Efficient Communication-Storage Tradeoffs for Multicast Encryption. - Ran Canetti; Tal Malkin; Kobbi Nissim (EUROCRYPT, 1999)

Firmato: A Novel Firewall Management Toolkit. - Yair Bartal; Alain J. Mayer; Kobbi Nissim; Avishai Wool (S&P, 1999)

On the Security of Pay-per-Click and Other Web Advertising Schemes. - Vinod Anupam; Alain J. Mayer; Kobbi Nissim; Benny Pinkas; Michael K. Reiter (Comput. Networks, 1999)

On the hardness of approximating N P witnesses. - Uriel Feige; Michael Langberg; Kobbi Nissim (APPROX, 2000)

Approximating the minimum bisection size (extended abstract). - Uriel Feige; Robert Krauthgamer; Kobbi Nissim (STOC, 2000)

Certificate revocation and certificate update. - Moni Naor; Kobbi Nissim (IEEE J. Sel. Areas Commun., 2000)

Private approximation of NP-hard functions. - Shai Halevi; Robert Krauthgamer; Eyal Kushilevitz; Kobbi Nissim (STOC, 2001)

Communication preserving protocols for secure function evaluation. - Moni Naor; Kobbi Nissim (STOC, 2001)

Communication Complexity and Secure Function Evaluation - Moni Naor; Kobbi Nissim (Electron. Colloquium Comput. Complex., 2001)

Extending Oblivious Transfers Efficiently. - Yuval Ishai; Joe Kilian; Kobbi Nissim; Erez Petrank (CRYPTO, 2003)

Revealing information while preserving privacy. - Irit Dinur; Kobbi Nissim (PODS, 2003)

On Cutting a Few Vertices from a Graph. - Uriel Feige; Robert Krauthgamer; Kobbi Nissim (Discret. Appl. Math., 2003)

Privacy-Preserving Datamining on Vertically Partitioned Databases. - Cynthia Dwork; Kobbi Nissim (CRYPTO, 2004)

Efficient Private Matching and Set Intersection. - Michael J. Freedman; Kobbi Nissim; Benny Pinkas (EUROCRYPT, 2004)

Communication Versus Computation. - Prahladh Harsha; Yuval Ishai; Joe Kilian; Kobbi Nissim; Srinivasan Venkatesh 001 (ICALP, 2004)

Firmato: A novel firewall management toolkit. - Yair Bartal; Alain J. Mayer; Kobbi Nissim; Avishai Wool (ACM Trans. Comput. Syst., 2004)

Practical privacy: the SuLQ framework. - Avrim Blum; Cynthia Dwork; Frank McSherry; Kobbi Nissim (PODS, 2005)

Simulatable auditing. - Krishnaram Kenthapadi; Nina Mishra; Kobbi Nissim (PODS, 2005)

Evaluating 2-DNF Formulas on Ciphertexts. - Dan Boneh; Eu-Jin Goh; Kobbi Nissim (TCC, 2005)

Communication Efficient Secure Linear Algebra. - Kobbi Nissim; Enav Weinreb (TCC, 2006)

Hard Instances of the Constrained Discrete Logarithm Problem. - Ilya Mironov; Anton Mityagin; Kobbi Nissim (IACR Cryptol. ePrint Arch., 2006)

Secure multiparty computation of approximations. - Joan Feigenbaum; Yuval Ishai; Tal Malkin; Kobbi Nissim; Martin J. Strauss; Rebecca N. Wright (ACM Trans. Algorithms, 2006)

Smooth sensitivity and sampling in private data analysis. - Kobbi Nissim; Sofya Raskhodnikova; Adam D. Smith 001 (STOC, 2007)

Communication vs. Computation. - Prahladh Harsha; Yuval Ishai; Joe Kilian; Kobbi Nissim; Srinivasan Venkatesh 001 (Comput. Complex., 2007)

Distributed Private Data Analysis: Simultaneously Solving How and What. - Amos Beimel; Kobbi Nissim; Eran Omri (CRYPTO, 2008)

Private Approximation of Search Problems. - Amos Beimel; Paz Carmi; Kobbi Nissim; Enav Weinreb (SIAM J. Comput., 2008)

Private Data Analysis via Output Perturbation - A Rigorous Approach to Constructing Sanitizers and Privacy Preserving Algorithms. - Kobbi Nissim (Privacy-Preserving Data Mining, 2008)

Private coresets. - Dan Feldman; Amos Fiat; Haim Kaplan; Kobbi Nissim (STOC, 2009)

Private Approximation of Clustering and Vertex Cover. - Amos Beimel; Renen Hallak; Kobbi Nissim (Comput. Complex., 2009)

First Issue Editorial. - John M. Abowd; Kobbi Nissim; Chris J. Skinner (J. Priv. Confidentiality, 2009)

Bounds on the Sample Complexity for Private Learning and Private Data Release. - Amos Beimel; Shiva Prasad Kasiviswanathan; Kobbi Nissim (TCC, 2010)

How Should We Solve Search Problems Privately? - Amos Beimel; Tal Malkin; Kobbi Nissim; Enav Weinreb (J. Cryptol., 2010)

What Can We Learn Privately? - Shiva Prasad Kasiviswanathan; Homin K. Lee; Kobbi Nissim; Sofya Raskhodnikova; Adam D. Smith 001 (SIAM J. Comput., 2011)

Approximately optimal mechanism design via differential privacy. - Kobbi Nissim; Rann Smorodinsky; Moshe Tennenholtz (ITCS, 2012)

Privacy-aware mechanism design. - Kobbi Nissim; Claudio Orlandi; Rann Smorodinsky (EC, 2012)

Hiding the Input-Size in Secure Two-Party Computation. - Yehuda Lindell; Kobbi Nissim; Claudio Orlandi (IACR Cryptol. ePrint Arch., 2012)

Efficient Set Operations in the Presence of Malicious Adversaries. - Carmit Hazay; Kobbi Nissim (J. Cryptol., 2012)

Characterizing the sample complexity of private learners. - Amos Beimel; Kobbi Nissim; Uri Stemmer (ITCS, 2013)

Analyzing Graphs with Node Differential Privacy. - Shiva Prasad Kasiviswanathan; Kobbi Nissim; Sofya Raskhodnikova; Adam D. Smith 001 (TCC, 2013)

Attacks on statistical databases: The highly noisy case. - Alexander Kantor; Kobbi Nissim (Inf. Process. Lett., 2013)

Denials leak information: Simulatable auditing. - Krishnaram Kenthapadi; Nina Mishra; Kobbi Nissim (J. Comput. Syst. Sci., 2013)

Redrawing the boundaries on purchasing data from privacy-sensitive individuals. - Kobbi Nissim; Salil P. Vadhan; David Xiao (ITCS, 2014)

Bounds on the sample complexity for private learning and private data release. - Amos Beimel; Hai Brenner; Shiva Prasad Kasiviswanathan; Kobbi Nissim (Mach. Learn., 2014)

Impossibility of Differentially Private Universally Optimal Mechanisms. - Hai Brenner; Kobbi Nissim (SIAM J. Comput., 2014)

Fair Information Sharing for Treasure Hunting. - Yiling Chen 001; Kobbi Nissim; Bo Waggoner (AAAI, 2015)

Differentially Private Release and Learning of Threshold Functions. - Mark Bun; Kobbi Nissim; Uri Stemmer; Salil P. Vadhan (FOCS, 2015)

GRECS: Graph Encryption for Approximate Shortest Distance Queries. - Xianrui Meng; Seny Kamara; Kobbi Nissim; George Kollios (IACR Cryptol. ePrint Arch., 2015)

Generic Attacks on Secure Outsourced Databases. - Georgios Kellaris; George Kollios; Kobbi Nissim; Adam O'Neill (CCS, 2016)

Adaptive Learning with Robust Generalization Guarantees. - Rachel Cummings; Katrina Ligett; Kobbi Nissim; Aaron Roth 001; Zhiwei Steven Wu (COLT, 2016)

Locating a Small Cluster Privately. - Kobbi Nissim; Uri Stemmer; Salil P. Vadhan (PODS, 2016)

PSI (Ψ): a Private data Sharing Interface. - Marco Gaboardi; James Honaker; Gary King; Kobbi Nissim; Jonathan R. Ullman; Salil P. Vadhan (CoRR, 2016)

Efficient Set Intersection with Simulation-Based Security. - Michael J. Freedman; Carmit Hazay; Kobbi Nissim; Benny Pinkas (J. Cryptol., 2016)

Calibrating Noise to Sensitivity in Private Data Analysis. - Cynthia Dwork; Frank McSherry; Kobbi Nissim; Adam D. Smith 001 (J. Priv. Confidentiality, 2016)

Private Learning and Sanitization: Pure vs. Approximate Differential Privacy. - Amos Beimel; Kobbi Nissim; Uri Stemmer (Theory Comput., 2016)

Mechanism Design and Differential Privacy. - Kobbi Nissim; David Xiao (Encyclopedia of Algorithms, 2016)

Private Incremental Regression. - Shiva Prasad Kasiviswanathan; Kobbi Nissim; Hongxia Jin (PODS, 2017)

Accessing Data while Preserving Privacy. - Georgios Kellaris; George Kollios; Kobbi Nissim; Adam O'Neill (CoRR, 2017)

Clustering Algorithms for the Centralized and Local Models. - Kobbi Nissim; Uri Stemmer (ALT, 2018)

The Limits of Post-Selection Generalization. - Jonathan R. Ullman; Adam D. Smith 001; Kobbi Nissim; Uri Stemmer; Thomas Steinke 002 (NeurIPS, 2018)

Computational Two-Party Correlation. - Iftach Haitner; Kobbi Nissim; Eran Omri; Ronen Shaltiel; Jad Silbak (Electron. Colloquium Comput. Complex., 2018)

Segmentation, Incentives, and Privacy. - Kobbi Nissim; Rann Smorodinsky; Moshe Tennenholtz (Math. Oper. Res., 2018)

Exploring Differential Obliviousness. - Amos Beimel; Kobbi Nissim; Mohammad Zaheri (APPROX-RANDOM, 2019)

Private Center Points and Learning of Halfspaces. - Amos Beimel; Shay Moran; Kobbi Nissim; Uri Stemmer (COLT, 2019)

The Privacy Blanket of the Shuffle Model. - Borja Balle; James Bell 001; Adrià Gascón; Kobbi Nissim (CRYPTO (2), 2019)

Surveillance and privacy in the public and private sectors: panel. - Stefan Savage; Ian Levy; Kobbi Nissim; Paul Ohm; Carmela Troncoso; Nicole Wong (CSLAW, 2019)

Differentially Private Summation with Multi-Message Shuffling. - Borja Balle; James Bell 001; Adrià Gascón; Kobbi Nissim (CoRR, 2019)

Improved Summation from Shuffling. - Borja Balle; James Bell 001; Adrià Gascón; Kobbi Nissim (CoRR, 2019)

The Complexity of Verifying Circuits as Differentially Private. - Marco Gaboardi; Kobbi Nissim; David Purser (CoRR, 2019)

Characterizing the Sample Complexity of Pure Private Learners. - Amos Beimel; Kobbi Nissim; Uri Stemmer (J. Mach. Learn. Res., 2019)

Simultaneous Private Learning of Multiple Concepts. - Mark Bun; Kobbi Nissim; Uri Stemmer (J. Mach. Learn. Res., 2019)

Concentration Bounds for High Sensitivity Functions Through Differential Privacy. - Uri Stemmer; Kobbi Nissim (J. Priv. Confidentiality, 2019)

Private Summation in the Multi-Message Shuffle Model. - Borja Balle; James Bell 001; Adrià Gascón; Kobbi Nissim (CCS, 2020)

The Complexity of Verifying Loop-Free Programs as Differentially Private. - Marco Gaboardi; Kobbi Nissim; David Purser (ICALP, 2020)

The Power of Synergy in Differential Privacy: Combining a Small Curator with Local Randomizers. - Amos Beimel; Aleksandra Korolova; Kobbi Nissim; Or Sheffet; Uri Stemmer (ITC, 2020)

Modernizing Data Control: Making Personal Digital Data Mutually Beneficial for Citizens and Industry. - Sujata Banerjee; Yiling Chen 001; Kobbi Nissim; David C. Parkes; Katie A. Siek; Lauren Wilcox (CoRR, 2020)

On the Round Complexity of the Shuffle Model. - Amos Beimel; Iftach Haitner; Kobbi Nissim; Uri Stemmer (IACR Cryptol. ePrint Arch., 2020)

Practical Locally Private Heavy Hitters. - Raef Bassily; Kobbi Nissim; Uri Stemmer; Abhradeep Thakurta (J. Mach. Learn. Res., 2020)

Linear Program Reconstruction in Practice. - Aloni Cohen; Kobbi Nissim (J. Priv. Confidentiality, 2020)

On Privacy in the Age of COVID-19. - Cynthia Dwork; Alan F. Karr; Kobbi Nissim; Lars Vilhuber (J. Priv. Confidentiality, 2020)

Towards formalizing the GDPR's notion of singling out. - Aloni Cohen; Kobbi Nissim (Proc. Natl. Acad. Sci. USA, 2020)

Computational Two-Party Correlation: A Dichotomy for Key-Agreement Protocols. - Iftach Haitner; Kobbi Nissim; Eran Omri; Ronen Shaltiel; Jad Silbak (SIAM J. Comput., 2020)

εpsolute: Efficiently Querying Databases While Providing Differential Privacy. - Dmytro Bogatov; Georgios Kellaris; George Kollios; Kobbi Nissim; Adam O'Neill (CCS, 2021)

Separating Adaptive Streaming from Oblivious Streaming Using the Bounded Storage Model. - Haim Kaplan; Yishay Mansour; Kobbi Nissim; Uri Stemmer (CRYPTO (3), 2021)

Privacy: From Database Reconstruction to Legal Theorems. - Kobbi Nissim (PODS, 2021)

Foundations for Robust Data Protection: Co-designing Law and Computer Science. - Kobbi Nissim; Alexandra Wood (TPS-ISA, 2021)

Learning Privately with Labeled and Unlabeled Examples. - Amos Beimel; Kobbi Nissim; Uri Stemmer (Algorithmica, 2021)

Separating Adaptive Streaming from Oblivious Streaming. - Haim Kaplan; Yishay Mansour; Kobbi Nissim; Uri Stemmer (CoRR, 2021)

Algorithmic Stability for Adaptive Data Analysis. - Raef Bassily; Kobbi Nissim; Adam D. Smith 001; Thomas Steinke 002; Uri Stemmer; Jonathan R. Ullman (SIAM J. Comput., 2021)

Dynamic algorithms against an adaptive adversary: generic constructions and lower bounds. - Amos Beimel; Haim Kaplan; Yishay Mansour; Kobbi Nissim; Thatchaphol Saranurak; Uri Stemmer (STOC, 2022)

The Sample Complexity of Distribution-Free Parity Learning in the Robust Shuffle Model. - Kobbi Nissim; Chao Yan (J. Priv. Confidentiality, 2022)

Black-Box Differential Privacy for Interactive ML. - Haim Kaplan; Yishay Mansour; Shay Moran; Kobbi Nissim; Uri Stemmer (NeurIPS, 2023)

Private Everlasting Prediction. - Moni Naor; Kobbi Nissim; Uri Stemmer; Chao Yan (NeurIPS, 2023)

Adaptive Data Analysis in a Balanced Adversarial Model. - Kobbi Nissim; Uri Stemmer; Eliad Tsfadia (NeurIPS, 2023)

On Differentially Private Online Predictions. - Haim Kaplan; Yishay Mansour; Shay Moran; Kobbi Nissim; Uri Stemmer (CoRR, 2023)

Doquet: Differentially Oblivious Range and Join Queries with Private Data Structures. - Lina Qiu; Georgios Kellaris; Nikos Mamoulis; Kobbi Nissim; George Kollios (Proc. VLDB Endow., 2023)

We Need to Focus on How Our Data Is Used, Not Just How It Is Shared. - Katrina Ligett; Kobbi Nissim (Commun. ACM, 2023)

Credit Attribution and Stable Compression. - Roi Livni; Shay Moran; Kobbi Nissim; Chirag Pabbaraju (NeurIPS, 2024)

From Isolation to Identification. - Giuseppe D'Acquisto; Aloni Cohen; Maurizio Naldi; Kobbi Nissim (PSD, 2024)

Properties of Effective Information Anonymity Regulations. - Aloni Cohen; Micah Altman; Francesca Falzon; Evangelina Anna Markatou; Kobbi Nissim (CoRR, 2024)

Launching the Society for Privacy and Confidentiality Research to Own the Journal of Privacy and Confidentiality. - John M. Abowd; Cynthia Dwork; Alan F. Karr; Kobbi Nissim; Jerome P. Reiter; Aleksandra B. Slavkovic; Lars Vilhuber (J. Priv. Confidentiality, 2024)

On the Rival Nature of Data: Tech and Policy Implications. - Ayelet Gordon-Tapiero; Katrina Ligett; Kobbi Nissim (CSLAW, 2025)

Data Reconstruction: When You See It and When You Don't. - Edith Cohen; Haim Kaplan; Yishay Mansour; Shay Moran; Kobbi Nissim; Uri Stemmer; Eliad Tsfadia (ITCS, 2025)

Differentially Private Quasi-Concave Optimization: Bypassing the Lower Bound and Application to Geometric Problems. - Kobbi Nissim; Eliad Tsfadia; Chao Yan (CoRR, 2025)

Bayesian Perspective on Memorization and Reconstruction. - Haim Kaplan; Yishay Mansour; Kobbi Nissim; Uri Stemmer (CoRR, 2025)