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Proceedings ArticleDOI

Privacy preserving error resilient dna searching through oblivious automata

TL;DR: A new error-resilient privacy-preserving string searching protocol that allows to execute any finite state machine in an oblivious manner, requiring a communication complexity which is linear both in the number of states and the length of the input string.
Abstract: Human Desoxyribo-Nucleic Acid (DNA) sequences offer a wealth of information that reveal, among others, predisposition to various diseases and paternity relations. The breadth and personalized nature of this information highlights the need for privacy-preserving protocols. In this paper, we present a new error-resilient privacy-preserving string searching protocol that is suitable for running private DNA queries. This protocol checks if a short template (e.g., a string that describes a mutation leading to a disease), known to one party, is present inside a DNA sequence owned by another party, accounting for possible errors and without disclosing to each party the other party's input. Each query is formulated as a regular expression over a finite alphabet and implemented as an automaton. As the main technical contribution, we provide a protocol that allows to execute any finite state machine in an oblivious manner, requiring a communication complexity which is linear both in the number of states and the length of the input string.
Citations
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Proceedings ArticleDOI
16 Oct 2012
TL;DR: In this paper, the authors provide a provable-security treatment for garbling schemes, endowing them with a versatile syntax and multiple security definitions, including privacy, obliviousness, and authenticity.
Abstract: Garbled circuits, a classical idea rooted in the work of Yao, have long been understood as a cryptographic technique, not a cryptographic goal. Here we cull out a primitive corresponding to this technique. We call it a garbling scheme. We provide a provable-security treatment for garbling schemes, endowing them with a versatile syntax and multiple security definitions. The most basic of these, privacy, suffices for two-party secure function evaluation (SFE) and private function evaluation (PFE). Starting from a PRF, we provide an efficient garbling scheme achieving privacy and we analyze its concrete security. We next consider obliviousness and authenticity, properties needed for private and verifiable outsourcing of computation. We extend our scheme to achieve these ends. We provide highly efficient blockcipher-based instantiations of both schemes. Our treatment of garbling schemes presages more efficient garbling, more rigorous analyses, and more modularly designed higher-level protocols.

483 citations

Journal ArticleDOI
TL;DR: This tutorial article introduces the fusion of signal processing and cryptography as an emerging paradigm to protect the privacy of users.
Abstract: In recent years, signal processing applications that deal with user-related data have aroused privacy concerns. For instance, face recognition and personalized recommendations rely on privacy-sensitive information that can be abused if the signal processing is executed on remote servers or in the cloud. In this tutorial article, we introduce the fusion of signal processing and cryptography as an emerging paradigm to protect the privacy of users. While service providers cannot access directly the content of the encrypted signals, the data can still be processed in encrypted form to perform the required signal processing task. The solutions for processing encrypted data are designed using cryptographic primitives like homomorphic cryptosystems and secure multiparty computation (MPC).

323 citations

Journal ArticleDOI
TL;DR: The most relevant PPDM techniques from the literature and the metrics used to evaluate such techniques are surveyed and typical applications of PPDD methods in relevant fields are presented.
Abstract: The collection and analysis of data are continuously growing due to the pervasiveness of computing devices. The analysis of such information is fostering businesses and contributing beneficially to the society in many different fields. However, this storage and flow of possibly sensitive data poses serious privacy concerns. Methods that allow the knowledge extraction from data, while preserving privacy, are known as privacy-preserving data mining (PPDM) techniques. This paper surveys the most relevant PPDM techniques from the literature and the metrics used to evaluate such techniques and presents typical applications of PPDM methods in relevant fields. Furthermore, the current challenges and open issues in PPDM are discussed.

223 citations

Book ChapterDOI
17 Sep 2010
TL;DR: This paper proposes a novel symmetric searchable encryption scheme that offers searching at constant time in the number of unique keywords stored on the server and presents two variants of the basic scheme which differ in the efficiency of search and storage.
Abstract: Searchable encryption is a technique that allows a client to store documents on a server in encrypted form. Stored documents can be retrieved selectively while revealing as little information as possible to the server. In the symmetric searchable encryption domain, the storage and the retrieval are performed by the same client. Most conventional searchable encryption schemes suffer from two disadvantages. First, searching the stored documents takes time linear in the size of the database, and/or uses heavy arithmetic operations. Secondly, the existing schemes do not consider adaptive attackers; a search-query will reveal information even about documents stored in the future. If they do consider this, it is at a significant cost to the performance of updates. In this paper we propose a novel symmetric searchable encryption scheme that offers searching at constant time in the number of unique keywords stored on the server. We present two variants of the basic scheme which differ in the efficiency of search and storage. We show how each scheme could be used in a personal health record system.

214 citations


Cites background from "Privacy preserving error resilient ..."

  • ...Searchable encryption has many applications, particularly where client privacy is a main concern such as in E-mail servers [4] (public setting), keeping medical information of a client [18] (public and symmetric setting), storing private videos and photos, and backup applications [17] (symmetric setting)....

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Posted Content
TL;DR: This paper begins to address genomic privacy by focusing on three important applications: Paternity Tests, Personalized Medicine, and Genetic Compatibility Tests, and proposes a set of efficient techniques based on private set operations that allow in in silico some operations that are currently performed via in vitro methods, in a secure fashion.
Abstract: Recent advances in DNA sequencing technologies have put ubiquitous availability of fully sequenced human genomes within reach. It is no longer hard to imagine the day when everyone will have the means to obtain and store one's own DNA sequence. Widespread and affordable availability of fully sequenced genomes immediately opens up important opportunities in a number of health-related fields. In particular, common genomic applications and tests performed in vitro today will soon be conducted computationally, using digitized genomes. New applications will be developed as genome-enabled medicine becomes increasingly preventive and personalized. However, this progress also prompts significant privacy challenges associated with potential loss, theft, or misuse of genomic data. In this paper, we begin to address genomic privacy by focusing on three important applications: Paternity Tests, Personalized Medicine, and Genetic Compatibility Tests. After carefully analyzing these applications and their privacy requirements, we propose a set of efficient techniques based on private set operations. This allows us to implement in in silico some operations that are currently performed via in vitro methods, in a secure fashion. Experimental results demonstrate that proposed techniques are both feasible and practical today.

214 citations

References
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Book
21 Oct 1957
TL;DR: The more the authors study the information processing aspects of the mind, the more perplexed and impressed they become, and it will be a very long time before they understand these processes sufficiently to reproduce them.
Abstract: From the Publisher: An introduction to the mathematical theory of multistage decision processes, this text takes a functional equation approach to the discovery of optimum policies. Written by a leading developer of such policies, it presents a series of methods, uniqueness and existence theorems, and examples for solving the relevant equations. The text examines existence and uniqueness theorems, the optimal inventory equation, bottleneck problems in multistage production processes, a new formalism in the calculus of variation, strategies behind multistage games, and Markovian decision processes. Each chapter concludes with a problem set that Eric V. Denardo of Yale University, in his informative new introduction, calls a rich lode of applications and research topics. 1957 edition. 37 figures.

14,187 citations

Book
01 Jan 1979
TL;DR: This book is a rigorous exposition of formal languages and models of computation, with an introduction to computational complexity, appropriate for upper-level computer science undergraduates who are comfortable with mathematical arguments.
Abstract: This book is a rigorous exposition of formal languages and models of computation, with an introduction to computational complexity. The authors present the theory in a concise and straightforward manner, with an eye out for the practical applications. Exercises at the end of each chapter, including some that have been solved, help readers confirm and enhance their understanding of the material. This book is appropriate for upper-level computer science undergraduates who are comfortable with mathematical arguments.

13,779 citations


"Privacy preserving error resilient ..." refers background in this paper

  • ...A deterministic finite automaton [11] (or finite state machine, FSM) is denoted by a 5-tuple M = (Q, Σ,∆, q0, F ), where Q is a finite set of states, Σ is a finite input alphabet, q0 ∈ Q is the initial state, F ⊆ Q is the set of final states, and ∆ denotes the transition function....

    [...]

Journal ArticleDOI
TL;DR: A computer adaptable method for finding similarities in the amino acid sequences of two proteins has been developed and it is possible to determine whether significant homology exists between the proteins to trace their possible evolutionary development.

11,844 citations