Schedule | CS561 Topics in Data Privacy

Tentative Schedule

Week/Dates	Tuesday	Thursday	Reading Materials
W1, 08/19 - 08/22	Introduction	Reidentification Attacks	k-Anonymity: a Model for Protecting Privacy l-Diversity: Privacy Beyond k-Anonymity t-Closeness: Privacy Beyond k-Anonymity and l-Diversity Composition Attacks and Auxiliary Information in Data Privacy Minimality Attack in Privacy Preserving Data Publishing
W2, 08/25 - 08/29	Reconstruction Attacks	Reconstruction Attacks (cont.)	Robust De-anonymization of Large Sparse Datasets Wherefore Art Thou R3579X? Anonymized Social Networks, Hidden Patterns, and Structural Steganography De-anonymizing Social Networks Link Prediction by De-anonymization: How We Won the Kaggle Social Network Challenge Understanding Database Reconstruction Attacks on Public Data Revealing Information while Preserving Privacy Linear Program Reconstruction in Practice
W3, 09/01 - 09/05	No Class	Secure Multi-Party Computation (MPC)	New Directions in Cryptography A Public Key Cryptosystem and a Signature Scheme Based on Discrete Logarithms A Randomized Protocol for Signing Contracts Protocols for Secure Computations
W4, 09/08 - 09/12	Homomorphic Encryption (HE)	Zero Knowledge Proofs (ZK)	Fully Homomorphic Encryption Using Ideal Lattices Fully Homomorphic Encryption over the Integers Implementing Gentry’s Fully-Homomorphic Encryption Scheme Efficient Fully Homomorphic Encryption from (Standard) LWE (Leveled) Fully Homomorphic Encryption without Bootstrapping Fully Homomorphic SIMD Operations Homomorphic Encryption from Learning with Errors: Conceptually-Simpler, Asymptotically-Faster, Attribute-Based Lattice-Based FHE as Secure as PKE FHEW: Bootstrapping Homomorphic Encryption in Less than a Second Homomorphic Encryption for Arithmetic of Approximate Numbers TFHE: Fast Fully Homomorphic Encryption over the Torus Secure Large-Scale Genome-Wide Association Studies Using Homomorphic Encryption CryptoNets: Applying Neural Networks to Encrypted Data with High Throughput and Accuracy The Knowledge Complexity of Interactive Proof Systems A Note on Efficient Zero-knowledge Proofs and Arguments Computationally Sound Proofs Pinocchio: Nearly Practical Verifiable Computation On the Size of Pairing-based Non-interactive Arguments Scalable, Transparent, and Post-Quantum Secure Computational Integrity
W5, 09/15 - 09/19	Intro to Differential Privacy (DP)	DP Mechanisms	Calibrating Noise to Sensitivity in Private Data Analysis Our Data, Ourselves: Privacy via Distributed Noise Generation Mechanism Design via Differential Privacy
W6, 09/22 - 09/26	No Class	DP Mechanisms	On Significance of the Least Significant Bits For Differential Privacy Renyi Differential Privacy Randomized Response: A Survey Technique for Eliminating Evasive Answer Bias Universally Utility-Maximizing Privacy Mechanisms Understanding the Sparse Vector Technique for Differential Privacy Boosting the Accuracy of Differentially Private Histograms through Consistency Differential Privacy via Wavelet Transforms Privtree: A Differentially Private Algorithm for Hierarchical Decompositions Differentially Private Spatial Decompositions A Data-and-Workload-Aware Algorithm for Range Queries under Differential Privacy Differentially Private k-Means Clustering RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response Locally Differentially Private Protocols for Frequency Estimation
W7, 09/29 - 10/03	More DP Mechanisms	No Class
W8, 10/06 - 10/10	Privacy Accounting	Private Machine Learning
W9, 10/13 - 10/17	Additional Topics in DP	Additional Topics in DP
W10, 10/20 - 10/24	Additional Topics in DP	Midtern Exam
W11, 10/27 - 10/31	TBA	TBA
W12, 11/03 - 11/07	Presentation	Presentation
W13, 11/10 - 11/14	Presentation	Presentation
W14, 11/17 - 11/21	Presentation	Presentation
W15, 11/24 - 11/28	Prensetation	No Class
W16, 12/01 - 12/05	Final Project Presentation	Final Project Presentation