Ashwinkumar Venkatanaga Machanavajjhala

Journal article Journal of Privacy and Confidentiality · January 1, 2026 We develop formal privacy mechanisms for releasing statistics from data with many outlying values, such as income data. These mechanisms ensure that a per-record differential privacy guarantee degrades slowly in the protected records’ influence on the stat ... Full text Cite

Differentially private explanations for aggregate query answers

Journal article VLDB Journal · March 1, 2025 Differential privacy (DP) is the state-of-the-art and rigorous notion of privacy for answering aggregate database queries while preserving the privacy of sensitive information in the data. In today’s era of data analysis, however, it poses new challenges f ... Full text Cite

R2T: Instance-Optimal Truncation for Differentially Private Query Evaluation with Foreign Ke

Journal article Communications of the ACM · March 1, 2025 Answering SPJA queries under differential privacy (DP), including graph-pattern counting under node-DP as an important special case, has received considerable attention in recent years. The dual challenge of foreign-key constraints and self-joins is partic ... Full text Cite

Instance-optimal Truncation for Differentially Private Query Evaluation with Foreign Keys

Journal article ACM Transactions on Database Systems · November 8, 2024 Answering SPJA queries under differential privacy (DP), including graph pattern counting under node-DP as an important special case, has received considerable attention in recent years. The dual challenge of foreign-key constraints combined with self-joins ... Full text Cite

HDMM: OPTIMIZING ERROR OF HIGH-DIMENSIONAL STATISTICAL QUERIES UNDER DIFFERENTIAL PRIVACY

Journal article Journal of Privacy and Confidentiality · August 31, 2023 In this work we describe the High-Dimensional Matrix Mechanism (HDMM), a differentially private algorithm for answering a workload of predicate counting queries. HDMM represents query workloads using a compact implicit matrix representation and exploits th ... Full text Cite

R2T: Instance-optimal Truncation for Differentially Private Query Evaluation with Foreign Keys

Journal article SIGMOD Record · June 8, 2023 Answering SPJA queries under differential privacy (DP), including graph pattern counting under node-DP as an important special case, has received considerable attention in recent years. The dual challenge of foreign-key constraints and self-joins is partic ... Full text Cite

Longshot: Indexing Growing Databases using MPC and Differential Privacy

Journal article Proceedings of the VLDB Endowment · January 1, 2023 In this work, we propose Longshot, a novel design for secure outsourced database systems that supports ad-hoc queries through the use of secure multi-party computation and differential privacy. By combining these two techniques, we build and maintain data ... Full text Cite

DP-PQD: Privately Detecting Per-Query Gaps In Synthetic Data Generated By Black-Box Mechanisms

Journal article Proceedings of the VLDB Endowment · January 1, 2023 Synthetic data generation methods, and in particular, private synthetic data generation methods, are gaining popularity as a means to make copies of sensitive databases that can be shared widely for research and data analysis. Some of the fundamental opera ... Full text Cite

Transitioning from testbeds to ships: an experience study in deploying the TIPPERS Internet of Things platform to the US Navy

Journal article Journal of Defense Modeling and Simulation · July 1, 2022 This paper describes the collaborative effort between privacy and security researchers at nine different institutions along with researchers at the Naval Information Warfare Center to deploy, test, and demonstrate privacy-preserving technologies in creatin ... Full text Cite

Multi-Analyst Differential Privacy for Online Query Answering

Journal article Proceedings of the VLDB Endowment · January 1, 2022 Most differentially private mechanisms are designed for the use of a single analyst. In reality, however, there are often multiple stake-holders with different and possibly conflicting priorities that must share the same privacy loss budget. This motivates ... Full text Cite

Equity and Privacy: More Than Just a Tradeoff

Journal article IEEE Security and Privacy · November 1, 2021 Full text Cite

DP-cryptography: Marrying Differential Privacy and Cryptography in Emerging Applications

Journal article Communications of the ACM · February 1, 2021 Full text Cite

Computing Local Sensitivities of Counting Queries with Joins

Journal article Proceedings of the ACM SIGMOD International Conference on Management of Data · June 14, 2020 Local sensitivity of a query Q given a database instance D, i.e. how much the output Q(D) changes when a tuple is added to D or deleted from D, has many applications including query analysis, outlier detection, and differential privacy. However, it is NP-h ... Full text Cite

ϵKtelo: A framework for defining differentially private computations

Journal article ACM Transactions on Database Systems · February 1, 2020 The adoption of differential privacy is growing, but the complexity of designing private, efficient, and accurate algorithms is still high. We propose a novel programming framework and system, ϵktelo, for implementing both existing and new privacy algorith ... Full text Cite

εktelo: A Framework for Defining Differentially-Private Computations

Journal article SIGMOD Record · November 5, 2019 The adoption of differential privacy is growing but the complexity of designing private, efficient and accurate algorithms is still high. We propose a novel programming framework and system, εktelo, for implementing both existing and new privacy algorithms ... Full text Cite

RELEASING EARNINGS DISTRIBUTIONS USING DIFFERENTIAL PRIVACY: DISCLOSURE AVOIDANCE SYSTEM FOR POST-SECONDARY EMPLOYMENT OUTCOMES (PSEO)

Journal article Journal of Privacy and Confidentiality · October 23, 2019 The U.S. Census Bureau recently released data on earnings percentiles of grad-uates from post-secondary institutions. This paper describes and evaluates the disclosure avoidance system developed for these statistics. We propose a differentially private alg ... Full text Cite

Is my model any good: differentially private regression diagnostics

Journal article Knowledge and Information Systems · January 1, 2018 Linear and logistic regression are popular statistical techniques for analyzing multi-variate data. Typically, analysts do not simply posit a particular form of the regression model, estimate its parameters, and use the results for inference or prediction. ... Full text Cite

A Framework for Sharing Confidential Research Data, Applied to Investigating Differential Pay by Race in the U. S. Government

Journal article · June 2017 Cite

Designing statistical privacy for your data

Journal article Communications of the ACM · March 1, 2015 Preparing data for public release requires significant attention to fundamental principles of privacy. If a privacy definition is chosen wisely by the data curator, the sensitive information will be protected. Algorithms that satisfy the spec are called pr ... Full text Cite

Privacy preserving interactive record linkage (PPIRL).

Journal article Journal of the American Medical Informatics Association : JAMIA · March 2014 ObjectiveRecord linkage to integrate uncoordinated databases is critical in biomedical research using Big Data. Balancing privacy protection against the need for high quality record linkage requires a human-machine hybrid system to safely manage u ... Full text Cite

Pufferfish: A framework for mathematical privacy definitions

Journal article ACM Transactions on Database Systems · January 1, 2014 In this article, we introduce a new and general privacy framework called Pufferfish. The Pufferfish framework can be used to create new privacy definitions that are customized to the needs of a given application. The goal of Pufferfish is to allow experts ... Full text Cite

Social genome: Putting big data to work for population informatics

Journal article Computer · January 1, 2014 Data-intensive research using distributed, federated, person-level datasets in near real time has the potential to transform social, behavioral, economic, and health sciences - but issues around privacy, confidentiality, access, and data integration have s ... Full text Cite

Blowfish privacy: Tuning privacy-utility trade-offs using policies

Journal article Proceedings of the ACM SIGMOD International Conference on Management of Data · January 1, 2014 Privacy definitions provide ways for trading-off the privacy of individuals in a statistical database for the utility of downstream analysis of the data. In this paper, we present Blowfish, a class of privacy definitions inspired by the Pufferfish framewor ... Full text Cite

MarkIt: Privacy markers for protecting visual secrets

Journal article Ubicomp 2014 Adjunct Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing · January 1, 2014 The increasing popularity of wearable devices that continuously capture video, and the prevalence of third-party applications that utilize these feeds have resulted in a new threat to privacy. In many situations, sensitive objects/regions are maliciously ( ... Full text Cite

Finding connected components in map-reduce in logarithmic rounds

Journal article Proceedings International Conference on Data Engineering · August 15, 2013 Given a large graph G = (V, E) with millions of nodes and edges, how do we compute its connected components efficiently? Recent work addresses this problem in map-reduce, where a fundamental trade-off exists between the number of map-reduce rounds and the ... Full text Cite

Curso: Protect yourself from curse of attribute inference: A social network privacy-analyzer

Journal article Proceedings of the ACM SIGMOD Workshop on Databases and Social Networks Dbsocial 2013 · July 26, 2013 While social networking platforms allow users to control how their private information is shared, recent research has shown that a user's sensitive attribute can be inferred based on friendship links and group memberships, even when the attribute value is ... Cite

Sparsi: Partitioning sensitive data amongst multiple adversaries

Journal article Proceedings of the VLDB Endowment · January 1, 2013 We present SPARSI, a novel theoretical framework for partitioning sensitive data across multiple non-colluding adversaries. Most work in privacy-aware data sharing has considered disclosing summaries where the aggregate information about the data is preser ... Full text Cite

An automatic blocking mechanism for large-scale de-duplication tasks

Journal article ACM International Conference Proceeding Series · December 19, 2012 De-duplication - identification of distinct records referring to the same real-world entity - is a well-known challenge in data integration. Since very large datasets prohibit the comparison of every pair of records, blocking has been identified as a techn ... Full text Cite

Challenges in enabling social application at scale clouddb'12 invited-keynote talk

Journal article International Conference on Information and Knowledge Management Proceedings · December 10, 2012 Internet users spend billions of minutes per month on so- cial networking sites like Facebook, LinkedIn and Twitter. Not only do they create tons of data everyday in the form of posts, tweets and photos, the connections between users have given rise to new ... Full text Cite

A rigorous and customizable framework for privacy

Journal article Proceedings of the ACM SIGACT SIGMOD SIGART Symposium on Principles of Database Systems · May 21, 2012 In this paper we introduce a new and general privacy framework called Pufferfish. The Pufferfish framework can be used to create new privacy definitions that are customized to the needs of a given application. The goal of Pufferfish is to allow experts in ... Full text Cite

Information integration over time in unreliable and uncertain environments

Journal article Www 12 Proceedings of the 21st Annual Conference on World Wide Web · May 16, 2012 Often an interesting true value such as a stock price, sports score, or current temperature is only available via the observations of noisy and potentially conflicting sources. Several techniques have been proposed to reconcile these conflicts by computing ... Full text Cite

Publishing search logs - A comparative study of privacy guarantees

Journal article IEEE Transactions on Knowledge and Data Engineering · February 6, 2012 Search engine companies collect the database of intentions, the histories of their users' search queries. These search logs are a gold mine for researchers. Search engine companies, however, are wary of publishing search logs in order not to disclose sensi ... Full text Cite

An analysis of structured data on the web

Journal article Proceedings of the VLDB Endowment · January 1, 2012 In this paper, we analyze the nature and distribution of structured data on the Web. Web-scale information extraction, or the problem of creating structured tables using extraction from the entire web, is gathering lots of research interest. We perform a s ... Full text Cite

Entity resolution: Theory, practice & open challenges

Journal article Proceedings of the VLDB Endowment · January 1, 2012 This tutorial brings together perspectives on ER from a variety of fields, including databases, machine learning, natural language processing and information retrieval, to provide, in one setting, a survey of a large body of work. We discuss both the pract ... Full text Cite

Preface

Journal article Proceedings IEEE International Conference on Data Mining Icdm · December 1, 2011 Full text Cite

Highly efficient algorithms for structural clustering of large websites

Journal article Proceedings of the 20th International Conference on World Wide Web Www 2011 · December 1, 2011 In this paper, we present a highly scalable algorithm for structurally clustering webpages for extraction. We show that, using only the URLs of the webpages and simple content features, it is possible to cluster webpages effectively and efficiently. At the ... Full text Cite

Load balancing and range queries in P2P systems using P-ring

Journal article ACM Transactions on Internet Technology · March 1, 2011 In peer-to-peer (P2P) systems, computers from around the globe share data and can participate in distributed computation. P2P became famous, and infamous, due to file-sharing systems like Napster. However, the scalability and robustness of these systems ma ... Full text Cite

Personalized social recommendations accurate or private?

Journal article Proceedings of the VLDB Endowment · January 1, 2011 With the recent surge of social networks such as Facebook, new forms of recommendations have become possible - recommendationsthat rely on one's social connections in orderto make personalized recommendations of ads, content, products, and people. Since re ... Full text Cite

Sampling hidden objects using nearest-neighbor oracles

Journal article Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining · January 1, 2011 Given an unknown set of objects embedded in the Euclidean plane and a nearest-neighbor oracle, how to estimate the set size and other properties of the objects? In this paper we address this problem. We propose an efficient method that uses the Voronoi par ... Full text Cite

Feed following: The big data challenge in social applications

Journal article Workshop on Databases and Social Networks Dbsocial 11 · January 1, 2011 Internet users spend billions of minutes per month on sites like Facebook and Twitter. These sites support feed following, where users "follow" activity streams associated with other users and entities. Followers get personalized feeds that blend streams p ... Full text Cite

No free lunch in data privacy

Journal article Proceedings of the ACM SIGMOD International Conference on Management of Data · January 1, 2011 Differential privacy is a powerful tool for providing privacy-preserving noisy query answers over statistical databases. It guarantees that the distribution of noisy query answers changes very little with the addition or deletion of any tuple. It is freque ... Full text Cite

Collective extraction from heterogeneous web lists

Journal article Proceedings of the 4th ACM International Conference on Web Search and Data Mining Wsdm 2011 · January 1, 2011 Automatic extraction of structured records from inconsistently formatted lists on the web is challenging: different lists present disparate sets of attributes with variations in the ordering of attributes; many lists contain additional attributes and noise ... Full text Cite

Privacy in data publishing

Journal article Proceedings International Conference on Data Engineering · June 2, 2010 This tutorial gives an overview of techniques for releasing data about individuals while preserving privacy. © 2010 IEEE. ... Full text Cite

Privacy-Preserving Data Publishing

Journal article Foundations and Trends in Databases · December 31, 2009 Privacy is an important issue when one wants to make use of data that involves individuals' sensitive information. Research on protecting the privacy of individuals and the confidentiality of data has received contributions from many fields, including comp ... Full text Cite

Data Publishing against Realistic Adversaries

Journal article Proceedings of the VLDB Endowment · January 1, 2009 Privacy in data publishing has received much attention recently. The key to defining privacy is to model knowledge of the attacker - if the attacker is assumed to know too little, the published data can be easily attacked, if the attacker is assumed to kno ... Full text Cite

Privacy: Theory meets practice on the map

Journal article Proceedings International Conference on Data Engineering · October 1, 2008 In this paper, we propose the first formal privacy analysis of a data anonymization process known as the synthetic data generation, a technique becoming popular in the statistics community. The target application for this work is a mapping program that sho ... Full text Cite

Scalable ranked publish/subscribe

Journal article Proceedings of the VLDB Endowment · January 1, 2008 Publish/subscribe (pub/sub) systems are designed to efficiently match incoming events (e.g., stock quotes) against a set of subscriptions (e.g., trader profiles specifying quotes of interest). However, current pub/sub systems only support a simple binary n ... Full text Cite

Methodology for thermal aware topologies and partitioning with better lateral spreading

Journal article Proceedings of the International Conference on Microelectronics, ICM · 2008 As the temperature became a first class design metric due to increased power densities, one of the key challenges in deep sub-micron technologies is to guarantee thermal safety while minimizing the performance impact. This highlights the need for thermal-a ... Full text Cite

P-ring: An efficient and robust P2P range index structure

Journal article Proceedings of the ACM SIGMOD International Conference on Management of Data · October 30, 2007 Peer-to-peer systems have emerged as a robust, scalable and decentralized way to share and publish data. In this paper, we propose P-Ring, a new P2P index structure that supports both equality and range queries. P-Ring is fault-tolerant, provides logarithm ... Full text Cite

Worst-case background knowledge for privacy-preserving data publishing

Journal article Proceedings International Conference on Data Engineering · September 24, 2007 Recent work has shown the necessity of considering an attacker's background knowledge when reasoning about privacy in data publishing. However, in practice, the data publisher does not know what background knowledge the attacker possesses. Thus, it is impo ... Full text Cite

ℓ-Diversity: Privacy beyond k-anonymity

Journal article Proceedings International Conference on Data Engineering · October 17, 2006 Publishing data about individuals without revealing sensitive information about them is an important problem. In recent y ears, a new definition of privacy called k-anonymity has gained popularity. In a k-anonymized dataset, each record is indistinguishabl ... Full text Cite

On the efficiency of checking perfect privacy

Journal article Proceedings of the ACM SIGACT SIGMOD SIGART Symposium on Principles of Database Systems · June 26, 2006 Privacy-preserving query-answering systems answer queries while provably guaranteeing that sensitive information is kept secret. One very attractive notion of privacy is perfect privacy-a secret is expressed through a query QS, and a query Q Full text Cite

A storage and indexing framework for P2P systems

Journal article Thirteenth International World Wide Web Conference Proceedings Www2004 · December 1, 2004 We present a modularized storage and indexing framework that cleanly separates the functional components of a P2P system, enabling us to tailor the P2P infrastructure to the specific needs of various Internet applications. ... Cite

An indexing framework for peer-to-peer systems

Journal article Proceedings of the ACM SIGMOD International Conference on Management of Data · January 1, 2004 Full text Cite

On perfectly secure communication over arbitrary networks

Journal article Proceedings of the Annual ACM Symposium on Principles of Distributed Computing · July 21, 2002 We study the interplay of network connectivity and perfectly secure message transmission under the corrupting influence of generalized Byzantine adversaries. It is known that in the threshold adversary model, where the Byzantine adversary can corrupt upto ... Full text Cite

Preface

Journal article Clinics Atlas of Office Procedures · December 1, 2001 Cite

A security assurance framework for component based software development

Journal article Informatica Ljubljana · November 1, 2001 Commercial-off-the-shelf (COTS) components are black box software products. The absence of their code precludes them from any kind of inspection of certify that the code is safe. This increases the security risk for safety-sensitive applications. The appli ... Cite

Diversity!

Journal article Utah Law Review · 1992 Cite