenges in the area, and will obtain the necessary background for a deeper study of the subjects.