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Privacy Preserving Trajectory Data Publishing Via Differential Privacy
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Book Synopsis Privacy-preserving Trajectory Data Publishing Via Differential Privacy by : Ishita Dwivedi
Download or read book Privacy-preserving Trajectory Data Publishing Via Differential Privacy written by Ishita Dwivedi and published by . This book was released on 2017 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Over the past decade, the collection of data by individuals, businesses and government agencies has increased tremendously. Due to the widespread of mobile computing and the advances in location-acquisition techniques, an immense amount of data concerning the mobility of moving objects have been generated. The movement data of an object (e.g. individual) might include specific information about the locations it visited, the time those locations were visited, or both. While it is beneficial to share data for the purpose of mining and analysis, data sharing might risk the privacy of the individuals involved in the data. Privacy-Preserving Data Publishing (PPDP) provides techniques that utilize several privacy models for the purpose of publishing useful information while preserving data privacy. The objective of this thesis is to answer the following question: How can a data owner publish trajectory data while simultaneously safeguarding the privacy of the data and maintaining its usefulness? We propose an algorithm for anonymizing and publishing trajectory data that ensures the output is differentially private while maintaining high utility and scalability. Our solution comprises a twofold approach. First, we generalize trajectories by generalizing and then partitioning the timestamps at each location in a differentially private manner. Next, we add noise to the real count of the generalized trajectories according to the given privacy budget to enforce differential privacy. As a result, our approach achieves an overall epsilon-differential privacy on the output trajectory data. We perform experimental evaluation on real-life data, and demonstrate that our proposed approach can effectively answer count and range queries, as well as mining frequent sequential patterns. We also show that our algorithm is efficient w.r.t. privacy budget and number of partitions, and also scalable with increasing data size."--Boise State University ScholarWorks.
Book Synopsis Privacy-Preserving Data Publishing by : Bee-Chung Chen
Download or read book Privacy-Preserving Data Publishing written by Bee-Chung Chen and published by Now Publishers Inc. This book was released on 2009-10-14 with total page 183 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is dedicated to those who have something to hide. It is a book about "privacy preserving data publishing" -- the art of publishing sensitive personal data, collected from a group of individuals, in a form that does not violate their privacy. This problem has numerous and diverse areas of application, including releasing Census data, search logs, medical records, and interactions on a social network. The purpose of this book is to provide a detailed overview of the current state of the art as well as open challenges, focusing particular attention on four key themes: RIGOROUS PRIVACY POLICIES Repeated and highly-publicized attacks on published data have demonstrated that simplistic approaches to data publishing do not work. Significant recent advances have exposed the shortcomings of naive (and not-so-naive) techniques. They have also led to the development of mathematically rigorous definitions of privacy that publishing techniques must satisfy; METRICS FOR DATA UTILITY While it is necessary to enforce stringent privacy policies, it is equally important to ensure that the published version of the data is useful for its intended purpose. The authors provide an overview of diverse approaches to measuring data utility; ENFORCEMENT MECHANISMS This book describes in detail various key data publishing mechanisms that guarantee privacy and utility; EMERGING APPLICATIONS The problem of privacy-preserving data publishing arises in diverse application domains with unique privacy and utility requirements. The authors elaborate on the merits and limitations of existing solutions, based on which we expect to see many advances in years to come.
Book Synopsis Privacy for Location-based Services by : Gabriel Ghinita
Download or read book Privacy for Location-based Services written by Gabriel Ghinita and published by Morgan & Claypool Publishers. This book was released on 2013-04-01 with total page 87 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sharing of location data enables numerous exciting applications, such as location-based queries, location-based social recommendations, monitoring of traffic and air pollution levels, etc. Disclosing exact user locations raises serious privacy concerns, as locations may give away sensitive information about individuals' health status, alternative lifestyles, political and religious affiliations, etc. Preserving location privacy is an essential requirement towards the successful deployment of location-based applications. These lecture notes provide an overview of the state-of-the-art in location privacy protection. A diverse body of solutions is reviewed, including methods that use location generalization, cryptographic techniques or differential privacy. The most prominent results are discussed, and promising directions for future work are identified.
Book Synopsis PRICAI 2014: Trends in Artificial Intelligence by : Duc-Nghia Pham
Download or read book PRICAI 2014: Trends in Artificial Intelligence written by Duc-Nghia Pham and published by Springer. This book was released on 2014-11-12 with total page 1122 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 13th Pacific Rim Conference on Artificial Intelligence, PRICAI 2014, held in Gold Coast, Queensland, Australia, in December 2014. The 74 full papers and 20 short papers presented in this volume were carefully reviewed and selected from 203 submissions. The topics include inference; reasoning; robotics; social intelligence. AI foundations; applications of AI; agents; Bayesian networks; neural networks; Markov networks; bioinformatics; cognitive systems; constraint satisfaction; data mining and knowledge discovery; decision theory; evolutionary computation; games and interactive entertainment; heuristics; knowledge acquisition and ontology; knowledge representation, machine learning; multimodal interaction; natural language processing; planning and scheduling; probabilistic.
Book Synopsis Differential Privacy by : Ninghui Li
Download or read book Differential Privacy written by Ninghui Li and published by Morgan & Claypool Publishers. This book was released on 2016-10-26 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the last decade, differential privacy (DP) has emerged as the de facto standard privacy notion for research in privacy-preserving data analysis and publishing. The DP notion offers strong privacy guarantee and has been applied to many data analysis tasks. This Synthesis Lecture is the first of two volumes on differential privacy. This lecture differs from the existing books and surveys on differential privacy in that we take an approach balancing theory and practice. We focus on empirical accuracy performances of algorithms rather than asymptotic accuracy guarantees. At the same time, we try to explain why these algorithms have those empirical accuracy performances. We also take a balanced approach regarding the semantic meanings of differential privacy, explaining both its strong guarantees and its limitations. We start by inspecting the definition and basic properties of DP, and the main primitives for achieving DP. Then, we give a detailed discussion on the the semantic privacy guarantee provided by DP and the caveats when applying DP. Next, we review the state of the art mechanisms for publishing histograms for low-dimensional datasets, mechanisms for conducting machine learning tasks such as classification, regression, and clustering, and mechanisms for publishing information to answer marginal queries for high-dimensional datasets. Finally, we explain the sparse vector technique, including the many errors that have been made in the literature using it. The planned Volume 2 will cover usage of DP in other settings, including high-dimensional datasets, graph datasets, local setting, location privacy, and so on. We will also discuss various relaxations of DP.
Book Synopsis Introduction to Privacy-Preserving Data Publishing by : Benjamin C.M. Fung
Download or read book Introduction to Privacy-Preserving Data Publishing written by Benjamin C.M. Fung and published by CRC Press. This book was released on 2010-08-02 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gaining access to high-quality data is a vital necessity in knowledge-based decision making. But data in its raw form often contains sensitive information about individuals. Providing solutions to this problem, the methods and tools of privacy-preserving data publishing enable the publication of useful information while protecting data privacy. Int
Book Synopsis Hands-On Differential Privacy: Introduction to the Theory and Practice Using Opendp by : Ethan Cowan
Download or read book Hands-On Differential Privacy: Introduction to the Theory and Practice Using Opendp written by Ethan Cowan and published by O'Reilly Media. This book was released on 2024-04-30 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many organizations today analyze and share large, sensitive datasets about individuals. Whether these datasets cover healthcare details, financial records, or exam scores, it's become more difficult for organizations to protect an individual's information through deidentification, anonymization, and other traditional statistical disclosure limitation techniques. This practical book explains how differential privacy (DP) can help. Authors Ethan Cowan, Mayana Pereira, and Michael Shoemate explain how these techniques enable data scientists, researchers, and programmers to run statistical analyses that hide the contribution of any single individual. You'll dive into basic DP concepts and understand how to use open source tools to create differentially private statistics, explore how to assess the utility/privacy trade-offs, and learn how to integrate differential privacy into workflows. With this book, you'll learn: How DP guarantees privacy when other data anonymization methods don't What preserving individual privacy in a dataset entails How to apply DP in several real-world scenarios and datasets Potential privacy attack methods, including what it means to perform a reidentification attack How to use the OpenDP library in privacy-preserving data releases How to interpret guarantees provided by specific DP data releases
Book Synopsis Advances in Spatial and Temporal Databases by : Nikos Mamoulis
Download or read book Advances in Spatial and Temporal Databases written by Nikos Mamoulis and published by Springer Science & Business Media. This book was released on 2009-06-30 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the refereed proceedings of the 11th International Symposium on Spatial and Temporal Databases, SSTD 2009, held in Aalborg, Denmark, in July 2009. The 20 revised full papers presented together with 3 keynotes, 7 short papers, and 10 demonstration papers, were thoroughly reviewed and selected from a total of 62 research submissions and 11 demonstration submissions. The papers are organized in topical sections on spatial and flow networks, integrity and security, uncertain data and new technologies, indexing and monitoring moving objects, advanced queries, as well as on models and languages.
Download or read book Cyber Security written by Wei Lu and published by Springer Nature. This book was released on 2021-01-18 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book constitutes the refereed proceedings of the 16th International Annual Conference on Cyber Security, CNCERT 2020, held in Beijing, China, in August 2020. The 17 papers presented were carefully reviewed and selected from 58 submissions. The papers are organized according to the following topical sections: access control; cryptography; denial-of-service attacks; hardware security implementation; intrusion/anomaly detection and malware mitigation; social network security and privacy; systems security.
Book Synopsis Smart Computing and Communication by : Meikang Qiu
Download or read book Smart Computing and Communication written by Meikang Qiu and published by Springer Nature. This book was released on 2021-04-16 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 5th International Conference on Smart Computing and Communication, SmartCom 2020, which took place in Paris, France, during December 29-31, 2020. The 30 papers included in this book were carefully reviewed and selected from 162 submissions. The scope of SmartCom 2020 was broad, from smart data to smart communications, from smart cloud computing to smart security. The conference gathered all high-quality research/industrial papers related to smart computing and communications and aimed at proposing a reference guideline for further research.
Book Synopsis Privacy-preserving Genomic Data Publishing Via Differential Privacy by : Tanya Khatri
Download or read book Privacy-preserving Genomic Data Publishing Via Differential Privacy written by Tanya Khatri and published by . This book was released on 2018 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Privacy-preserving data publishing is a mechanism for sharing data while ensuring the privacy of individuals is preserved in the published data and utility is maintained for data mining and analysis. There is a huge need for sharing genomic data to advance medical and health research. However, since genomic data is highly sensitive and the ultimate identifier, it is a big challenge to publish genomic data while protecting the privacy of individuals in the data. In this thesis, we address the aforementioned challenge by presenting an approach for privacy-preserving genomic data publishing via differentially-private suffix tree. The proposed algorithm uses a top-down approach and utilizes Laplace mechanism to divide the raw genomic data into disjoint partitions, and then normalize the partitioning structure to ensure consistency and maintain utility. The output of our algorithm is a differentially-private suffix tree, a data structure most suitable for efficient search on genomic data. We experiment on real-life genomic data obtained from the Human Genome Privacy Challenge project, and we show that our approach is efficient, scalable, and achieves high utility with respect to genomic sequence matching count queries."--Boise State University ScholarWorks.
Book Synopsis Parallel Architectures, Algorithms and Programming by : Hong Shen
Download or read book Parallel Architectures, Algorithms and Programming written by Hong Shen and published by Springer Nature. This book was released on 2020-01-25 with total page 563 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 10th International Symposium on Parallel Architectures, Algorithms and Programming, PAAP 2019, held in Guangzhou, China, in December 2019. The 39 revised full papers and 8 revised short papers presented were carefully reviewed and selected from 121 submissions. The papers deal with research results and development activities in all aspects of parallel architectures, algorithms and programming techniques.
Book Synopsis Privacy in Statistical Databases by : Josep Domingo-Ferrer
Download or read book Privacy in Statistical Databases written by Josep Domingo-Ferrer and published by Springer Nature. This book was released on 2022-09-14 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the International Conference on Privacy in Statistical Databases, PSD 2022, held in Paris, France, during September 21-23, 2022. The 25 papers presented in this volume were carefully reviewed and selected from 45 submissions. They were organized in topical sections as follows: Privacy models; tabular data; disclosure risk assessment and record linkage; privacy-preserving protocols; unstructured and mobility data; synthetic data; machine learning and privacy; and case studies.
Book Synopsis Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security by : Indrajit Ray
Download or read book Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security written by Indrajit Ray and published by . This book was released on 2015-10-12 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: CCS'15: The 22nd ACM Conference on Computer and Communications Security Oct 12, 2015-Oct 16, 2015 Denver, USA. You can view more information about this proceeding and all of ACM�s other published conference proceedings from the ACM Digital Library: http://www.acm.org/dl.
Book Synopsis Recent Challenges in Intelligent Information and Database Systems by : Ngoc Thanh Nguyen
Download or read book Recent Challenges in Intelligent Information and Database Systems written by Ngoc Thanh Nguyen and published by Springer Nature. This book was released on 2023-09-28 with total page 638 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the second part of the proceedings of the 15th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2023, held in Phuket, Thailand, during July 24–26, 2023. The 50 full papers included in this book were carefully reviewed and selected from 224 submissions. They were organized in topical sections as follows: Computer Vision, Cybersecurity and Fraud Detection, Data Analysis, Modeling, and Processing, Data Mining and Machine Learning, Forecasting and Optimization Techniques, Healthcare and Medical Applications, Speech and Text Processing.
Book Synopsis Privacy-Preserving Data Mining by : Charu C. Aggarwal
Download or read book Privacy-Preserving Data Mining written by Charu C. Aggarwal and published by Springer Science & Business Media. This book was released on 2008-06-10 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in hardware technology have increased the capability to store and record personal data. This has caused concerns that personal data may be abused. This book proposes a number of techniques to perform the data mining tasks in a privacy-preserving way. This edited volume contains surveys by distinguished researchers in the privacy field. Each survey includes the key research content as well as future research directions of a particular topic in privacy. The book is designed for researchers, professors, and advanced-level students in computer science, but is also suitable for practitioners in industry.
Book Synopsis Differential Privacy and Applications by : Tianqing Zhu
Download or read book Differential Privacy and Applications written by Tianqing Zhu and published by Springer. This book was released on 2017-08-22 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on differential privacy and its application with an emphasis on technical and application aspects. This book also presents the most recent research on differential privacy with a theory perspective. It provides an approachable strategy for researchers and engineers to implement differential privacy in real world applications. Early chapters are focused on two major directions, differentially private data publishing and differentially private data analysis. Data publishing focuses on how to modify the original dataset or the queries with the guarantee of differential privacy. Privacy data analysis concentrates on how to modify the data analysis algorithm to satisfy differential privacy, while retaining a high mining accuracy. The authors also introduce several applications in real world applications, including recommender systems and location privacy Advanced level students in computer science and engineering, as well as researchers and professionals working in privacy preserving, data mining, machine learning and data analysis will find this book useful as a reference. Engineers in database, network security, social networks and web services will also find this book useful.
