Kobbi Nissim
#13,758
Most Influential Person Now
Israeli computer scientist
Kobbi Nissim's AcademicInfluence.com Rankings
Kobbi Nissimcomputer-science Degrees
Computer Science
#916
World Rank
#949
Historical Rank
Algorithms
#54
World Rank
#54
Historical Rank
Database
#100
World Rank
#103
Historical Rank
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Computer Science
Why Is Kobbi Nissim Influential?
(Suggest an Edit or Addition)According to Wikipedia, Kobbi Nissim is a computer scientist at Georgetown University, where he is the McDevitt Chair of Computer Science. His areas of research include cryptography and data privacy. He is known for the introduction of differential privacy.
Kobbi Nissim's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- Calibrating Noise to Sensitivity in Private Data Analysis (2006) (6218)
- Evaluating 2-DNF Formulas on Ciphertexts (2005) (1662)
- Efficient Private Matching and Set Intersection (2004) (1256)
- Revealing information while preserving privacy (2003) (1067)
- What Can We Learn Privately? (2008) (1029)
- Smooth sensitivity and sampling in private data analysis (2007) (985)
- Practical privacy: the SuLQ framework (2005) (880)
- Extending Oblivious Transfers Efficiently (2003) (651)
- Certificate revocation and certificate update (1998) (555)
- Firmato: a novel firewall management toolkit (1999) (418)
- Privacy-Preserving Datamining on Vertically Partitioned Databases (2004) (403)
- Analyzing Graphs with Node Differential Privacy (2013) (306)
- Efficient Communication-Storage Tradeoffs for Multicast Encryption (1999) (237)
- Algorithmic stability for adaptive data analysis (2015) (227)
- Generic Attacks on Secure Outsourced Databases (2016) (219)
- Practical Locally Private Heavy Hitters (2017) (216)
- Secure multiparty computation of approximations (2001) (199)
- Efficient Set Operations in the Presence of Malicious Adversaries (2010) (179)
- Bounds on the sample complexity for private learning and private data release (2010) (172)
- Distributed Private Data Analysis: On Simultaneously Solving How and What (2008) (170)
- The Privacy Blanket of the Shuffle Model (2019) (168)
- Simulatable auditing (2005) (165)
- Communication preserving protocols for secure function evaluation (2001) (163)
- Differentially Private Release and Learning of Threshold Functions (2015) (163)
- Private Learning and Sanitization: Pure vs. Approximate Differential Privacy (2013) (154)
- Differential Privacy: A Primer for a Non-Technical Audience (2018) (145)
- Approximately optimal mechanism design via differential privacy (2010) (145)
- GRECS: Graph Encryption for Approximate Shortest Distance Queries (2015) (111)
- Privacy-aware mechanism design (2011) (107)
- Private coresets (2009) (104)
- Impossibility of Differentially Private Universally Optimal Mechanisms (2010) (83)
- On the Security of Pay-per-Click and Other Web Advertising Schemes (1999) (82)
- Efficient Set Intersection with Simulation-Based Security (2014) (73)
- Simultaneous Private Learning of Multiple Concepts (2015) (67)
- Redrawing the boundaries on purchasing data from privacy-sensitive individuals (2014) (64)
- Characterizing the sample complexity of private learners (2013) (63)
- Private Summation in the Multi-Message Shuffle Model (2020) (55)
- Adaptive Learning with Robust Generalization Guarantees (2016) (53)
- Clustering Algorithms for the Centralized and Local Models (2017) (52)
- Bridging the Gap between Computer Science and Legal Approaches to Privacy (2018) (51)
- Towards formalizing the GDPR’s notion of singling out (2019) (48)
- PSI (Ψ): a Private data Sharing Interface (2016) (47)
- Private approximation of NP-hard functions (2001) (44)
- Differentially Private Summation with Multi-Message Shuffling (2019) (43)
- Locating a Small Cluster Privately (2016) (42)
- On the Generalization Properties of Differential Privacy (2015) (38)
- Is privacy privacy? (2018) (36)
- Communication Complexity and Secure Function Evaluation (2001) (36)
- Communication Efficient Secure Linear Algebra (2006) (34)
- Succinct Proofs for NP and Spooky Interactions (2004) (34)
- Accessing Data while Preserving Privacy (2017) (32)
- Private approximation of search problems (2006) (30)
- Approximating the minimum bisection size (extended abstract) (2000) (27)
- Hiding the Input-Size in Secure Two-Party Computation (2013) (25)
- On Cutting a Few Vertices from a Graph (2003) (24)
- Differential Privacy – A Primer for the Perplexed (2011) (24)
- Linear Program Reconstruction in Practice (2018) (23)
- Private Center Points and Learning of Halfspaces (2019) (23)
- Separating Adaptive Streaming from Oblivious Streaming Using the Bounded Storage Model (2021) (21)
- Learning Privately with Labeled and Unlabeled Examples (2014) (20)
- The Limits of Post-Selection Generalization (2018) (19)
- Private Data Analysis via Output Perturbation - A Rigorous Approach to Constructing Sanitizers and Privacy Preserving Algorithms (2008) (18)
- Improved Summation from Shuffling (2019) (18)
- Secure DisCSP Protocols – From Centralized Towards Distributed Solutions (2005) (18)
- Characterizing the Sample Complexity of Pure Private Learners (2019) (17)
- Dynamic algorithms against an adaptive adversary: generic constructions and lower bounds (2021) (15)
- What a Hybrid Legal-Technical Analysis Teaches Us About Privacy Regulation: The Case of Singling Out (2020) (14)
- Private Incremental Regression (2017) (12)
- The power of synergy in differential privacy: Combining a small curator with local randomizers (2019) (11)
- Separating Adaptive Streaming from Oblivious Streaming (2021) (11)
- On the hardness of approximating N P witnesses (2000) (10)
- How Should We Solve Search Problems Privately? (2007) (9)
- Private Approximation of Clustering and Vertex Cover (2007) (9)
- Concentration Bounds for High Sensitivity Functions Through Differential Privacy (2017) (9)
- Communication Versus Computation (2004) (9)
- The Complexity of Verifying Loop-Free Programs as Differentially Private (2019) (8)
- On the Round Complexity of the Shuffle Model (2020) (8)
- On Privacy in the Age of COVID-19 (2020) (8)
- Fair Information Sharing for Treasure Hunting (2015) (7)
- Integrating Approaches to Privacy Across the Research Lifecycle: When Is Information Purely Public? (2015) (7)
- Computational Two-Party Correlation: A Dichotomy for Key-Agreement Protocols (2018) (7)
- Hard Instances of the Constrained Discrete Logarithm Problem (2006) (6)
- Exploring Differential Obliviousness (2019) (6)
- Certiicate Revocation and Certiicate Update (1998) (6)
- εpsolute: Efficiently Querying Databases While Providing Differential Privacy (2017) (6)
- Privacy: From Database Reconstruction to Legal Theorems (2021) (6)
- Certi cate Revocation and Certi cate Update (2016) (5)
- Segmentation, Incentives and Privacy (2018) (4)
- Computational Two-Party Correlation (2018) (4)
- The Complexity of Verifying Circuits as Differentially Private (2019) (4)
- Denials leak information: Simulatable auditing (2013) (4)
- Data Protection's Composition Problem (2019) (3)
- Communication vs. Computation (2007) (3)
- Integrating Approaches to Privacy Across the Research Lifecycle: Long-Term Longitudinal Studies (2014) (3)
- Bounds on the sample complexity for private learning and private data release (2013) (2)
- Secure Multiparty Computation of Approximations (Extended Abstract) (2001) (2)
- Mechanism Design and Differential Privacy (2016) (2)
- Attacks on statistical databases: The highly noisy case (2013) (1)
- Efficient Set Operations in the Presence of Malicious Adversaries (2011) (1)
- The Sample Complexity of Distribution-Free Parity Learning in the Robust Shuffle Model (2021) (1)
- Opinions ∙ Data Protection’s Composition Problem (2019) (1)
- Privacy in public databases: A foundational approach (2005) (1)
- Modernizing Data Control: Making Personal Digital Data Mutually Beneficial for Citizens and Industry (2020) (1)
- Approximately Optimal Mechanism Design (2012) (1)
- First Issue Editorial (2009) (1)
- On Differentially Private Online Predictions (2023) (0)
- Efficient Set Intersection with Simulation-Based Security (2014) (0)
- Surveillance and privacy in the public and private sectors: panel (2019) (0)
- D S ] 1 3 M ar 2 01 7 Locating a Small Cluster Privately ∗ (2018) (0)
- Eecient Communication-storage Tradeoos for Multicast Encryption (2007) (0)
- Session details: Session 12B (2011) (0)
- Session details: Session 2B (2011) (0)
- Foundations for Robust Data Protection: Co-designing Law and Computer Science (2021) (0)
- Title : Mechanism Design and Differential Privacy Name : (2019) (0)
- Work : Exploring Differential Obliviousness (2019) (0)
- NCRN Meeting Spring 2017: Formal Privacy Models and Title 13 (2017) (0)
- A Principled Approach to Defining Anonymization As Applied to EU Data Protection Law (2022) (0)
- D S ] 2 J un 2 01 6 Adaptive Learning with Robust Generalization Guarantees (2018) (0)
- Role of concurrent chemoradiotherapy in organ preservation for locally advanced head and neck cancer. (2016) (0)
- How Auditors May Inadvertently Compromise Your Privacy (2008) (0)
- Session details: Session 1: 08:30--8:40 (2014) (0)
- Privacy (2021) (0)
- Usability Testing Plan and Educational Documents for Differential Privacy (2016) (0)
- Learning Privately with Labeled and Unlabeled Examples (2020) (0)
- Secure Remote Storage Using Oblivious RAM (2016) (0)
- Üøøòòòòò Ççððúúóù× Ìööò×××ö× Ae Blockin (2003) (0)
- A pr 2 01 6 Locating a Small Cluster Privately (2016) (0)
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What Schools Are Affiliated With Kobbi Nissim?
Kobbi Nissim is affiliated with the following schools:
